Temporally consistent predominance and distribution of secondary malaria vectors in the Anopheles community of the upper Zambezi floodplain

Regional optimisation of malaria vector control approaches requires detailed understanding both of the species composition of Anopheles mosquito communities, and how they vary over spatial and temporal scales. Knowledge of vector community dynamics is particularly important in settings where ecohydrological conditions fluctuate seasonally and inter-annually, such as the Barotse floodplain of the upper Zambezi river. DNA barcoding of anopheline larvae sampled in the 2019 wet season revealed the predominance of secondary vector species, with An. coustani comprising > 80% of sampled larvae and distributed ubiquitously across all ecological zones. Extensive larval sampling, plus a smaller survey of adult mosquitoes, identified geographic clusters of primary vectors, but represented only 2% of anopheline larvae. Comparisons with larval surveys in 2017/2018 and a contemporaneous independent 5-year dataset from adult trapping corroborated this paucity of primary vectors across years, and the consistent numerical dominance of An. coustani and other secondary vectors in both dry and wet seasons, despite substantial inter-annual variation in hydrological conditions. This marked temporal consistency of spatial distribution and anopheline community composition presents an opportunity to target predominant secondary vectors outdoors. Larval source management should be considered, alongside prevalent indoor-based approaches, amongst a diversification of vector control approaches to more effectively combat residual malaria transmission.

High resolution climate reconstructions of recent warming using instrumental and ice core records from coastal Antarctica

In-situ observational record of Antarctic surface temperatures is rather sparse. Proxy based ice core studies are thus critical for reconstructing the past climate change on centennial and decadal time scales. The present study review the available instrumental and proxy records from the Dronning Maud Land region of East Antarctica as well as report recent evidences of Antarctic climate change and its global linkages. The monthly mean air temperature records of the Novolazarevskaya (Novo) station, which is the longest (since 1961) and continuous meteorological record in this region, revealed a significant warming trend at a rate of 0.25 °C / decade. To understand the spatial and temporal consistency of this warming, well-dated ice cores from the coastal Dronning Maud Land region were assessed. All proxy records consistently suggest an enhanced warming up to +0.12 °C / decade. This is further supported by a recent assessment of stable oxygen and hydrogen isotope proxy records from two high resolution ice cores (IND-25/B5 and IND-22/B4) from this region. Among these records, the IND-25/B5 provided ultra-high-resolution data for the past 100 years (1905-2005) and the IND-22/B4 core represented the past ~470 years (1530-2002) of Antarctic change. These ice records provided insights on the influence of solar forcing on Antarctic climate system as well as its linkages with the tropical and mid-latitude climatic modes like the Southern Annular Mode (SAM) and El Niño Southern Oscillation (ENSO). The calculated surface air temperatures using these records showed a warming by 0.06-0.1 °C / decade, with greatly enhanced warming during the past several decades (~0.4 °C / decade). It is confirmed that the coastal areas of Dronning Maud Land are indeed warming and the trend is apparently enhancing in the recent decades.

The MOPITT Version 9 CO Product: Sampling Enhancements and Validation

Characteristics of the Version 9 (V9) MOPITT ("Measurements of Pollution in the Troposphere") satellite retrieval product for tropospheric carbon monoxide (CO) are described. The new V9 product includes many CO retrievals over land which, in previous MOPITT product versions, would have been discarded by the cloud detection algorithm. Globally, the number of daytime MOPITT retrievals over land has increased by 30–40 % relative to the Version 8 product, although the increase in retrieval coverage exhibits significant geographical variability. Areas benefiting from the improved cloud detection performance include (but are not limited to) source regions often characterized by high aerosol concentrations. The V9 MOPITT product also incorporates a modified calibration strategy for the MOPITT near-infrared (NIR) CO channels, resulting in greater temporal consistency for the NIR-only and thermal infrared-near infrared (TIR-NIR) retrieval variants. Validation results based on in-situ CO profiles acquired from aircraft in a variety of contexts indicate that retrieval biases for V9 are typically within the range of ±5 % and are generally comparable to results for the V8 product.

Temporal Consistency-Based Loss Function for Both Deep Q-Networks and Deep Deterministic Policy Gradients for Continuous Actions

Artificial intelligence (AI) techniques in power grid control and energy management in building automation require both deep Q-networks (DQNs) and deep deterministic policy gradients (DDPGs) in deep reinforcement learning (DRL) as off-policy algorithms. Most studies on improving the stability of DRL have addressed these with replay buffers and a target network using a delayed temporal difference (TD) backup, which is known for minimizing a loss function at every iteration. The loss functions were developed for DQN and DDPG, and it is well-known that there have been few studies on improving the techniques of the loss functions used in both DQN and DDPG. Therefore, we modified the loss function based on a temporal consistency (TC) loss and adapted the proposed TC loss function for the target network update in both DQN and DDPG. The proposed TC loss function showed effective results, particularly in a critic network in DDPG. In this work, we demonstrate that, in OpenAI Gym, both “cart-pole” and “pendulum”, the proposed TC loss function shows enormously improved convergence speed and performance, particularly in the critic network in DDPG.

Genetic, environmental and intrinsic determinants of the human antibody epitope repertoire

Phage-displayed immunoprecipitation sequencing (PhIP-Seq) has successfully enabled high-throughput profiling of human antibody profiles. However, a comprehensive overview of environmental and genetic determinants shaping human adaptive immunity is currently lacking. In this study, we aimed to investigate the effects of genetic, environmental and intrinsic factors on the variation in human antibody repertoires. We characterized serological antibody repertoires against 344,000 peptides using PhIP-Seq libraries from a wide range of microbial and environmental antigens in 1,443 participants from a population cohort. We demonstrate individual-specificity, temporal consistency and co-housing similarities in antibody repertoire. Genetic analyses showed involvement of the HLA, IGHV and FUT2 regions. Furthermore, we uncovered associations between 48 phenotypic factors and 544 antibody-bound peptides, including age, cell counts, sex, smoking behavior and allergies, among others. Overall, our results indicate that human antibody epitope repertoires are shaped by both host genetics and environmental exposures and highlight unique signatures of distinct phenotypes and genotypes.

Spatio-Temporal Patterns of Increasing Illegal Livestock Grazing over Three Decades at Moyowosi Kigosi Game Reserve, Tanzania

The global increase of livestock has caused illegal intrusion of livestock into protected areas. Until now, hotspot areas of illegal grazing have rarely been mapped, long-term monitoring data are missing, and little is known about the drivers of illegal grazing. We localized hotspots of illegal grazing and identified factors that influenced spatio-temporal patterns of illegal grazing over three decades in the Moyowosi Kigosi Game Reserve (MKGR), Tanzania. We used questionnaires with local pastoralists (N = 159), georeferenced aerial survey data and ranger reports from 1990–2019 to understand the reasons for illegal grazing in the area. We found that hotspots of illegal grazing occurred initially within 0–20 km of the boundary (H (3) = 137, p < 0.001; (H (3) = 32, p < 0.001) and encroached further into the protected area with time (H (3) = 11.3, p = 0.010); (H (2) = 59.0, p < 0.001). Further, livestock herd sizes decreased with increasing distance from the boundary (R = −0.20, p = 0.020; R = −0.40, p = 0.010). Most interviewees (81%) claimed that they face challenges of reduced foraging land in the wet season, caused by increasing land used for cultivation, which drives them into the MKGR to feed their livestock. We conclude that there is spatio-temporal consistency in the illegal livestock intrusion over three decades, and hotspot areas are located along the boundary of the MKGR. We suggest focusing patrols at these hotspot areas, especially during the wet season, to use limited law enforcement resources effectively.

Development and Validation of the Depression Inventory for Type 1 Diabetes (DID-1)

People with type 1 diabetes (T1D) are more likely to have depression than the general population and their prognosis is worse. Unfortunately, the characteristics of persons with T1D lead to inadequate screening for depression in this population. To aid in the detection of depression in this population, this study was undertaken to develop a depressive symptoms assessment instrument specific to patients with T1D and to examine its psychometric properties. A total of 207 people with T1D participated in this study. The reliability of the new scale was assessed using Cronbach’s alpha and the Spearman-Brown split-half coefficient. The Depression Inventory for type 1 Diabetes (DID-1), composed of 45 items on a Likert scale (1–7), shows high internal and temporal consistency, as well as adequate concurrent, convergent and discriminant validity. Factor analysis identified 7 factors (Symptoms of depression, Diminished interest, Hopelessness and dissatisfaction, Guilt, Fear, frustration and irritability, Defenselessness, and Interference in daily life) that explained 61.612% of the total variability. The cut-off score for diagnosis was set at 155 points. It was concluded that the DID-1 scale is a reliable, valid and useful tool for the assessment of depressive symptoms, eliminating the bias of other nonspecific diabetes scales.

Landsat-Derived Annual Maps of Agricultural Greenhouse in Shandong Province, China from 1989 to 2018

Agricultural greenhouse (AG), one of the fastest-growing technology-based approaches worldwide in terms of controlling the environmental conditions of crops, plays an essential role in food production, resource conservation and the rural economy, but has also caused environmental and socio-economic problems due to policy promotion and market demand. Therefore, long-term monitoring of AG is of utmost importance for the sustainable management of protected agriculture, and previous efforts have verified the effectiveness of remote sensing-based techniques for mono-temporal AG mapping in a relatively small area. However, currently, a continuous annual AG remote sensing-based dataset at large-scale is generally unavailable. In this study, an annual AG mapping method oriented to the provincial area and long-term period was developed to produce the first Landsat-derived annual AG dataset in Shandong province, China from 1989 to 2018 on the Google Earth Engine (GEE) platform. The mapping window for each year was selected based on the vegetation growth and the phenological information, which was critical in distinguishing AG from other misclassified categories. Classification for each year was carried out initially based on the random forest classifier after the feature optimization. A temporal consistency correction algorithm based on classification probability was then proposed to the classified AG maps for further improvement. Finally, the average User’s Accuracy, Producer’s Accuracy and F1-score of AG based on visually-interpreted samples over 30 years reached 96.56%, 86.64% and 0.911, respectively. Furthermore, we also found that the ranked features via calculating the importance of each tested feature resulted in the highest accuracy and the strongest stability in the initial classification stage, and the proposed temporal consistency correction algorithm improved the final products by approximately five percent on average. In general, the resultant AG sequence dataset from our study has revealed the expansion of this typical object of “Human–Nature” interaction in agriculture and has a potential application in use of greenhouse-related technology and the scientific planning of protected agriculture.

Infrasound as a Cue for Seabird Navigation

Seabirds are amongst the most mobile of all animal species and spend large amounts of their lives at sea. They cross vast areas of ocean that appear superficially featureless, and our understanding of the mechanisms that they use for navigation remains incomplete, especially in terms of available cues. In particular, several large-scale navigational tasks, such as homing across thousands of kilometers to breeding sites, are not fully explained by visual, olfactory or magnetic stimuli. Low-frequency inaudible sound, i.e., infrasound, is ubiquitous in the marine environment. The spatio-temporal consistency of some components of the infrasonic wavefield, and the sensitivity of certain bird species to infrasonic stimuli, suggests that infrasound may provide additional cues for seabirds to navigate, but this remains untested. Here, we propose a framework to explore the importance of infrasound for navigation. We present key concepts regarding the physics of infrasound and review the physiological mechanisms through which infrasound may be detected and used. Next, we propose three hypotheses detailing how seabirds could use information provided by different infrasound sources for navigation as an acoustic beacon, landmark, or gradient. Finally, we reflect on strengths and limitations of our proposed hypotheses, and discuss several directions for future work. In particular, we suggest that hypotheses may be best tested by combining conceptual models of navigation with empirical data on seabird movements and in-situ infrasound measurements.