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This paper presents the results of a combined experimental and computational study of the mechanisms of blister formation, and their effects on the degradation of organic light emitting devices (OLEDs). Blister formation is attributed to the effects of thermally induced mismatch stresses associated with applied bias. These result in interfacial cracking phenomena that are affected by the solvents that are used in OLED fabrication. The OLEDs are first fabricated using an electron transport layer of poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) deposited on an active layer made from solutions of poly[2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylenevinylene] dissolved in different solvents (toluene, chloroform, and chlorobenzene). The formation of blisters and degradation is then studied under applied bias for devices fabricated using different solvents (toluene, chloroform, and chlorobenzene) and emissive layer thicknesses. The underlying layer mechanical properties are then incorporated into interfacial fracture mechanic models that explain the formation of blisters that degrade the performance of OLED structures.

This paper uses a combination of experiments and theory to study the effects of annealing temperature on the mechanical properties of hybrid organic–inorganic perovskites (HOIPs). We examined the mechanical (hardness and Young’s modulus), microstructural, and surface topography properties of the HOIP film at different annealing temperatures ranging from 80 to 170 °C. A mechanism-based strain gradient (MSG) theory is used to explain indentation size effects in films at different annealing temperatures. Intrinsic film yield strengths and hardness values (deduced from the MSG theory) are then shown to exhibit a Hall–Petch dependence on the inverse square root of the average grain size. The implications of the results are then discussed for the design of mechanically robust perovskite solar cells.

Abstract Background Despite WHO guidelines for testing all suspected cases of malaria before initiating treatment, presumptive malaria treatment remains common practice among some clinicians and in certain low-resource settings the capacity for microscopic testing is limited. This can lead to misdiagnosis, resulting in increased morbidity due to lack of treatment for undetected conditions, increased healthcare costs, and potential for drug resistance. This is particularly an issue as multiple conditions share the similar etiologies to malaria, including brucellosis, a rare, under-detected zoonosis. Linking rapid diagnostic tests (RDTs) and digital test readers for the detection of febrile illnesses can mitigate this risk and improve case management of febrile illness. Methods This technical advance study examines Connected Diagnostics, an approach that combines the use of point-of-care RDTs for malaria and brucellosis, digitally interpreted by a rapid diagnostic test reader (Deki Reader) and connected to mobile payment mechanisms to facilitate the diagnosis and treatment of febrile illness in nomadic populations in Samburu County, Kenya. Consenting febrile patients were tested with RDTs and patient diagnosis and risk information were uploaded to a cloud database via the Deki Reader. Patients with positive diagnoses were provided digital vouchers for transportation to the clinic and treatment via their health wallet on their mobile phones. Results In total, 288 patients were tested during outreach visits, with 9% testing positive for brucellosis and 0.6% testing positive for malaria. All patients, regardless of diagnosis were provided with a mobile health wallet on their cellular phones to facilitate their transport to the clinic, and for patients testing positive for brucellosis or malaria, the wallet funded their treatment. The use of the Deki Reader in addition to quality diagnostics at point of care also facilitated geographic mapping of patient diagnoses in relation to key risk areas for brucellosis transmission. Conclusions This study demonstrates that the Connected Dx approach can be effective even when addressing a remote, nomadic population and a rare disease, indicating that this approach to diagnosing, treatment, and payment for healthcare costs is feasible and can be scaled to address more prevalent diseases and conditions in more populous contexts.

Accurate identification and estimation of the population densities of microscopic, soil-dwelling plant-parasitic nematodes (PPNs) are essential, as PPNs cause significant economic losses in agricultural production systems worldwide. This study presents a comprehensive review of emerging techniques used for the identification of PPNs, including morphological identification, molecular diagnostics such as polymerase chain reaction (PCR), high-throughput sequencing, meta barcoding, remote sensing, hyperspectral analysis, and image processing. Classical morphological methods require a microscope and nematode taxonomist to identify species, which is laborious and time-consuming. Alternatively, quantitative polymerase chain reaction (qPCR) has emerged as a reliable and efficient approach for PPN identification and quantification; however, the cost associated with the reagents, instrumentation, and careful optimisation of reaction conditions can be prohibitive. High-throughput sequencing and meta-barcoding are used to study the biodiversity of all tropical groups of nematodes, not just PPNs, and are useful for describing changes in soil ecology. Convolutional neural network (CNN) methods are necessary to automate the detection and counting of PPNs from microscopic images, including complex cases like tangled nematodes. Remote sensing and hyperspectral methods offer non-invasive approaches to estimate nematode infestations and facilitate early diagnosis of plant stress caused by nematodes and rapid management of PPNs. This review provides a valuable resource for researchers, practitioners, and policymakers involved in nematology and plant protection. It highlights the importance of fast, efficient, and robust identification protocols and decision-support tools in mitigating the impact of PPNs on global agriculture and food security.

Plant-parasitic nematodes (PPN), especially sedentary endoparasitic nematodes like root-knot nematodes (RKN), pose a significant threat to major crops and vegetables. They are responsible for causing substantial yield losses, leading to economic consequences, and impacting the global food supply. The identification of PPNs and the assessment of their population is a tedious and time-consuming task. This study developed a state-of-the-art deep learning model-based decision support tool to detect and estimate the nematode population. The decision support tool is integrated with the fast inferencing YOLOv5 model and used pretrained nematode weight to detect plant-parasitic nematodes (juveniles) and eggs. The performance of the YOLOv5-640 model at detecting RKN eggs was as follows: precision = 0.992; recall = 0.959; F1-score = 0.975; and mAP = 0.979. YOLOv5-640 was able to detect RKN eggs with an inference time of 3.9 milliseconds, which is faster compared to other detection methods. The deep learning framework was integrated into a user-friendly web application system to build a fast and reliable prototype nematode decision support tool (NemDST). The NemDST facilitates farmers/growers to input image data, assess the nematode population, track the population growths, and recommend immediate actions necessary to control nematode infestation. This tool has the potential for rapid assessment of the nematode population to minimise crop yield losses and enhance financial outcomes.

The use of biochar is changing, and the combined application of biochar with fertilizer is increasingly gaining acceptance. However, the yield gains results reported in the existing literature through the co-application of fertilizer with biochar are conflicting. To resolve this, we utilized a meta-analysis of 627 paired data points extracted from 57 published articles to assess the performance of the co-application of biochar and fertilizers on crop yield compared with the corresponding controls. We also studied the impact of biochar characteristics, experimental conditions, and soil properties on crop yield. Our analysis showed that individually, biochar and inorganic fertilizer increased crop yield by 25.3% ± 3.2 (Bootstrap CI 95%) and 21.9% ± 4.4, respectively. The co-application of biochar with both inorganic and organic fertilizers increased crop yield by 179.6% ± 18.7, however, this data needs to be treated with caution due to the limited dataset. The highest yield increase was observed with amendments to very acidic soils (pH ≤5), but the benefits of biochar were not affected by the rate and the time after the application. In addition, the effects of biochar are enhanced when it is produced at 401-500 °C with a C:N ratio of 31-100. Our results suggest that the co-application of biochar with either inorganic and/or organic fertilizers in acidic soils increase crop productivity compared to amendment with either fertilizer or biochar. Our meta-analysis supports the utilization of biochar to enhance the efficiency and profitability of fertilizers., (Copyright © 2021 Elsevier B.V. All rights reserved.)

The potential existence of threshold yield loss in dry season rice growing systems under coastal saline environment remains unexplored, a scenario that could have policy relevance in government planning of rice intensification in the coastal areas of Bangladesh. This study applied the adaptation tipping points (ATPs) approach to investigate threshold yield loss from multiple perspectives of farmers affected by salinity. Data were generated from 280 randomly-selected farmers (rice farmers, n = 109; shrimp farmers, n = 107; salt farmers, n = 64) from two coastal sub-districts using a semi-structured survey. Key informant interviews and focus group discussions were conducted to complement the survey results. Our study revealed that despite government actions to promote dry season rice cultivation, farmers have been growing less rice in this season, with salinity-affected yield loss being the prime reason. Most of the rice farmers have considered that they would discontinue rice cultivation in this season due to yield loss, while shrimp and salt farmers have already reduced rice cultivation for the same reason and shifted to shrimp and salt farming as they perceived these enterprises as highly profitable and require less labour than rice farming. Rice farmers would tolerate a greater rice yield loss (23%) under saline conditions compared with the shrimp (16%) and salt farmers (14%). The yield loss thresholds indicate the need for government actions to support and encourage integrated land management for rice, shrimp and salt farming, rather than research and extension efforts for dry season rice expansion alone. These actions could strengthen sustainable livelihood options to ensure food security, and contribute to the achievement of sustainable development goals, for instance no poverty (SDG-1), zero hunger (SDG-2), and good health and well-being (SDG-3)., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Watershed morphometric assessment is about measurements and calculations of land surface forms for the purpose of understanding hydro-geomorphological character and patterns. Important natural environment geo-information and summary of the spatial characteristics of Tana River Basin (TRB) in Kenya have been obtained through hydro-geomorphometric analysis. Advanced Spaceborne Thermal Emission and Reflection Radiometer Digital Elevation Model (ASTERDEM) data and ArcGIS (ESRI Inc., version 10.4.1) together with published mathematical equations were applied to extract morphometric parameters of the drainage basin, which covers a total area of 94,930 km 2 and a span of 527.75 km. The quantitative morphometric analysis considered a total of 28 relief, areal, and linear hydro-morphometric characteristics of the TRB. Relief parameters of the basin suggest moderate-to-low overall watershed steepness, upland with rolling land surface patterns, rugged landforms susceptible to erosion and sediment transportation, and a landscape in evolution process tending towards maturity. This means stability of the land surface can be attained with intensive land degradation reversing strategies like erosion control measures. Areal characteristics further support the basin's susceptibility to erosion as shown by stream length, stream drainage density, and circulatory ratio values. Also, the areal aspects portray peak runoffs with short duration flashes. Linear parameter value results such as bifurcation ratio imply that infiltration capacity varies with stream orders across the watershed. This hydro-geomorphometric analysis would be useful to land and water managers, researchers and practitioners of TRB, and other similar systems in designing and planning soil and water conservation and management practices such as soil erosion control, groundwater recharge activities, catchment modelling, runoff and flood studies, prospecting groundwater mapping, and biological applications.

Coastal salinity causes substantial adverse impacts on agricultural productivity and food security. Farmers' choice of salinity adaptation strategies might depend on how they perceive the problem. This research examined rice farmers' perceptions of salinity, adaptation strategies, and its implications for policy initiatives to sustain rice production in the affected coastal areas of Bangladesh. Boro rice growers (n = 109) randomly selected from two coastal sub-districts were interviewed using a semi-structured survey. Awareness of salinity and its increase over the past 20 years was widespread among rice farmers. A high proportion of farmers (90%) perceived the reproductive (e.g. booting, heading, and flowering) stages of the rice plant as the most sensitive to salinity problems. Salinity (ECe) was measured in the farmers' fields and were categorized according to farmers' perceptions and scientific interpretation (e.g. high or low). Farmers perceived a field affected by high salinity at a lower EC reading than the scientific interpretation of the salinity level. Most of the farmers (67%) were undertaking early transplanting and applying irrigation in order to adapt to salinity problems which occur later in rice crop growth during Boro season. Thus, farmers' actions demonstrated that their perceptions of salinity and adaptation responses were pre-emptive of when salinity was most likely to have an impact on the rice crop. Farmers' perceptions of salinization and measures to manage salinity need to be considered in research prioritization and policy formulation by the government. This action could potentially secure rice production and thus contribute to the achievement of Sustainable Development Goals (SDG-1, 2 and 3)., Competing Interests: Declaration of competing interest The authors declares no conflict of interests., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Background: Limited data exist on health outcomes during pregnancy and childbirth in low- and middle-income countries. This is a pilot of an innovative data collection tool using mobile technology to collect patient-reported outcome measures (PROMs) selected from the International Consortium of Health Outcomes Measurement (ICHOM) Pregnancy and Childbirth Standard Set in Nairobi, Kenya., Methods: Pregnant women in the third trimester were recruited at three primary care facilities in Nairobi and followed prospectively throughout delivery and until six weeks postpartum. PROMs were collected via mobile surveys at three antenatal and two postnatal time points. Outcomes included incontinence, dyspareunia, mental health, breastfeeding and satisfaction with care. Hospitals reported morbidity and mortality. Descriptive statistics on maternal and child outcomes, survey completion and follow-up rates were calculated., Results: In six months, 204 women were recruited: 50% of women returned for a second ante-natal care visit, 50% delivered at referral hospitals and 51% completed the postnatal visit. The completion rates for the five PROM surveys were highest at the first antenatal care visit (92%) and lowest in the postnatal care visit (38%). Data on depression, dyspareunia, fecal and urinary incontinence were successfully collected during the antenatal and postnatal period. At six weeks postpartum, 86% of women breastfeed exclusively. Most women that completed the survey were very satisfied with antenatal care (66%), delivery care (51%), and post-natal care (60%)., Conclusion: We have demonstrated that it is feasible to use mobile technology to follow women throughout pregnancy, track their attendance to pre-natal and post-natal care visits and obtain data on PROM. This study demonstrates the potential of mobile technology to collect PROM in a low-resource setting. The data provide insight into the quality of maternal care services provided and will be used to identify and address gaps in access and provision of high quality care to pregnant women., Competing Interests: IA, CA and TK worked for the International Consortium of Health Outcomes Measurement (ICHOM). The feasibility of implementing one of the ICHOM Standard Set was piloted in this study. The financers also do not alter our adherence to PLOS ONE policies on sharing data and materials.

Background: Knowledge of antibiotic prescription practices in low- and middle-income countries is limited due to a lack of adequate surveillance systems., Objective: To assess the prescription of antibiotics for the treatment of acute respiratory tract infections (ARIs) in primary care., Method: An explanatory sequential mixed-methods study was conducted in 4 private not-for-profit outreach clinics located in slum areas in Nairobi, Kenya. Claims data of patients who received healthcare between April 1 and December 27, 2016 were collected in real-time through a mobile telephone-based healthcare data and payment exchange platform (branded as M-TIBA). These data were used to calculate the percentage of ARIs for which antibiotics were prescribed. In-depth interviews were conducted among 12 clinicians and 17 patients to explain the quantitative results., Results: A total of 49,098 individuals were registered onto the platform, which allowed them to access healthcare at the study clinics through M-TIBA. For 36,210 clinic visits by 21,913 patients, 45,706 diagnoses and 85,484 medication prescriptions were recorded. ARIs were the most common diagnoses (17,739; 38.8%), and antibiotics were the most frequently prescribed medications (21,870; 25.6%). For 78.5% (95% CI: 77.9%, 79.1%) of ARI diagnoses, antibiotics were prescribed, most commonly amoxicillin (45%; 95% CI: 44.1%, 45.8%). These relatively high levels of prescription were explained by high patient load, clinician and patient perceptions that clinicians should prescribe, lack of access to laboratory tests, offloading near-expiry drugs, absence of policy and surveillance, and the use of treatment guidelines that are not up-to-date. Clinicians in contrast reported to strictly follow the Kenyan treatment guidelines., Conclusion: This study showed successful quantification of antibiotic prescription and the prescribing pattern using real-world data collected through M-TIBA in private not-for-profit clinics in Nairobi., Competing Interests: AIGHD received funding from Joep Lange Institute to conduct this research. M-TIBA is rolled out by CarePay Ltd, Kenya. No authors declare a conflict of interest. Neither Joep Lange Institute nor CarePay had a role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We confirm our adherence to PLOS ONE policies on sharing data and materials.

Background: Despite WHO guidelines for testing all suspected cases of malaria before initiating treatment, presumptive malaria treatment remains common practice among some clinicians and in certain low-resource settings the capacity for microscopic testing is limited. This can lead to misdiagnosis, resulting in increased morbidity due to lack of treatment for undetected conditions, increased healthcare costs, and potential for drug resistance. This is particularly an issue as multiple conditions share the similar etiologies to malaria, including brucellosis, a rare, under-detected zoonosis. Linking rapid diagnostic tests (RDTs) and digital test readers for the detection of febrile illnesses can mitigate this risk and improve case management of febrile illness., Methods: This technical advance study examines Connected Diagnostics, an approach that combines the use of point-of-care RDTs for malaria and brucellosis, digitally interpreted by a rapid diagnostic test reader (Deki Reader) and connected to mobile payment mechanisms to facilitate the diagnosis and treatment of febrile illness in nomadic populations in Samburu County, Kenya. Consenting febrile patients were tested with RDTs and patient diagnosis and risk information were uploaded to a cloud database via the Deki Reader. Patients with positive diagnoses were provided digital vouchers for transportation to the clinic and treatment via their health wallet on their mobile phones., Results: In total, 288 patients were tested during outreach visits, with 9% testing positive for brucellosis and 0.6% testing positive for malaria. All patients, regardless of diagnosis were provided with a mobile health wallet on their cellular phones to facilitate their transport to the clinic, and for patients testing positive for brucellosis or malaria, the wallet funded their treatment. The use of the Deki Reader in addition to quality diagnostics at point of care also facilitated geographic mapping of patient diagnoses in relation to key risk areas for brucellosis transmission., Conclusions: This study demonstrates that the Connected Dx approach can be effective even when addressing a remote, nomadic population and a rare disease, indicating that this approach to diagnosing, treatment, and payment for healthcare costs is feasible and can be scaled to address more prevalent diseases and conditions in more populous contexts.

Climate change is causing droughts affecting crop production on a global scale. Classical breeding and selection strategies for drought-tolerant cultivars will help prevent crop losses. Plant breeders, for all crops, need a simple and reliable method to identify drought-tolerant cultivars, but such a method is missing. Plant metabolism is often disrupted by abiotic stress conditions. To survive drought, plants reconfigure their metabolic pathways. Studies have documented the importance of metabolic regulation, i.e. osmolyte accumulation such as polyols and sugars (mannitol, sorbitol); amino acids (proline) during drought. This study identified and quantified metabolites in drought tolerant and drought susceptible Camellia sinensis cultivars under wet and drought stress conditions. For analyses, GC-MS and LC-MS were employed for metabolomics analysis.%RWC results show how the two drought tolerant and two drought susceptible cultivars differed significantly (p≤0.05) from one another; the drought susceptible exhibited rapid water loss compared to the drought tolerant. There was a significant variation (p<0.05) in metabolite content (amino acid, sugars) between drought tolerant and drought susceptible tea cultivars after short-time withering conditions. These metabolite changes were similar to those seen in other plant species under drought conditions, thus validating this method. The Short-time Withering Assessment of Probability for Drought Tolerance (SWAPDT) method presented here provides an easy method to identify drought tolerant tea cultivars that will mitigate the effects of drought due to climate change on crop losses., (Copyright © 2016. Published by Elsevier GmbH.)