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Communication and gender dynamics in agricultural innovation systems during the COVID-19 pandemic: a phenomenological study of sugarcane family farmers in Batangas, Philippines
No full textThe study investigated the communication and livelihood dynamics of selected
sugarcane farmers registered as members of the Sugarcane Block Farm System in ten
communities in Balayan and Calaca, Batangas, Philippines. The study: (1) examined
family farmers’ communication dynamics in relation to gender roles; (2) analysed the
process of co-creation of knowledge within the agricultural innovation system; and (3)
examined government policies to support sugarcane family farmers in enhancing their
livelihood dynamics.
The research utilised the modified transcendental phenomenological approach to
unpack the lived experiences of forty sugarcane family farmers. These participants
undertook a series of semi-structured interviews and focus group discussions between
January and December 2022 with the assistance of the Balayan Mill District a regional arm
of the Sugar Regulatory Administration – Department of Agriculture, which supervises the
participating block farms. A key informant interview was also conducted with the head of
the office to gain a holistic appreciation of the government's efforts to address the issues of
the sugarcane family farmers.
The study revealed dualism in leadership within the block farms. While patriarchal
views still exist within the sector, the farmers made an effort to address these concerns by
providing spaces for females to lead and participate within the SBFS. The implementation
of the existing agricultural innovation system was challenged, particularly during the
COVID-19 pandemic, as alternative communication modalities were implemented to
bridge the communication gap. This highlighted the weaknesses in accessing ICTs in rural
communities, a longstanding problem in the country due to the financial and educational
limitations of the participants. Lastly, the need to re-evaluate the existing government laws
and policies on sugarcane farming is essential in order to address the issues surrounding
the livelihood dynamics of the family farmers. Particularly with regard to the provision of
an enabling environment for farmers to participate in the co-creation of knowledge to
strengthen their sustainability as sugarcane farmers
The response of carbon uptake to soil moisture stress: adaptation to climatic aridity
Get PDFThe coupling between carbon uptake and water loss through stomata implies that gross primary production (GPP) can be limited by soil water availability through reduced leaf area and/or stomatal conductance. Ecosystem and land-surface models commonly assume that GPP is highest under well-watered conditions and apply a stress function to reduce GPP as soil moisture declines. Optimality considerations, however, suggest that the stress function should depend on climatic aridity: ecosystems adapted to more arid climates should use water more conservatively when soil moisture is high, but maintain unchanged GPP down to a lower critical soil-moisture threshold. We use eddy-covariance flux data to test this hypothesis. We investigate how the light-use efficiency (LUE) of GPP depends on soil moisture across ecosystems representing a wide range of climatic aridity. ‘Well-watered’ GPP is estimated using the sub-daily P model, a first-principles LUE model driven by atmospheric data and remotely sensed vegetation cover. Breakpoint regression is used to relate daily β(θ) (the ratio of flux data–derived GPP to modelled well-watered GPP) to soil moisture estimated via a generic water balance model. The resulting piecewise function describing β(θ) varies with aridity, as hypothesised. Unstressed LUE, even when soil moisture is high, declines with increasing aridity index (AI). So does the critical soil-moisture threshold. Moreover, for any AI value, there exists a soil moisture level at which β(θ) is maximised. This level declines as AI increases. This behaviour is captured by universal non-linear functions relating both unstressed LUE and the critical soil-moisture threshold to AI. Applying these aridity-based functions to predict the site-level response of LUE to soil moisture substantially improves GPP simulation under both water-stressed and unstressed conditions, suggesting a route towards a robust, universal model representation of the effects of low soil moisture on leaf-level photosynthesis
Preclinical development of the TLR4 antagonist FP12 as a drug lead targeting the HMGB1/MD-2/TLR4 axis in lethal influenza infection
Get PDFBackground Acute Lung Injuries (ALI) are a severe consequence of influenza-induced cytokine storm that can cause respiratory failure and death. It has been demonstrated that Toll-like Receptor 4 (TLR4) is involved in cytokine storm and that TLR4−/− mice are protected against ALI. Therefore, TLR4 is a prime target for protection against ALI. FP12 is a known TLR4 antagonist that reduces TLR4-dependent immune activation and it is a promising lead compound for the treatment of innate immunity related pathologies. Objectives We present here the preclinical development of FP12 as an anti-inflammatory lead compound acting on influenza-induced ALI. Methods In vitro: We pre-treated THP-1 cells with FP12 (10 μM) for 0.5 h, then exposed to LPS (100 ng/ml) for 0 to 16 h. In some experiments, cells were simultaneously incubated with FP12 and LPS, or FP12 was added 30 min after LPS. Cytokine levels were measured by Western blot and ELISA assays. In vivo: WT C57BL/6J mice were infected with mouse-adapted influenza virus (PR8). Two days after infection, mice received either vehicle, FP7 (200 µg/mouse), or FP12 (200 µg/mouse) once daily (Day 2 to Day 6). Mice were monitored daily for survival for 14 days. Data were collected through histological staining, qRT-PCR, and ELISA assay. Results FP12 treatment inhibited both LPS- and HMGB1-induced TLR4 intracellular pathways (MyD88 and TRIF) leading to significantly reduced levels of a variety of proinflammatory cytokines including Type I interferon (IFN-β), highlighting its effectiveness in controlling proinflammatory protein production and reducing inflammation. FP12 protected mice therapeutically from influenza virus-induced lethality and reduced both cytokine gene expression and High Mobility Group Box 1 (HMGB1) levels in the lungs as well as ALI. Conclusion FP12 can antagonize TLR4 activation in vitro and protects mice from severe influenza infection, most likely by reducing the TLR4-dependent cytokine storm mediated by danger-associated molecular patterns (DAMPs)
Quanta emission rate during speaking and coughing mediated by indoor temperature and humidity
Get PDFIn epidemiological prospective modelling, assessing the hypothetical infectious quanta emission rate (Eq) is critical for estimating airborne infection risk. Existing Eq models overlook environmental factors such as indoor relative humidity (RH) and temperature (T), despite their importance to droplet evaporation dynamics. Here we include these environmental factors in a prospective Eq model based on the airborne probability functions with emitted droplet distribution for speaking and coughing activities. Our results show relative humidity and temperature have substantial influence on Eq. Drier environments exhibit a notable increase in suspended droplets (cf. moist environments), with Eq having a 10-fold increase when RH decreases from 90 % to 20 % for coughing and a 2-fold increase for speaking at a representative summer temperature (T = 25 C). In warmer environments, Eq values are consistently higher (cf. colder), with increases of up to 22 % for coughing and 9 % for speaking. This indicates temperature has a smaller impact than humidity. We demonstrate that indoor environmental conditions are important when quantifying the quanta emission rate using a prospective method. This is essential for assessing airborne infection risk
Stable individual differences in habituation and sensitization to prolonged painful stimulation are underpinned by activity in the hippocampus, amygdala and sensorimotor cortices
Get PDFAcute pain serves to warn an organism of potential damage. Two plausible theoretical response scenarios for prolonged painful stimulation could be hypothesised: If the organism does not sense potential harm an individual may habituate. Whereas, if harm is possible, pain sensitization maybe more probable. Examining how an individual adapts to prolonged stimulation will provide unique insight to the mechanisms underlying pain habituation and sensitisation and, potentially, a valuable perspective on the development of chronic pain. However, currently little is known about the stability of these individual differences or their underlying neural mechanisms. To address this, eighty-five participants completed an MRI session, involving a noxious stimulation task and a resting-state scan. Habituation/sensitization was operationalized as the slope of change in pain ratings across the task. Habituation was associated with increasing activity in the anterior hippocampus and amygdala over time, with sensitization associated with increasing activity in the sensorimotor cortices. These regions were then used as seeds for a resting-state functional connectivity analysis, which revealed that habituation was associated with higher connectivity between the hippocampus and ventromedial prefrontal cortex(vmPFC), and higher connectivity between sensorimotor regions and the hippocampus, amygdala and insula cortex. We have shown that habituation/sensitization to pain is a stable trait underpinned by differential activity in brain regions supporting sensory processing and appraisal. The perspective of these stable phenotypical patterns could have clinical applications and potential for improving our understanding of the development of chronic pain
Evaluation and verification of new UK air temperature extremes during the July 2022 heatwave: part 2, minimum temperatures
Get PDFThe brief but intense heatwave which affected all areas of the British Isles during the third week of July 2022 was particularly noteworthy as being the first occasion on which screen temperatures exceeded 40 °C anywhere in the United Kingdom. The event resulted in widespread new records for high air temperatures, both day maximum and night minimum, many by surprisingly wide margins relative to existing climatology. This two-part analysis examines the causes and distribution of resulting extremes of air temperature, specifically the validity of new UK air temperature records: Part 1 considered maximum temperatures, and Part 2 minimum temperatures
What shared learning spaces taught me about student belonging
No full textAn examination of what we can learn from the transition from online learning spaces during the Covid pandemic to our campus teaching post-pandemi
Cultural heritage, community engagement and sustainable tourism: case studies from archaeological sites in the global south
No full textImplementation of static image particle characterisation in pharmaceutical development
No full textParticle size analysis is one of the most utilised particle characterisation approaches within the
pharmaceutical industry. Particle size can affect the quality, processability and/or performance
of a pharmaceutical process/product. The particle size and shape of an active pharmaceutical
ingredient (API) can affect the stability, dissolution rate, flow, sticking propensity to name but
a few. In turn, these can affect product quality attributes such as content uniformity (via
cohesion and/or segregation), tablet die filling, tablet disintegration/dissolution rates etc.
Consequently, particle size is commonly an integral part of a drug release specification
designed to ensure the quality of a drug product.
Historically, the use of laser light scattering (LLS) has dominated the particle sizing arena,
however, as scientists move towards the need to better understand and model their materials
and processes, the use of image analysis tools such as static image analysis (SIA) have see a
significant increase in popularity due to their ability to provide data rich information about a
wider range of particle characteristics.
The aim of this work was first to curate a database of active pharmaceutical ingredients (API),
characterising not just size but also information relating to shape (e.g., elongation, width, and
length) for each particle within the samples. It was hoped that this information would also
enable understand of the influence of distribution shape and separate the information provided
through different weighting approaches, both arithmetically and volumetrically weighted.
Using this data, the next stage would be to investigate means to improve how the data is
reported and used. The next stage would be to consider how this data could be utilised to enable
improved understanding of our powders, and through comparison with materials of similar sets
of particle characteristics, provide a means to use historical knowledge to mitigate future
challenges.
In addition to this, work to characterise and track API characteristics within a multi-component
system using an integrated image analysis / Raman system. The aim of this would be to
challenge the common assumption that the characteristics of the input API are indicative of the
API after manufacture. The work was aimed to assess the propensity for an API to undergo
process induced attrition during manufacture and determine the sources of attrition.
Finally, a proposal of how the above approaches can be implemented into the pharmaceutical
development workflow to enhance the understanding of our materials and thereby the
performance of our products