Exploring the role of antecedents of product innovativeness and corporate social responsibility in extending customer citizenship behavior

In recent times, enhancing and extending the customer base is possible when organizations increase customer citizenship behavior among their consumers. Since the customers are much aware of firms’ social and environmental contributions thus, organizations take adequate measures to improve their product innovativeness and corporate social responsibility. Hence the current study is designed to ascertain the role of Corporate Social Responsibility (CSR) and product innovativeness in patronizing Customer Citizenship Behavior. Based on the survey research design, the current study applies structural equation modeling using Partial Least squares on the data set of 453 respondents. The results revealed that all proposed hypotheses were significant and positive. These findings imply that the service providers and manufacturers should increase transparency in the communication process through which CSR and innovativeness are effectively communicated to the customers, eventually assisting them in increasing their Customer Citizenship Behavior among customers. These results offer valuable policy insights

Inhibition of mast cell tryptase attenuates neuroinflammation via PAR-2/p38/NFκB pathway following asphyxial cardiac arrest in rats

Background: Cardiac arrest survivors suffer from neurological dysfunction including cognitive impairment. Cerebral mast cells, the key regulators of neuroinflammation contribute to neuroinflammation-associated cognitive dysfunction. Mast cell tryptase was demonstrated to have a proinflammatory effect on microglia via the activation of microglial protease-activated receptor-2 (PAR-2). This study investigated the potential anti-neuroinflammatory effect of mast cell tryptase inhibition and the underlying mechanism of PAR-2/p-p38/NFκB signaling following asphyxia-induced cardiac arrest in rats. Methods: Adult male Sprague-Dawley rats resuscitated from 10 min of asphyxia-induced cardiac arrest were randomized to four separate experiments including time-course, short-term outcomes, long-term outcomes and mechanism studies. The effect of mast cell tryptase inhibition on asphyxial cardiac arrest outcomes was examined after intranasal administration of selective mast cell tryptase inhibitor (APC366; 50 μg/rat or 150 μg/rat). AC55541 (selective PAR-2 activator; 30 μg/rat) and SB203580 (selective p38 inhibitor; 300 μg/rat) were used for intervention. Short-term neurocognitive functions were evaluated using the neurological deficit score, number of seizures, adhesive tape removal test, and T-maze test, while long-term cognitive functions were evaluated using the Morris water maze test. Hippocampal neuronal degeneration was evaluated by Fluoro-Jade C staining. Results: Mast cell tryptase and PAR-2 were dramatically increased in the brain following asphyxia-induced cardiac arrest. The inhibition of mast cell tryptase by APC366 improved both short- and long-term neurological outcomes in resuscitated rats. Such behavioral benefits were associated with reduced expressions of PAR-2, p-p38, NFκB, TNF-α, and IL-6 in the brain as well as less hippocampal neuronal degeneration. The anti-neuroinflammatory effect of APC366 was abolished by AC55541, which when used alone, indeed further exacerbated neuroinflammation, hippocampal neuronal degeneration, and neurologic deficits following cardiac arrest. The deleterious effects aggregated by AC55541 were minimized by p38 inhibitor. Conclusions: The inhibition of mast cell tryptase attenuated neuroinflammation, led to less hippocampal neuronal death and improved neurological deficits following cardiac arrest. This effect was at least partly mediated via inhibiting the PAR-2/p-p38/NFκB signaling pathway. Thus, mast cell tryptase might be a novel therapeutic target in the management of neurological impairment following cardiac arrest.United States Department of Health & Human Services National Institutes of Health (NIH) - USA (P01NS082184)Loma Linda University Neurosurgery Department Research Fun

Arabidopsis Hormone Database: a comprehensive genetic and phenotypic information database for plant hormone research in Arabidopsis

Plant hormones are small organic molecules that influence almost every aspect of plant growth and development. Genetic and molecular studies have revealed a large number of genes that are involved in responses to numerous plant hormones, including auxin, gibberellin, cytokinin, abscisic acid, ethylene, jasmonic acid, salicylic acid, and brassinosteroid. Here, we develop an Arabidopsis hormone database, which aims to provide a systematic and comprehensive view of genes participating in plant hormonal regulation, as well as morphological phenotypes controlled by plant hormones. Based on data from mutant studies, transgenic analysis and gene ontology (GO) annotation, we have identified a total of 1026 genes in the Arabidopsis genome that participate in plant hormone functions. Meanwhile, a phenotype ontology is developed to precisely describe myriad hormone-regulated morphological processes with standardized vocabularies. A web interface (http://ahd.cbi.pku.edu.cn) would allow users to quickly get access to information about these hormone-related genes, including sequences, functional category, mutant information, phenotypic description, microarray data and linked publications. Several applications of this database in studying plant hormonal regulation and hormone cross-talk will be presented and discussed

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Discrimination Algorithm and Procedure of Snow Depth and Sea Ice Thickness Determination Using Measurements of the Vertical Ice Temperature Profile by the Ice-Tethered Buoys

Snow depth and sea ice thickness in the Polar Regions are significant indicators of climate change and have been measured over several decades by ice-tethered buoys. However, sea ice temperature profiles measured by ice-tethered buoys are rarely used to infer snow depth and sea ice thickness owing to the lack of automatic discrimination algorithms, restricting the use of the data for sea ice thermodynamics studies. In this study, snow depth and sea ice thickness were retrieved through the measurements of sea ice temperature profiles using discrimination algorithms of the change point and the maximum likelihood detection methods. The data measured by 50 ice-tethered buoys were used to evaluate the accuracy of the results determined by the algorithm. Influences on the seasonal sea ice thermodynamic state, vertical interval of temperature sensors on the buoys, and initial ice thickness on the estimation errors were also evaluated. The performance of the discrimination algorithm for the data from the Arctic and Antarctic regions was also compared. There were no identifiable differences between the estimation errors from the Arctic and Antarctica. Increases in both the interval of the temperature sensors and the initial ice thickness enlarged the error for the estimation of ice thickness. A procedure developed in this study strengthens the potential application of measurements from the ice-tethered buoys only with the measurements of the vertical temperature profile of the layer of snow-covered ice, but not the measurements of ice basal and surface positions using acoustic sounding

Snow depth and sea ice thickness derived from the measurements of SIMBA buoys deployed in the Arctic Ocean during the Legs 1a, 1, and 3 of the MOSAiC campaign in 2019-2020

The Snow and Ice Mass Balance Array (SIMBA) is a thermistor string type IMB (Jackson et al., 2013) which measures the environment temperature SIMBA-ET and temperature change around the thermistors after a weak heating applied to each sensor (SIMBA-HT). Totally, there were 22 SIMBAs deployed in the Arcitic Ocean over the Distributed Network (DN) and the Central Observatory during the Legs 1a, 1 and 3 of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign. The SIMBA thermistor chain is 5.12 m long, and equipped with 256 thermistors (Maxim Integrated DS28EA00) at 0.02 m spacing. Based on a manual identification method, the SIMBA-ET and SIMBA-HT were processed to yield snow depth and ice thickness. Here, we combined the two optimal methods (the ET vertical gradient and HT rise ratio) to reduce the uncertainty. To keep the consistency, we use the snow or ice surface, consequentially the snow depth, determined by the ET vertical gradient. The formations of snow ice and superposed ice are not considered in this data set. That is to say, the value of snow depth includes the layers of snow ice at two sites (2019T56 and 2019T72). The superposed ice was generally negligible. We used the HT rise ratio to determine the ice-water interface, consequentially the ice thickness. Overall, the measurement accuracy was 0.02 m for both the snow depth and ice thickness. After the snow cover melted over, the negative values for the snow depth indicate the onset of ice surface melt. The submitted data package include 19 data files (for each buoy) and 1 buoy information file

Temperature and heating induced temperature difference measurements from SIMBA-type sea ice mass balance buoy 2019T58, deployed during MOSAiC 2019/20

Temperature and heating-induced temperature differences were measured along a chain of thermistors. SIMBA 2019T58 (a.k.a. FMI_05_09, IRIDIUM number 300234065171790) is an autonomous instrument that was installed on drifting sea ice in the Arctic Ocean during the 1st leg of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) in October 2019. The buoy was deployed at M4 site with initial thicknesses of snow and ice of 0.08 and 0.84 m, respectively, on 7 October 2019. The thermistor chain was 5 m long and included 241 sensors with a regular spacing of 2 cm. The depths for the sensors are 64 to -414 cm, referring to the initial interface between snow and ice. The last sensor was used to measure the air temperature at 1 m above the initial snow surface. The resulting time series describes the evolution of temperature and temperature differences after two heating cycles of 30 and 120 s as a function of depth and time between 7 October 2019 and 21 July 2020 in sample intervals of 6 hours for temperature and 24 hours for temperature differences. In addition to temperature, geographic position, barometric pressure, tilt and compass were measured

Temperature measurements from SIMBA-type sea ice mass balance buoy 2019T72

Temperature profile from atmosphere through snow and ice into the ocean

Temperature and heating induced temperature difference measurements from SIMBA-type sea ice mass balance buoy 2019T64, deployed during MOSAiC 2019/20

Temperature and heating-induced temperature differences were measured along a chain of thermistors. SIMBA 2019T64 (a.k.a. PRIC_09_03, IRIDIUM number 300234068701300) is an autonomous instrument that was installed on drifting sea ice in the Arctic Ocean during the 1st leg of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) in October 2019. The buoy was deployed at the M6 site with initial thicknesses of snow and ice of 0.16 and 1.74 m, respectively, on 10 October 2019. The thermistor chain was 5 m long and included 241 sensors with a regular spacing of 2 cm. The depths for the sensors are 68 to -410 cm, referring to the initial interface between snow and ice. The last sensor was used to measure the air temperature at 1 m above the initial snow surface. The resulting time series describes the evolution of temperature and temperature differences after two heating cycles of 30 and 120 s as a function of depth and time between 10 October 2019 and 2 August 2020 in sample intervals of 6 hours for temperature and 24 hours for temperature differences. In addition to temperature, geographic position, barometric pressure, tilt and compass were measured

Auxiliary data from SIMBA-type sea ice mass balance buoy 2019T64

Geographic position, barometric pressure, tilt and compass