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After digital platforms have become successful in the information technology (IT) industry, incumbents from traditional industries increasingly implement digital platform strategies. However, there is mixed evidence on whether these incumbents benefit from digital platform strategies. To provide systematic insights, we focus on the banking industry. With the emergence of open banking, banks have begun implementing digital platforms to unlock the innovative power of third-party developers. We conducted an event study based on the announcement of digital platform strategies in a global sample of 165 banks. We show that, on average, investors react positively to the announcements. Contrary to our expectations, this effect is more substantial for banks from emerging markets than those from developed markets. Prior artificial intelligence (AI) orientation only partly contributes to investors' favorable perception of a digital platform strategy. These results point to the complex interplay of AI orientation and digital platform strategies, yielding questions for future research. [ABSTRACT FROM AUTHOR]

Lamiaceae is one of the most economically important plant families based on their aromatic, medicinal, and industrial significance. In the present study three species of the Lamiaceae subfamily, Nepetoideae (Ocimum basillicum, Nepeta cateria, Leucas aspera) and one species from Lamioideae (Rosmarinus officinalis) were selected to document the pollinator bee diversity, foraging behavior, and their role on seed set. Thirty-two species of bees representing three families of Hymenoptera, (Apidae (94.87%) followed by Megachilidae (3.74%) and Halictidae (1.40%) were observed in all four plant species. Non-Apis bees were more abundant (69.35%) than Apis species (30.65%). The species-level variation in pollinator bees was observed in each plant species irrespective of space, time, and environmental conditions. O. basillicum attracted the maximum number of pollinator species (22) followed by R. officinalis (14) and L. aspera (10) and N. cataria (5). In O. basillicum, Ceratina species were major flower visitors, whereas R. officinalis was mainly visited by both Ceratina and Apis sp. L. aspera was dominated by Amegilla species and N. cataria mostly visited by the Apis bee species. However, irrespective of the diversity, the abundance of pollinator activity mainly contributed to enhancing the maximum number of seeds set in each species up to 64% overall increase under open pollination compared to bagged conditions. Also, a significant reduction in the seed set percentage was observed in R. officinalis and L. aspera under bagged pollination conditions. This indicates the high dependency of Lamiaceae plants on bee pollinators to maintain their reproduction and regeneration activities. [ABSTRACT FROM AUTHOR]

Ecological risk assessments (ERAs) are crucial when developing national strategies to manage adverse effects from pesticide exposure to natural populations. Yet, estimating risk with surrogate species in controlled laboratory studies jeopardizes the ERA process because natural populations exhibit intraspecific variation within and across species. Here, we investigate the extent to which the ERA process underestimates the risk from pesticides on different species by conducting a meta‐analysis of all records in the ECOTOX Knowledgebase for honey bees and wild bees exposed to neonicotinoids. We found the knowledgebase is largely populated by acute lethality data on the Western honey bee and exhibits within and across species variation in LD50 up to 6 orders of magnitude from neonicotinoid exposure. We challenge the reliability of surrogate species as predictors when extrapolating pesticide toxicity data to wild pollinators and recommend solutions to address the (a)biotic interactions occurring in nature that make such extrapolations unreliable in the ERA process. [ABSTRACT FROM AUTHOR]

Bee declines pose a serious risk to agricultural sustainability, wild plant diversity, and the commercial bee industry, generating local and global concerns about bee health. Parasites, including micro‐parasites and macro‐parasites, negatively impact bee population dynamics. Management of parasites requires an understanding of the cyclic trends in prevalence and the factors impacting these patterns. In this study, we advance understanding of parasite epidemiology and transmission among members of the bee community toward the goal of improving predictability of parasite prevalence seasonally. Honey bees and bumble bees were collected throughout an active season and across multiple overwintering periods. These bees were molecularly tested for two common bee viruses—deformed wing virus (DWV) and black queen cell virus (BQCV)—and morphologically screened for Vairimorpha spp., nematodes, and parasitic flies to determine whether these parasites exhibit unique seasonal trends, if overwintering behavior impacts parasite survival, and how these patterns differ between honey bees and bumble bees. The results suggest consistent seasonal trends between honey bees and bumble bees; however, these trends are parasite‐specific. Honey bees consistently exhibited a higher magnitude of viral prevalence compared with bumble bees. Both honey bees and bumble bees reduced viral prevalence over the winter; however, only in bumble bees did this drop to negligible prevalence each spring. These data suggest that honey bees may have a larger impact on parasite transmission, as they pose to reinfect bees which otherwise would have very low prevalence each spring and sustain high levels of infection in communities year‐round. [ABSTRACT FROM AUTHOR]

Honeybees are the most critical pollinators providing key ecosystem services that underpin crop production and sustainable agriculture. Amidst a backdrop of rapid global change, this eusocial insect encounters a succession of stressors during nesting, foraging, and pollination. Ectoparasitic mites, together with vectored viruses, have been recognized as central biotic threats to honeybee health, while the spread of invasive giant hornets and small hive beetles also increasingly threatens colonies worldwide. Cocktails of agrochemicals, including acaricides used for mite treatment, and other pollutants of the environment have been widely documented to affect bee health in various ways. Additionally, expanding urbanization, climate change, and agricultural intensification often result in the destruction or fragmentation of flower‐rich bee habitats. The anthropogenic pressures exerted by beekeeping management practices affect the natural selection and evolution of honeybees, and colony translocations facilitate alien species invasion and disease transmission. In this review, the multiple biotic and abiotic threats and their interactions that potentially undermine bee colony health are discussed, while taking into consideration the sensitivity, large foraging area, dense network among related nestmates, and social behaviors of honeybees. [ABSTRACT FROM AUTHOR]

Pesticide use in agricultural landscapes creates environmental contamination that is heterogenous in space and time. Mobile organisms, such as bees, are exposed to multiple contamination sources when visiting patches that vary in the amount, timing and toxicity of pesticides used. Yet, environmental risk assessments (ERA) typically fail to consider this heterogeneity, in part because of the complexities of estimating exposure to different pesticides, and subsequent risk at organism‐relevant scales.We use pesticide assays of 269 bee‐collected pollen samples to understand the spatiotemporal variability of risk across a network of 41 field sites in southern Sweden. Observed bee pesticide risk is calculated based on compound‐specific residue quantifications in pollen and standardized toxicity data. We then compare the ability of three classes of landscape‐scale variables to predict this risk: (1) landscape composition and configuration metrics, (2) landscape load based on national pesticide use data and (3) predictions from a newly developed bee pesticide exposure model.Based on use data, 10 crops account for 81% of the total risk. We detected 49 pesticide compounds in bee‐collected pollen. Although herbicides and fungicides constitute the bulk of detected pesticides, both in frequency and amount quantified, unsurprisingly, insecticides contribute the most to risk.Landscape composition and configuration metrics did not predict observed pesticide risk, and interactions with bee species indicate taxa‐dependency in predictions. Landscape load predicted observed risk consistently between taxa. Risk estimates from our exposure model were strongly predictive but only when considering realized risk (i.e., risk estimates based on prior pesticide use information).Synthesis and applications. Predicting pesticide risk based on landscape patterns could enable landscape‐scale ERA. However, simple metrics of landscape pattern, such as proportion of agricultural land, are not sufficient. We found that risk observed in bee‐collected pollen was best predicted when integrating spatialized pesticide use in the pesticide exposure model, underscoring the importance of such data for research, monitoring and mitigation. Further, we propose a guidance framework for future landscape ecotoxicological risk analyses that clarifies data needs relative to risk prediction goals. [ABSTRACT FROM AUTHOR]

A new TLC–densitometric method has been developed for the identification and quantification of paracetamol (PA), propyphenazone (PP) and caffeine (C) in Saridon tablets using the NP-TLC technique combined with densitometry. This method allows for the simultaneous determination of PA, PP, and C in the same sample. Among all the tested chromatographic conditions, the mixture consisting of chloroform + toluene + ethyl acetate + ethanol + acetic acid (18:18:7.5:5.0:0.3, v/v/v/v/v) and a silica gel 60F254 plate proved to be the most effective for the separation of the three tested active pharmaceutical ingredients (APIs) and substances related to paracetamol. The full validation of the proposed NP-TLC method proved that it is specific, precise, accurate, robust and sensitive. The percentage content in relation to the content declared by the manufacturer was for propyphenazone 99.8%, paracetamol 101.6% and caffeine 100.8%, which was in accordance with pharmacopoeial requirements. The results presented indicate the possibility of using the developed method in the routine control of pharmaceutical preparations containing these APIs. The proposed method is economical and more sensitive compared to the previously proposed planar methods for the simultaneous determination of APIs. What is more, the presented method may be an excellent economical alternative when the HPLC method is unavailable for such a determination. [ABSTRACT FROM AUTHOR]

Bees, as a distinguished lineage of hymenopteran insects, have undergone significant evolutionary adaptations, transitioning to a pollen-based provisioning strategy for their offspring and diverging from a reliance on prey. Within the intricate composition of bee products lies a myriad of chemicals that have garnered widespread recognition for their therapeutic and health-enhancing attributes. Bee venom, a constituent of apitherapy deeply embedded in traditional medicine with a millennia-long historical foundation, is a subject of considerable interest. Honeybees, among various bee species, manifest considerable, albeit variable, levels of antioxidant, antibacterial, and anticancer activities in their venom. This variability underscores the need for a comprehensive exploration of the diverse applications of bee venom. The present review, thus, seeks to systematically collate and analyze pertinent scientific literature, shedding light on the multifaceted roles of bee venom across various therapeutic domains. Moreover, the review evaluates the extant evidence supporting the therapeutic use of bee venom, identifying gaps and limitations within the existing body of research. By synthesizing recent advancements and critically examining the scientific landscape, this review contributes to the evolving understanding of bee venom bioactivities and offers a foundation for advancing their applications in contemporary therapeutic settings. [ABSTRACT FROM AUTHOR]

Potential genotoxic substances in medicines are of rising concern to pharmaceutical and regulatory authorities at detectable levels due to their potential to induce human carcinogenesis. Molecule functional groups may contribute to the genotoxicity of small molecules by converting starting materials and synthetic intermediates into reactive components. It is challenging for the pharmaceutical research and development analytical community to identify these genotoxic chemicals at trace levels without using susceptible and selective analytical methods. The literature currently needs more experimental advice for analyzing some significant contaminants. Analytical methods play a vital role in the pharmaceutical industry for monitoring and controlling impurities in drug products. These methods provide critical information on the final product's quality, purity, and efficacy by identifying unwanted substances such as degradation products, residual solvents, and process contaminants. The significance of analytical methods in pharmaceutical process impurities includes ensuring quality control, regulatory compliance, process optimization, troubleshooting, and batch release. These methods help to ensure that the final product meets the required specifications, complies with regulatory requirements, and provides the safe and effective patient treatment. The study analyses the structural alarms of commonly encountered likely genotoxic contaminants and draught regulations of various regulatory authorities to restrict the number of impurities in medicinal substances and to identify their toxicity. [ABSTRACT FROM AUTHOR]

Deep Eutectic Solvents (DESs) have appeared in recent years as an appealing alternative to classical organic solvents, due to their valuable environmental properties. In addition, these compounds, formed by the combination of one hydrogen bond donor with a hydrogen bond acceptor at a defined stoichiometric ratio, present other valuable activities not only as a reaction medium. DESs can also be employed as catalysts through hydrogen-bond interactions in different chemical transformations, thus substituting hazardous reagents and solvents. The search for novel and more environmentally friendly catalysts is an area of interest of pharmaceutical chemists, and therefore, the efforts made in the application of DESs as catalysts in the synthesis of APIs or its precursors are described, focusing mainly on condensations, nucleophilic additions to carbonyl moieties, and multicomponent reactions. [ABSTRACT FROM AUTHOR]

Healthy honey bee colonies follow predictable patterns of weight change through the season, gaining weight when resources are abundant and losing weight during periods of scarcity. Divergence from this pattern can indicate trouble in the colony, necessitating beekeeper intervention. While colony weight monitoring has long been used to evaluate colony progress and diagnose potential problems, research has been limited by the labor associated with manual weight measurements. The introduction of next generation colony weight monitoring permits the collection of hive weight data continuously and remotely, enhancing the range of questions that can be answered with these data. However, there is currently no central guide for researchers aiming to use hive scales in their research. Here, we review the literature and describe current methods used to process and analyze within-day, or diel, and seasonal colony weight changes. Diel weight dynamics are based around the circadian rhythm of the colony, resulting from the departure and arrival of foragers and the intake, consumption, and dehydration of food stores. Seasonal weight dynamics can be used to assess colony survival and productivity, often in relation to large-scale patterns of climate, landscape, and floral resource phenology. In addition to describing methods, we highlight future applications of hive weight monitoring, including monitoring weight across ecological gradients and physiological time, coupling of weight monitoring with other colony monitoring techniques, and the practical use of weight monitoring in commercial beekeeping operations. This paper serves as a tool for those wishing to conduct research using colony weight monitoring, and guides the future of remote weight monitoring in honey bee research. [ABSTRACT FROM AUTHOR]

In this article, we examine how critical thinking, methods and design are used within the tech industry, using Philip Agre's notion of critical technical practice (CTP) to consider the rise of 'cynical' technical practice. Arguments by tech firms that their AI systems are ethical, contextual, situated or fair, as well as APIs that are privacy-compliant and offer greater user control, are now commonplace. Yet, these justifications routinely disguise the organisational, and economic, reasons for the development of technical systems and features. The article considers how different forms of 'technical critique' are used by technical practitioners such as software engineers, applying Agre's work on CTP, AI planning, grammars of action and empowerment to evaluate, and contextualise these justifications. As Agre understood, technical practitioners are not necessarily 'a-critical' or 'uncritical' in their approach to the design of technological systems or methods, but ordinarily compare the utility or performance of such according to a golden ethic: 'does it work?'. Drawing on Agre's studies of AI in the 1990s, the article considers how and what Agre considered to be the 'Cartesian soul' of AI research, on linguistic structuralism, and continues to frame much work within the wider tech industry today. Yet increasingly, as the article shows, 'narrow' and cynical forms of technical criticality are being used to legitimise, and publicise, corporate strategies of tech firms, whether through the development of AI systems by automotive start-ups such as Comma, or the management of relations with external developers through APIs, in the case of Facebook. Rather than judging the moral character of technical practitioners, however, the article offers an approach – via the work of Philip Agre – to examine how critical thinking is used, and often abused, within and beyond the tech industry. [ABSTRACT FROM AUTHOR]

Bees are essential pollinators of many crops and wild plants, and pesticide exposure is one of the key environmental stressors affecting their health in anthropogenically modified landscapes. Until recently, almost all information on routes and impacts of pesticide exposure came from honey bees, at least partially because they were the only model species required for environmental risk assessments (ERAs) for insect pollinators. Recently, there has been a surge in research activity focusing on pesticide exposure and effects for non-Apis bees, including other social bees (bumble bees and stingless bees) and solitary bees. These taxa vary substantially from honey bees and one another in several important ecological traits, including spatial and temporal activity patterns, foraging and nesting requirements, and degree of sociality. In this article, we review the current evidence base about pesticide exposure pathways and the consequences of exposure for non-Apis bees. We find that the insights into non-Apis bee pesticide exposure and resulting impacts across biological organizations, landscapes, mixtures, and multiple stressors are still in their infancy. The good news is that there are many promising approaches that could be used to advance our understanding, with priority given to informing exposure pathways, extrapolating effects, and determining how well our current insights (limited to very few species and mostly neonicotinoid insecticides under unrealistic conditions) can be generalized to the diversity of species and lifestyles in the global bee community. We conclude that future research to expand our knowledge would also be beneficial for ERAs and wider policy decisions concerning pollinator conservation and pesticide regulation. [ABSTRACT FROM AUTHOR]

Assessing the relative contributions of different pollinator taxa to pollination services is a central task in both basic eco‐evolutionary research and applied conservation and agriculture. To that end, many studies have quantified single‐visit pollen deposition and visitation frequency, which together determine a pollinator species' rate of conspecific pollen delivery. However, for plant species that require or benefit from outcrossing, pollination service quality further depends upon the ratio of outcross to self‐pollen deposited, which is determined by two additional pollinator traits: pollen carryover and movement patterns among genetically compatible plant individuals. Here, we compare the pollination capacities of managed honey bees, native bumble bees, and native mining bees in apple—a varietally self‐incompatible commercial crop—when pollen carryover and pollinator movement patterns are considered. We constructed simulation models of outcross pollen deposition parameterized using empirically measured single‐visit pollen deposition, visitation frequency, and probabilities of intertree movement exhibited by each pollinator type, as well as pollen carryover patterns simulated based on parameters reported in the literature. In these models, we also explicitly specified the spatial relationships among cross‐compatible trees based on field‐realistic orchard layout schemes. We found that estimated pollination service delivery was considerably reduced for all pollinator types when pollen carryover and pollinator movement patterns were considered, as compared to when only single‐visit pollen deposition and visitation frequency were considered. We also found that the performance of different pollinator types varied greatly across simulated orchard layout schemes and pollen carryover scenarios, including one instance where bumble and mining bees reversed their relative rankings. In all simulations, native bumble and mining bees outperformed managed honey bees in terms of both outcross pollen delivery per unit time and per flower visited, with disparities being greatest under scenarios of low pollen carryover. We demonstrate the degree to which pollination studies may reach inaccurate conclusions regarding pollination service delivery when pollen carryover and pollinator movement patterns are ignored. Our finding of the strong context dependence of pollination efficiency, even within a single plant–pollinator taxon pair, cautions that future studies in both basic and applied pollination biology should explicitly consider the ecological context in which pollination interactions take place. [ABSTRACT FROM AUTHOR]

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Floral displays often signal the presence of nectar, but nectar may not always be present due to previous visits by nectarivores or temporal changes in nectar availability. But how does the presence of empty flowers impact the preferences of foraging honey bees for the available flowers? We aimed to test if previously rewarding flowers changed the preference relationship between neighboring flowers, and if empty flowers impacted overall visitation, in the honey bee Apis mellifera. Using artificial flowers, we showed that although empty flowers did not influence foraging choices in A. mellifera workers, empty flowers did increase movement between flowers in the patch. The presence of empty flowers also resulted in increased rates of patch abandonment. Our results suggest that while empty flowers may not directly impact foraging preferences in bees, they can have an impact on visitation within patches and in the surrounding area, with possible knock-on effects for the pollination of both the emptied flower and neighboring plants. [ABSTRACT FROM AUTHOR]

Identification of a plant's pollen components can be used to establish its geographical provenance, while also providing insights into the diet and foraging preferences of the honeybee (Apis mellifera L.). The diversity and amount of pollen represent crucial factors for pollinators. Here, we identified plant species visited by honeybees by analyzing the pollen pellets collected from honeybees in Kastoria, Greece. The results indicate that pollen from different periods was identified by means of floral composition. An interesting observation is that all identified plants belonged to different genera. Among the identified plants, native ones, such as the Macedonian pine, Pinus peuce, present a distinct foraging profile for local honeybees. [ABSTRACT FROM AUTHOR]

We examine phylogenetic relationships among species and populations of Asian cavity-nesting honeybees, emphasizing detection of potential unrecognized species in the geographically widespread Apis cerana Fabricius (Hymenoptera, Apidae). We carried out a phylogenetic analysis of genome-wide single nucleotide polymorphisms (SNPs) using BEASTv1.8.4 and IQ-TREE 2. Our samples cover the largest geographic area and number of populations of Asian cavity-nesting honey bees sampled to date. We used STRUCTURE, Bayes Factor Delimitation, and discriminant analysis of principal components to infer probable species among populations of cavity-nesting honeybees currently recognized as Apis cerana. Our results support 4 species within A. cerana : the yellow "plains" honeybee of India and Sri Lanka; the lineage inhabiting the oceanic Philippine islands; the Sundaland lineage found in Indonesia, Malaysia, and parts of southeast Asia; and a Mainland lineage, which we provisionally consider A. cerana in a narrow sense. [ABSTRACT FROM AUTHOR]

A new precise and accurate GC-ALS method was developed and validated for quantitative determination of hazardous high boiling solvents impurities i.e. acetic acid and dimethyl sulphoxide in Linagliptin drug molecule using direct injection technique by GC-ALS with the help of Flame ionization detector (FID). The column used was Agilent J & W DB-FFAP, 30M X 0.530 mm X 1μm capillary column. The stationary phase of the column was nitro terephthalic acid-modified polyethylene glycol (PEG). The method was validated for specificity, precision, LOD, LOQ, accuracy, linearity, range, solution stability, and robustness. The detection limit and quantitation limit obtained for acetic acid was 83.3 μg/g and 252.4 μg/g respectively. For Dimethyl sulphoxide detection limit and quantitation limit obtained were 83.7 μg/g and 253.7 μg/g respectively. The method was found to be linear in the range between 253.9 μg/g to 7616.9 μg/g for acetic acid and 253.5 μg/g to 7605.8 μg/g for dimethyl sulphoxide. The average recoveries obtained were 85.20% and 89.69% at LOQ level for acetic acid and dimethyl sulphoxide respectively, and for 150% level recovery were 94.26% and 100.43% for acetic acid and dimethyl sulphoxide respectively. The developed method was found to be robust, specificity was also demonstrated, and standard and the spiked solution was stable for up 20 Hrs. Thus, the method is used for routine analysis of their intended use. For quantification of Acetic acid and Dimethyl sulphoxide in Linagliptin, no pharmacopeial method is available so developed this simple method for laboratory use. [ABSTRACT FROM AUTHOR]

Novel transmission routes can allow infectious diseases to spread, often with devastating consequences. Ectoparasitic varroa mites vector a diversity of RNA viruses, having switched hosts from the eastern to western honey bees (Apis cerana to Apis mellifera). They provide an opportunity to explore how novel transmission routes shape disease epidemiology. As the principal driver of the spread of deformed wing viruses (mainly DWV-A and DWV-B), varroa infestation has also driven global honey bee health declines. The more virulent DWV-B strain has been replacing the original DWV-A strain in many regions over the past two decades. Yet, how these viruses originated and spread remains poorly understood. Here, we use a phylogeographic analysis based on whole-genome data to reconstruct the origins and demography of DWV spread. We found that, rather than reemerging in western honey bees after varroa switched hosts, as suggested by previous work, DWV-A most likely originated in East Asia and spread in the mid-20th century. It also showed a massive population size expansion following the varroa host switch. By contrast, DWV-B was most likely acquired more recently from a source outside East Asia and appears absent from the original varroa host. These results highlight the dynamic nature of viral adaptation, whereby a vector's host switch can give rise to competing and increasingly virulent disease pandemics. The evolutionary novelty and rapid global spread of these host-virus interactions, together with observed spillover into other species, illustrate how increasing globalization poses urgent threats to biodiversity and food security. [ABSTRACT FROM AUTHOR]

Blindspots in APIs can cause software engineers to introduce vulnerabilities, but such blindspots are, unfortunately, common. We study the effect APIs with blindspots have on developers in two languages by replicating a 109-developer, 24-Java-API controlled experiment. Our replication applies to Python and involves 129 new developers and 22 new APIs. We find that using APIs with blindspots statistically significantly reduces the developers’ ability to correctly reason about the APIs in both languages, but that the effect is more pronounced for Python. Interestingly, for Java, the effect increased with complexity of the code relying on the API, whereas for Python, the opposite was true. This suggests that Python developers are less likely to notice potential for vulnerabilities in complex code than in simple code, whereas Java developers are more likely to recognize the extra complexity and apply more care, but are more careless with simple code. Whether the developers considered API uses to be more difficult, less clear, and less familiar did not have an effect on their ability to correctly reason about them. Developers with better long-term memory recall were more likely to correctly reason about APIs with blindspots, but short-term memory, processing speed, episodic memory, and memory span had no effect. Surprisingly, professional experience and expertise did not improve the developers’ ability to reason about APIs with blindspots across both languages, with long-term professionals with many years of experience making mistakes as often as relative novices. Finally, personality traits did not significantly affect the Python developers’ ability to reason about APIs with blindspots, but less extroverted and more open developers were better at reasoning about Java APIs with blindspots. Overall, our findings suggest that blindspots in APIs are a serious problem across languages, and that experience and education alone do not overcome that problem, suggesting that tools are needed to help developers recognize blindspots in APIs as they write code that uses those APIs. [ABSTRACT FROM AUTHOR]

Simple Summary: In honey bees, drones disperse to specific locations in order to mate before returning to their natal nests. However, in apiaries of Apis mellifera, drones have been witnessed returning to non-natal nests; this behavior may also sometimes occur at natural nests. This behavior could be due to the unnaturally high density of nests in apiaries. In this study, we genotyped colonies of the Apis cerana honey bee collected in its invasive range of Far North Queensland, Australia, to determine whether there is evidence of drone drift between colonies. We found no such evidence of drone drift. Some drones that do not match the resident queen's genotype are instead likely due to queen turnover or worker reproduction. The modes through which individuals disperse prior to reproduction has important consequences for gene flow in populations. In honey bees (Apis sp.), drones (males) reproduce within a short flight range of their natal nest, leaving and returning each afternoon within a narrow mating window. Drones are assumed to return to their natal nests as they depend on workers to feed them. However, in apiaries, drones are reported to regularly make navigation errors and return to a non-natal nest, where they are accepted and fed by unrelated workers. If such a "drone drift" occurred in wild populations, it could facilitate some further degree of dispersal for males, particularly if drones drift into host nests some distance away from their natal nest. Here, we investigated whether drone drift occurs in an invasive population of the Asian honey bee (Apis cerana). Based on the genotypes of 1462 drones from 19 colonies, we found only a single drone that could be considered a candidate drifter (~0.07%). In three other colonies, drones whose genotypes differed from the inferred queen were best explained by recent queen turnover or worker-laying. We concluded that drone drift in this population is low at best, and A. cerana drones either rarely make navigation errors in wild populations or are not accepted into foreign nests when they do so. We therefore confirm that drone dispersal distance is limited to the distance of daily drone flights from natal nests, a key assumption of both colony density estimates based on sampling of drone congregation areas and population genetic models of gene flow in honey bees. [ABSTRACT FROM AUTHOR]

The microbiomes associated with bee nests influence colony health through various mechanisms, although it is not yet clear how honeybee congeners differ in microbiome assembly processes, in particular the degrees to which floral visitations and the environment contribute to different aspects of diversity. We used DNA metabarcoding to sequence bacterial 16S rRNA from honey and stored pollen from nests of 4 honeybee species (Apis cerana, A. dorsata, A. florea, and A. laboriosa) sampled throughout Yunnan, China, a global biodiversity hotspot. We developed a computational pipeline integrating multiple databases for quantifying key facets of diversity, including compositional, taxonomic, phylogenetic, and functional ones. Further, we assessed candidate drivers of observed microbiome dissimilarity, particularly differences in floral visitations, habitat disturbance, and other key environmental variables. Analyses revealed that microbiome alpha diversity was broadly equivalent across the study sites and between bee species, apart from functional diversity which was very low in nests of the reclusive A. laboriosa. Turnover in microbiome composition across Yunnan was driven predominantly by pollen composition. Human disturbance negatively impacted both compositional and phylogenetic alpha diversity of nest microbiomes, but did not correlate with microbial turnover. We herein make progress in understanding microbiome diversity associated with key pollinators in a biodiversity hotspot, and provide a model for the use of a comprehensive informatics framework in assessing pattern and drivers of diversity, which enables the inclusion of explanatory variables both subtly and fundamentally different and enables elucidation of emergent or unexpected drivers. [ABSTRACT FROM AUTHOR]

Introduction: The characterisation of active substances is an essential tool to ensure the traceability and authenticity of legal medicines. Metformin is a well-established biguanide derivative recommended in oral formulations as a first-line treatment for type 2 diabetes. With its increasing demand, metformin is likely to be an attractive target for falsification and substandard production, thus posing health risks to consumers. Methods that are able to identify even small differences in active pharmaceutical ingredients (APIs) are deemed necessary. The detection of fraudulent practices in APIs is not straightforward, and a single technique that can provide sufficient information to unambiguously address this issue is still not available. Methods: This study investigated an integrated analytical platform based on NIR, ¹H-NMR, 13C-NMR, and high-resolution LC-MS combined with chemometrics to profile 32 metformin hydrochloride samples originating from several global authorised manufacturers. The study's aim was to explore differences in the chemical characteristics of metformin hydrochloride APIs to identify or predict a possible classification for each manufacturer in view of prospective authenticity studies. Different pre-processing methods were applied; bucket tables for ¹H- and 13C-NMR were obtained, while mass spectrometry data were processed in targeted and untargeted modes. Datasets were individually analysed and merged by a multivariate unsupervised method and performing principal component analysis (PCA). Results and Discussion: The results evidenced differences in cluster behaviour, depending on manufacturers. Each technique has shown a specific clustering tendency, highlighting how different analytical approaches are able to characterise metformin APIs. Some manufacturers' samples, however, showed similar behaviour independently of the techniques. NIR and ¹H-NMR were confirmed as the more predictive techniques if taken individually; ¹H-NMR, in particular, achieved good separation between the samples of the two most representative manufacturers. For LC-MS, the targeted approach resulted in a separation in groups clearer than that of the untargeted approach. Nevertheless, the untargeted LC-MS approaches presented in this paper could be a possible alternative to obtaining different information for drug substances, with several different and complex synthetic pathways leading to several unknown impurities. Further grouping of manufacturers emerged by data fusion, highlighting its potential in the traceability of metformin. [ABSTRACT FROM AUTHOR]

Wound management represents a continuous challenge for health systems worldwide, considering the growing incidence of wound-related comorbidities, such as diabetes, high blood pressure, obesity, and autoimmune diseases. In this context, hydrogels are considered viable options since they mimic the skin structure and promote autolysis and growth factor synthesis. Unfortunately, hydrogels are associated with several drawbacks, such as low mechanical strength and the potential toxicity of byproducts released after crosslinking reactions. To overcome these aspects, in this study new smart chitosan (CS)-based hydrogels were developed, using oxidized chitosan (oxCS) and hyaluronic acid (oxHA) as nontoxic crosslinkers. Three active product ingredients (APIs) (fusidic acid, allantoin, and coenzyme Q10), with proven biological effects, were considered for inclusion in the 3D polymer matrix. Therefore, six API-CS-oxCS/oxHA hydrogels were obtained. The presence of dynamic imino bonds in the hydrogels' structure, which supports their self-healing and self-adapting properties, was confirmed by spectral methods. The hydrogels were characterized by SEM, swelling degree, pH, and the internal organization of the 3D matrix was studied by rheological behavior. Moreover, the cytotoxicity degree and the antimicrobial effects were also investigated. In conclusion, the developed API-CS-oxCS/oxHA hydrogels have real potential as smart materials in wound management, based on their self-healing and self-adapting properties, as well as on the benefits of APIs. [ABSTRACT FROM AUTHOR]

The ecosystem services offered by honey-producing bees are highly significant for the fertilization of flowers to produce fruits and seeds. The pollen found on bees and in honeycombs and honey represents the type of vegetation visited by the bees. The pollen diversity of honeycombs built by four honey-producing bees of the west coast and Western Ghats of India was evaluated to identify the floral sources. A spectrum of 54 pollen types (belonging to 52 genera in 34 families) was identified on the west coast, while 94 pollen types (belonging to 73 genera in 41 families) were identified in the Western Ghats. The results show that the bees of the four species on the west coast visited a limited number of plant species to gather nectar but included a higher quantity of total pollen of specific plant species. In the Western Ghats, the same species of bees visited more plant species but obtained lower quantities of pollen of specific plant species. This study shows that the honey-producing bees of the west coast and the Western Ghats prefer multifloral nectar for the production of honey. Floral resources for honey-producing bees are more diverse in the Western Ghats than on the west coast of India. Such differences might influence the quality (physical and nutraceutical) of honey produced by the bees in different geographic regions. [ABSTRACT FROM AUTHOR]

Honey bees facilitate pollination during their search for nectar and pollen and in the process promote fruit and seed formation. Yet, this honey bee facilitation has not been verified for Tanzania's seed crops such as sunflower. This study aimed to determine the diversity of sunflower pollinators and the contribution of honey bees on sunflower production. Thus, a field experiment was conducted in 2019 during the rainy and dry seasons. It involved three pollination environments: (i) Plots caged with honey bees, (ii) Plots caged without honey bees, and (iii) Open field plots. Polyethylene net with 0.4 mm size were used to build cages of 4 m × 5.5 m × 8 m whereas each plot had 75 plants. The plots were laid in Randomized Complete Block Design (RCBD) each with three replicates. Insect visitors to the open field plots were observed and recorded. In open plot treatment, there were 2,509 visitors representing four orders of Hymenoptera, Diptera, Lepidoptera and Coleoptera. Honey bees were the most frequent visiting insects accounting for 69.2%. The number and weight of abortive and filled sunflower seeds between treatments for both seasons were significantly different (p ≤ 0.0001). Plots caged without insects showed significantly lower filled seed numbers and weight (p < 0.001). However, treatments for plots caged with honey bees and open field showed no significant difference in seed numbers and weight (p > 0.05). Overall insect pollination contributed up to 97.7% of the total sunflower yield. In aaddition, pollination done by honey bees contributed to 87.4% of sunflower yield. Thus, the integration of honey bees in sunflower cultivation as pollinators ensures adequate pollination and production even when used as solely pollinators. [ABSTRACT FROM AUTHOR]

Nosema ceranae is a microsporidian that infects Apis species. Recently, natural compounds have been proposed to control nosemosis and reduce its transmission among honey bees. We investigated how ethanolic extract of Tetrigona apicalis's propolis and chito-oligosaccharide (COS) impact the health of N. ceranae-infected Apis dorsata workers. Nosema ceranae spores were extracted from the guts of A. florea workers and fed 106 spores dissolved in 2 µL 50% (w/v) sucrose solution to A. dorsata individually. These bees were then fed a treatment consisting either of 0% or 50% propolis extracts or 0 ppm to 0.5 ppm COS. We found that propolis and COS significantly increased the number of surviving bees and lowered the infection ratio and spore loads of N. ceranae-infected bees 14 days post-infection. Our results suggest that propolis extract and COS could be possible alternative treatments to reduce N. ceranae infection in A. dorsata. Moreover, N. ceranae isolated from A. florea can damage the ventricular cells of A. dorsata, thereby lowering its survival. Our findings highlight the importance of considering N. ceranae infections and using alternative treatments at the community level where other honey bee species can act as a reservoir and readily transmit the pathogen among the honey bee species. [ABSTRACT FROM AUTHOR]

The imagined universe of the people of Late Antiquity was heavily populated by gods. Even the broader philosophical trends and monotheistic foundation of Judaism and Christianity had failed to entirely diminish their power. How then did Jews and Christians cope with such a backdrop presence of "other gods"? Earlier research suggested that Jewish attitudes, which found their way into early Christian sources as well, fluctuate between accommodation and rejection. Following analysis of Jewish and Christian Late Antique literary traditions dealing with gods, and more specifically, goddesses, this essay aims to demonstrate that such "fluctuation" resulted - in addition to the extreme positions - in a variety of middle of the road strategies. These strategies point to a keen harmonizing impulse to absorb--via domestication--motifs with mythic religious vitality from the broader cultural repository. [ABSTRACT FROM AUTHOR]

Recent software advances have led to an expansion of the development and usage of application programming interfaces (APIs). From millions of Android packages (APKs) available on Google Store to millions of open-source packages available in Maven, PyPI, and npm, APIs have become an integral part of software development. Like any software artifact, software APIs evolve and suffer from this evolution. Prior research has uncovered many challenges to the development, usage, and evolution of APIs. While some challenges have been studied and solved, many remain. These challenges are scattered in the literature, which hides advances and cloaks the remaining challenges. In this systematic literature review on APIs and API evolution, we uncover and describe publication trends and trending topics.We compile common research goals, evaluation methods, metrics, and subjects.We summarize the current state-of-the-art and outline known existing challenges aswell as newchallenges uncovered during this review. We conclude that the main remaining challenges related to APIs and API evolution are (1) automatically identifying and leveraging factors that drive API changes, (2) creating and using uniform benchmarks for research evaluation, and (3) understanding the impact of API evolution on API developers and users with respect to various programming languages. [ABSTRACT FROM AUTHOR]

The Electronic Health Record has failed to meet its intended purpose. We propose a new approach focusing on the use of data for health and health care. The first step is to create a repository of all patient data with data storage independent of data use. All use functionality is external to data storage. We propose the development of a common data model in which data elements have a rich set of attributes including actionable knowledge. Finally, functionality is provided through a series of application program interfaces (API). New APIs will address directly new methods for using data to increase the effectiveness of data application to improve management of the health and care of a patient. Together these components will open a pathway to finally accomplish the goals of a better future health system. [ABSTRACT FROM AUTHOR]

Due to advances in electron microscopy and deep learning, it is now practical to reconstruct a connectome, a description of neurons and the chemical synapses between them, for significant volumes of neural tissue. Smaller past reconstructions were primarily used by domain experts, could be handled by downloading data, and performance was not a serious problem. But new and much larger reconstructions upend these assumptions. These networks now contain tens of thousands of neurons and tens ofmillions of connections, with yet larger reconstructions pending, and are of interest to a large community of non-specialists. Allowing other scientists to make use of this data needs more than publication--it requires new tools that are publicly available, easy to use, and efficiently handle large data. We introduce neuPrint to address these data analysis challenges. Neuprint contains two major components--a web interface and programmer APIs. The web interface is designed to allow any scientist worldwide, using only a browser, to quickly ask and answer typical biological queries about a connectome. The neuPrint APIs allow more computer-savvy scientists to make more complex or higher volume queries. NeuPrint also provides features for assessing reconstruction quality. Internally, neuPrint organizes connectome data as a graph stored in a neo4j database. This gives high performance for typical queries, provides access though a public and well documented query language Cypher, and will extend well to future larger connectomics databases. Our experience is also an experiment in open science.We find a significant fraction of the readers of the article proceed to examine the data directly. In our case preprints worked exactly as intended, with data inquiries and PDF downloads starting immediately after pre-print publication, and little affected by formal publication later. Fromthis we deduce that many readers are more interested in our data than in our analysis of our data, suggesting that data-only papers can be well appreciated and that public data release can speed up the propagation of scientific results bymanymonths. We also find that providing, and keeping, the data available for online access imposes substantial additional costs to connectomics research. [ABSTRACT FROM AUTHOR]

High levels of genetic diversity are critical to the success of breeding programs. Russian honey bees are a selected stock that undergoes breeding in a closed block-based mating system. Given its established history, Russian stock has longitudinal measures of genetic integrity (i.e., genetically based stock identity) and diversity. Assessments using genetic stock identification (GSI) have shown that genetic diversity parameters were assessed across breeding blocks for three generations, spanning 6 yr (2014, 2017, and 2020), showing levels comparable to those when the stock was initially released in 2008. Allelic richness (mean number of alleles) and gene diversity levels were consistent over time and among blocks. Blocks were generally not differentiated from one another within each year. However, the 2020 population was distinct when compared with bees sampled in both 2014 and 2017. Genetic distance relationships supported differentiation of the 2020 population by distinct clustering. The patterns observed here are consistent with historical changes made to the breeding program to increase stringency of the selection criteria. [ABSTRACT FROM AUTHOR]

Researchers, policymakers, and competition and regulation authorities worldwide recognize the utility of application programming interfaces (APIs) in powering the digital economy and driving datafication and platformization processes. However, it remains unclear how the APIs of leading social media relate to platform governance and how this relationship evolved. This article traces the evolution of Facebook's APIs, which evolved from a relatively simple programming interface for data access into a complex layered and interconnected governance arrangement. The study draws on a large corpus of (archived) developer pages and API reference documentation to examine the history of Facebook's API governance; that is, the governance of and by Facebook through its APIs. This historical analysis emphasizes the technical dimensions and dynamics of what, how, and whom powerful platforms seek to govern, thus highlighting the technicity of platform governance and how it evolved. Because APIs facilitate and govern the material conditions of app development and the social and economic processes they sustain, powerful platforms influence the evolution of their larger ecosystems. As such, the technicity of Facebook's API governance represents a major source of the platform's "infrastructural power." [ABSTRACT FROM AUTHOR]

Foraging rate of different pollinator species under the genus Apis and non-Apis studied on two castor (Ricinus communis) hybrid under agro-ecological conditions of Haryana, revealed that irrespective of interspecific variation, the maximum foraging rate was found associated with Apis florea followed by A. dorsata, A. cerana and A. mellifera. Further, Eristalnus sp. visits of flowers were the lowest. Adding to the visiting frequency, honey producing bees (Apis sp.) visited significantly more flower per unit time compared to other pollinators (non-Apis) species. The study gave an idea of different foraging rates of different pollinators on castor flower. © 2022 Association for Advancement of Entomology [ABSTRACT FROM AUTHOR]

This study utilized switchable solvent liquid-phase microextraction (SS-LPME) to enrich eleven nervous system active pharmaceutical ingredients (APIs) from aqueous samples for their determination at trace levels by gas chromatography mass spectrometry. The analytes selected for the study included APIs utilized in antidepressant, antipsychotic, antiepileptic, and anti-dementia drugs. Parameters of the microextraction method including switchable solvent volume, concentration and volume of the trigger agent (sodium hydroxide), and sample agitation period were optimized univariately to boost extraction efficiency. Under the optimum conditions, the detection limits calculated for the analytes were in the range of 0.20–8.0 ng/mL, and repeatability for six replicate measurements as indicated by percent relative standard deviation values were below 10%. Matrix matching calibration strategy was used to enhance quantification accuracy for the analytes. The percent recovery results calculated for the eleven analytes ranged between 86 and 117%. [ABSTRACT FROM AUTHOR]

Copyright of IWNW is the property of Ain Shams University, Faculty of Archaeology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Abanico Veterinario is the property of Sistema Superior Editorial and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objective: This study: 1) characterized the app market by EHR app gallery and type of app; 2) tracked changes in the EHR app galleries from the end of 2019 through 2020; and 3) examined how apps connect to EHR data systems, and if the apps support the HL7 FHIR standard.Materials and Methods: We developed a program that gathered data from the public app galleries hosted by Allscripts, athenahealth, Cerner Corporation, Epic Systems Corporation, and SMART. Data collection for this study began in December 2019 and ended December 2020. The program was run 11 times during this period, and the data collected were used to generate the findings and trends observed in this study.Results: The total number of unique apps increased from 600 to 734 during the study period. The most common types of apps marketed were intended for administrative (42%) and clinical use (38%). About 1 in 5 apps (22%) described support for the FHIR standard. Support for FHIR varied by intended functionality and gallery.Discussion: This study provides early insights into the number of third-party apps that are connecting to EHRs, what services they provide, and if these connections use standards-based application programming interfaces (APIs).Conclusion: It is a federal government priority to improve the access and use of electronic health information, including third-party apps that can introduce competition as well as best-of-breed functions and user experiences. This study shows that there is room for growth, and variation exists among some of the largest EHR developers. [ABSTRACT FROM AUTHOR]

Structure and function of the honey bee, Apis mellifera stinger is very well known. Nevertheless, we described two novel ultrastructural details at the end of the stinger using scanning electron microscopy. We found that the tips of the stinger lancets are not smooth; their edges are serrated and their surface contains numerous pits. We determined the height of the edge teeth to be approximately 0.16 ± 0.02 µm and the average width of the pits to range from 0.06 to 0.4 µm. We hypothesized these ultrastructures can cause more extensive tissue damage in victims and cut up more cell membranes than if their surfaces were smooth. The potential impact of such injury on the overall efficacy of the bee sting is discussed. [ABSTRACT FROM AUTHOR]

Bumblebees (Bombus) are charismatic and important pollinators. They are one of the best-studied insect groups, especially in terms of ecology, behavior, and social structure. As many species are declining, there is a clear need to understand more about them. Microbial symbionts, which can influence many dimensions of animal life, likely have an outsized role in bumblebee biology. Recent research has shown that a conserved set of beneficial gut bacterial symbionts is ubiquitous across bumblebees. These bacteria are related to gut symbionts of honeybees, but have not been studied as intensively. Here, we synthesize studies of bumblebee gut microbiota, highlight major knowledge gaps, and suggest future directions. Several patterns emerge, such as symbiont-host specificity maintained by sociality, frequent symbiont loss from individual bees, symbiont-conferred protection from trypanosomatid parasites, and divergence between bumblebee and honeybee microbiota in several key traits. For many facets of bumblebee–microbe interactions, however, underlying mechanisms and ecological functions remain unclear. Such information is important if we are to understand how bumblebees shape, and are shaped by, their gut microbiota. Bumblebees may prove a useful system for microbiome scientists, providing insights into general principles of host–microbe interactions. We also note how microbiota could influence bumblebee traits and responses to stressors. Finally, we propose that tinkering with the microbiota could be one way to aid bumblebee resilience in the face of global change. [ABSTRACT FROM AUTHOR]

As the availability of online data grows rapidly, researchers are confronted with a pressing question: How should social scientists collect Internet data for research? This study focuses on one of the most commonly used data collection techniques: web scraping. Going beyond canned approaches by leveraging a general framework of data communication, this study illustrates how online information can be systematically queried and fetched for reproducible research. To generalize our approaches, we additionally explore the variations in site security and architecture that analysts may encounter during the scraping process before they are given access to the desired data. The approaches we introduce do not rely on any proprietary software and can be easily implemented on any computing platform with programming languages such as Python or R. The methodological discussion in this study is meant to be applicable to current web-based research efforts. We include three examples with complete Python implementation. We also present an integrated workflow that enables researchers to produce analytical data sets that are traceable and thus verifiable for analysis or replication. Lastly, options related to the validity and efficiency of data are discussed, and we highlight the ongoing debate surrounding the ethics of online data collection, ultimately advocating for the fair use of online data. [ABSTRACT FROM AUTHOR]

Extensive development of games for various purposes including education and entertainment has resulted in increased development of game engines. Game engines are being used on a large scale as they support and simplify game development to a greater extent. Game developers using game engines are often compelled to use various application programming interfaces (APIs) of game engines in the process of game development. Thus, both quality and ease of development of games are greatly influenced by APIs defined in game engines. Hence, understanding API usability in game engines could greatly help in choosing better game engines among the ones that are available for game development and also could help developers in designing better game engines. In this article, we thus aim to evaluate API usability of 95 publicly available game engine repositories on GitHub, written primarily in C++ programming language. We test API usability of these game engines against the eight structural API usability metrics—AMNOI, AMNCI, AMGI, APXI, APLCI, AESI, ATSI, and ADI. We see this research as a first step toward the direction of improving usability of APIs in game engines. We present the results of the study, which indicate that about 25% of the game engines considered have minimal API usability, with respect to the considered metrics. It was observed that none of the considered repositories have ideal (all metric scores equal to 1) API usability, indicating the need for developers to consider API usability metrics while designing game engines. [ABSTRACT FROM AUTHOR]

The explosion in availability and variety of data requires learning experiences that reveal more of the data world faster and develop practical skills with digital technologies. Key high‐level goals of the International Data Science in Schools Project (IDSSP) include having students continually immersed in the cycle of learning from data, and data science being fun to teach and fun to learn. We advocate curiosity‐driven, exploratory learning for pursuing these goals. Our illustrations use tasks embedded in contexts that teenagers can relate to, provide visual rewards for computational actions, use rich data‐contexts, and integrate statistical and computational thinking. They provide engaging introductions to modern data sourced from databases via Application Programming Interfaces (APIs) that are accessible to a broad range of students and facilitate student personalization for investigation. We provide in‐depth discussion of teaching strategies that heavily involve questioning and student tinkering supported by graphical‐user interfaces that enable students to interact with the data sources rapidly in multiple ways. [ABSTRACT FROM AUTHOR]

The explosion in availability and variety of data requires learning experiences that reveal more of the data world faster and develop practical skills with digital technologies. Key high‐level goals of the International Data Science in Schools Project (IDSSP) include having students continually immersed in the cycle of learning from data, and data science being fun to teach and fun to learn. We advocate curiosity‐driven, exploratory learning for pursuing these goals. Our illustrations use tasks embedded in contexts that teenagers can relate to, provide visual rewards for computational actions, use rich data‐contexts, and integrate statistical and computational thinking. They provide engaging introductions to modern data sourced from databases via Application Programming Interfaces (APIs) that are accessible to a broad range of students and facilitate student personalization for investigation. We provide in‐depth discussion of teaching strategies that heavily involve questioning and student tinkering supported by graphical‐user interfaces that enable students to interact with the data sources rapidly in multiple ways. [ABSTRACT FROM AUTHOR]

India's import dependency for critical drug intermediates and active pharmaceutical ingredients (APIs) put questions on India's health and economic security. The quest for the solution lies in the self-sufficiency of the Indian pharmaceutical industry. Being a key investor, Japan appears to be a promising companion with its abundant capital and technical expertise in pharmaceuticals. This article aims to investigate how the current pandemic is going to offer opportunities and nurture the investment relations between the two giants of pharma sector. India and Japan both articulated new policies in response to reduced product supply from China amid the lockdown. India needs closer cooperation from Japan in pharmaceuticals to recover its fully integrated supply chain. The Covid-19 pandemic can be considered as an occasion for both the economies to magnify the interrelation and develop a new set of complementarities. [ABSTRACT FROM AUTHOR]

The explosion in availability and variety of data requires learning experiences that reveal more of the data world faster and develop practical skills with digital technologies. Key high-level goals of the International Data Science in Schools Project (IDSSP) include having students continually immersed in the cycle of learning from data, and data science being fun to teach and fun to learn. We advocate curiosity-driven, exploratory learning for pursuing these goals. Our illustrations use tasks embedded in contexts that teenagers can relate to, provide visual rewards for computational actions, use rich datacontexts, and integrate statistical and computational thinking. They provide engaging introductions to modern data sourced from databases via Application Programming Interfaces (APIs) that are accessible to a broad range of students and facilitate student personalization for investigation. We provide in-depth discussion of teaching strategies that heavily involve questioning and student tinkering supported by graphical-user interfaces that enable students to interact with the data sources rapidly in multiple ways. [ABSTRACT FROM AUTHOR]