Miracle-dz/UniFAR-FTUs huggingface dataset:
Assortative pairing for boldness and consequences for reproductive success in Montagu’s harrier

Behavioural combination within pairs depending on personality and plasticity might influence reproductive success. However, studies testing this hypothesis are rare, especially in the case of monogamous species with bi-parental care in which the sexes exhibit different behavioural roles. In this study, we investigated the pairing patterns for both boldness and boldness plasticity in Montagu’s harriers (Circus pygargus), a species with sex-specific care, and the consequences for their reproductive success. We measured individual boldness and plasticity for both sexes, and we assessed the pairing pattern in the Montagu’s harrier population for these two traits. We calculated four indices to characterize the behavioural association within pairs: pair boldness, boldness similarity within pairs, pair plasticity and plasticity similarity within pairs. The relationship between the behaviour of the parents and the reproductive success was then tested through these four indices. We found a pattern of assortative pairing based on both boldness and plasticity in the Montagu’s harrier population. Within-pair similarity of plasticity had a significant effect on the reproductive success, which was higher for less similar pairs than for more similar pairs. Our results question the origin of this pairing pattern and suggest that ecological constraint and not sexual selection could be the major driver.
Soil nitrogen supply rates during a cotton season

As a result of the demand for increased yield per hectare production output for cotton farms in Australia, as well as the limitations of expanding paddock areas to meet this demand, an increase of nitrogen - the primary cotton plant is required. This comes at a time when rising input costs, as well as sustainability targets are key factors in determining the type of nitrogen fertiliser applied and other components associated with fertiliser usage such as time and rate of application. By matching a cotton plant’s varied nitrogen requirements with peak soil potential nitrogen supply, soil nitrogen losses can be minimised, creating sustainable and more efficient nitrogen use for growers. The mineral nitrogen supply patterns of Urea, the most commonly used nitrogen fertiliser, as well as ENTEC® Urea, a controlled release fertiliser were investigated. This research was specifically designed to compare the potential net soil mineral nitrogen supply over a period of 60 days for each treatment, as well as the potential greenhouse gas emissions from the soil that included nitrous oxide, carbon dioxide and methane over the same time period. To compare soil nitrogen mineralisation and nitrogen release patterns and processes between fertiliser treatments, a pot study was conducted under laboratory conditions. The study was based on a 60 day aerobic incubation method with a constant soil temperature (25oC), fertiliser application rate (600 kg/ha N), soil moisture range (>75% field capacity) and soil type (Black Vertosol from an irrigated cotton farm Yargullen, QLD). Soil extraction (2M KCl), colorimetric and gas chromatography laboratory methods were used to obtain sufficient data for the net soil nitrate and ammonium concentrations on days 0, 3, 7, 14, 30, 45 and 60. Concurrently, soil gaseous emissions in the form of a linear flux over 45 minute sampling periods for days 0-5, 14, 45 and 60 were achieved. Results indicated that soil applied with ENTEC® Urea provided a delay in the peak net mineral nitrogen supply with a steady increase occurring until day 60, when compared to Urea which peaked in mineral nitrogen supply by day 14. If fertiliser was applied in September at a similar time to planting, net supply from Urea would not coincide with increased nitrogen demands from first boll fill and boll opening phase (50-100 after sowing). ENTEC® Urea however, would meet the nitrogen requirements of cotton plants with a single fertiliser application at season commencement, as well as providing a more sustainable fertiliser option with a 73.3% reduction in nitrous oxide emissions when compared to Urea. Further investigation could include relating the results to field conditions using a degree day relationship and to compare the mineral nitrogen and gaseous emission results from field experiments.
Techno-Economic Viability of Agro-Photovoltaic Irrigated Arable Lands in the EU-Med Region: A Case-Study in Southwestern Spain

Solar photovoltaic (PV) energy is positioned to play a major role in the electricity generation mix of Mediterranean countries. Nonetheless, substantial increase in ground-mounted PV installed capacity could lead to competition with the agricultural use of land. A way to avert the peril is the electricity-food dual use of land or agro-photovoltaics (APV). Here, the profitability of a hypothetical APV system deployed on irrigated arable lands of southwestern Spain is analyzed. The basic generator design, comprised of fixed-tilt opaque monofacial PV modules on a 5 m ground-clearance substructure, featured 555.5 kWp/ha. Two APV shed orientations, due south and due southwest, were compared. Two 4-year annual-crop rotations, cultivated beneath the heightened PV modules and with each rotation spanning 24 ha, were studied. One crop rotation was headed by early potato, while the other was headed by processing tomato. All 9 crops involved fulfilled the two-fold condition of being usually cultivated in the area and compatible with APV shed intermitent shading. Crop revenues under the partial shading of PV modules were derived from official average yields in the area, through the use of two alternative sets of coefficients generated for low and high crop-yield shade-induced penalty. Likewise, two irrigation water sources, surface and underground, were compared. Crop total production costs, PV system investment and operating costs and revenues from the sale of electricity, were calculated. The internal rates of return (IRRs) obtained ranged from a minimum of 3.8% for the combination of southwest orientation, early-potato rotation, groundwater and high shade-induced crop-yield penalty, to a maximum of 5.6% for the combination of south orientation, processing-tomato rotation, surface water and low shade-induced crop-yield penalty.
PERCEIVED BENEFITS OF WHATSAPP VOICE MESSAGING: INVESTIGATING EFL STUDENTS’ EXPERIENCES

Rapid emergence of wireless technologies and ownership of mobile devices have changed many aspects of peoples’ lives. These mobile technologies have been integrated into language learning and teaching as well. Successful and effective use of these technologies in language learning, however, depends on the incorporation of pedagogical principles guided by theories of second language acquisition (SLA). Accordingly, informed by the interaction hypothesis (Gass & Mackey, 2015), this study employed a messaging application, WhatsApp, to help language learners improve their communication skills. Nine A1 level EFL students used WhatsApp voice messaging with their peers outside the classes to accomplish the tasks assigned to them for four weeks in the spring semester of 2018. Later, their experiences were investigated by means of written surveys. Content analysis of the data demonstrated that all the students who took part in the study benefitted from the WhatsApp voice messaging practice and perceived numerous benefits. These included speaking and pronunciation development, an opportunity for language practice, review of previous learning, overcoming shyness, and awareness and correction of errors. The findings were discussed in the light of the existing literature and certain implications arose for both language learners and teachers. Article visualizations:
Nesting ecology and reuse of nest burrows by Bank Swallow (Riparia riparia) in southern Yukon

Bank Swallow (Riparia riparia) is a declining insectivorous bird that nests colonially in near-vertical surfaces, including natural banks along waterways as well as those created by industrial excavation. Several threats are likely contributing to the population decline, conservation measures have been recommended, and monitoring methods have been developed. However, little is known of this species in the extensive boreal portion of its breeding range. To assess whether recommendations developed in southern areas are likely to be effective in a more northerly region, we investigated aspects of the nesting ecology of Bank Swallow in southern Yukon during 2013–2017. Nesting activity occurred between 20 May and 21 August. We found an exceptional abundance of nest burrows in natural riverbanks along 46 km of the Yukon River near Whitehorse (326 burrows/km), but relatively low percent burrow occupancy in both natural and artificial habitats compared to studies from other regions. Year-to-year persistence of nest burrows and rates of reuse of burrows were high compared to other studies. We highlight the potential importance of the boreal region for recovery of Bank Swallow in Canada, and the importance of using region-specific estimates of percent occupancy when monitoring Bank Swallow using burrow counts. Further study is needed to determine whether unoccupied burrows contribute to nesting success, and whether there are situations in which Bank Swallow burrows should be protected year-round instead of only during nesting.
Secure decision tree twin support vector machine training and classification process for encrypted IoT data via blockchain platform

A secure decision tree twin support vector machine (DT‐TSVM) multi‐classification algorithm has been proposed in this paper for improving the reliability and security of the collected IoT data from multiple data providers. The multiclass secure DT‐TSVM algorithm has been employed to train a machine learning model using the encrypted training dataset. The training dataset is collected via a blockchain platform. A blockchain method has been adopted to construct a secure and reliable distributed platform among dataset providers. The Paillier homomorphic cryptosystem has been applied for encrypting the IoT dataset. Then, the dataset has been recorded on the distributed ledger. The secure DT‐TSVM algorithm's‐based train model effectiveness has been compared with the other two available algorithms, namely the multiclass binary support vector machine (MBSVM) and one‐to‐one SVM algorithms. The experiment results showed that the privacy‐preserving multiclass secure DT‐TSVM‐based model did not reduce the accuracy, but it increased the average precision and recall by 0.53% and 0.44% than MBSVM and 0.82% and 0.71% than one‐to‐one SVM, respectively. Further, the time consumption of data providers and data analysts did not change significantly with the increase of number of data provider.
Radiological Scouting, Monitoring and Inspection Using Drones

Human populations and natural ecosystems are bound to be exposed to ionizing radiation from the deposition of artificial radionuclides resulting from nuclear accidents, nuclear devices or radiological dispersive devices (“dirty bombs”). On the other hand, Naturally Occurring Radioactive Material industries such as phosphate production or uranium mining, contribute to the on site storage of residuals with enhanced concentrations of natural radionuclides. Therefore, in the context of the European agreements concerning nuclear energy, namely the European Atomic Energy Community Treaty, monitoring is an essential feature of the environmental radiological surveillance. In this work, we obtain 3D maps from outdoor scenarios, and complete such maps with measured radiation levels and with its radionuclide signature. In such scenarios, we face challenges such as unknown and rough terrain, limited number of sampled locations and the need for different sensors and therefore different tasks. We propose a radiological solution for scouting, monitoring and inspecting an area of interest, using a fleet of drones and a controlling ground station. First, we scout an area with a Light Detection and Ranging sensor onboard a drone to accurately 3D-map the area. Then, we monitor that area with a Geiger–Müller Counter at a low-vertical distance from the ground to produce a radiological (heat)map that is overlaid on the 3D map of the scenario. Next, we identify the hotspots of radiation, and inspect them in detail using a drone by landing on them, to reveal its radionuclide signature using a Cadmium–Zinc–Telluride detector. We present the algorithms used to implement such tasks both at the ground station and on the drones. The three mission phases were validated using actual experiments in three different outdoor scenarios. We conclude that drones can not only perform the mission efficiently, but in general they are faster and as reliable as personnel on the ground.
Field evidence reveals conservative water use of poplar saplings under high aerosol conditions

Anthropogenic aerosols could alter multiple meteorological processes such as radiation regime and air temperature, thereby modifying plant transpiration. However, the lack of field observations at leaf and plant level hinders our ability to understand how aerosols could affect plant water use. Aerosol concentrations in northern China fluctuate periodically over a wide range. Taking advantage of this unique natural experiment opportunity, we conducted a series of physiological and environmental measurements at different times of the day to explore diurnal aerosols' effect on leaf transpiration and sap flow of planted poplar saplings (Populus × canadensis Moench). We found that high aerosol concentrations suppressed sun leaf transpiration by reducing leaf‐to‐air vapour pressure deficit (VPDleaf), while had no effect on shade leaf transpiration mainly because the negative effect of reduced VPDleaf on transpiration offset the positive effects of the increased stomatal conductance (gs). As aerosol concentration increased, the gs of both sun and shade leaves decreased more rapidly with an increase in VPDleaf, which caused their transpiration rates to become less sensitive to VPDleaf. Similarly, aerosols reduced sap flow density and its sensitivity to VPD. Synthesis. Our study provided observational evidence on aerosols' effects on plant transpiration at the leaf and canopy scales. The reduced transpiration and stronger stomatal control indicated that plant water use becomes more conservative under elevated aerosol concentrations.
The incidence and risk factors of bronchopulmonary
dysplasia in extremely preterm infants included in the
Polish National Program for Respiratory Syncytial Virus
Prophylaxis

Introduction: Bronchopulmonary dysplasia (BPD) is a chronic lung disease diagnosed in premature infants, which may cause severe respiratory failure due to respiratory syncytial virus (RSV) infection. The aim of this study was to assess the incidence and severity of BPD in infants born before 28 weeks of gestational age (GA) enrolled into the Polish National Program for RSV Prophylaxis (PNPRSVP). Material and methods: A retrospective analysis of data on children born in 2013 included in a prophylaxis program during the seasons 2012–2013 and 2013–2014. The following data were evaluated: the need for oxygen therapy for at least 28 days and the need for oxygen therapy at 36 weeks of postmenstrual age (PMA). Results: The analysis was carried out in a group of 603 children, who constituted 87.7% of the population entitled to prophylactic administration of palivizumab. BPD was diagnosed in 80.9% of extremely preterm infants; however, in 70.7% of cases the disease was mild. The risk factors for the development of BPD were GA, birth weight and birth weight below the 10th centile for GA. During the program, the median number of doses received was 5 (range 1–5), and 82.3% of children received all of the expected doses. Conclusions: Although the incidence of BPD in extremely preterm infants was high, mainly its mild form was recognized. Monitoring of the incidence of the disease and identifying the risk factors can be carried out effectively based on long-term data collected during the PNPRSVP.
Au-decorated semiconducting AlN nanosheet as an electronic sensor for theophylline drug

ABSTRACT Density functional theory calculations based on the TPSS functional were performed to investigate the potential application of the pristine AlN nanosheet (AlNNS) as well as the Au-decorated AlNNS (Au@AlNNS) in the detection of the theophylline (TP) drug. We found that the pristine sheet weakly adsorbed the drug, and its sensing response was about 6.0. After the Au-decoration on the AlNNS, the TP drug was powerfully adsorbed onto the Au@AlNNS with the adsorption energy of −1.33 eV, and the sensing response increased to 689.2. The localised molecular orbital energy decomposition analysis illustrated that the electrostatic attraction is stronger than the covalent interaction after the TP adsorption onto the Au@AlNNS. Based on the partial density of state analysis, the TP drug created a new state through the HOMO–LUMO gap of Au@AlNNS, which significantly increased the electrical conductivity. A short recovery time of 2.51 s was attained for the TP desorption from the Au@AlNNS surface. The water solvent weakened the adsorption process and decreased the sensing response to 524.6. Based on the results, we suggested the Au@AlNNS as a biosensor for the TP drug recognition.
Combining Petrology and Seismology to Unravel the Plumbing System of a Typical Arc Volcano: An Example From Marapi, West Sumatra, Indonesia

Marapi in Sumatra is characterized by frequent short‐lived explosions and small eruptions (Volcanic Explosivity Index 1–2) and in the past 250 years, the volcano has erupted >60 times. Recent volcanic bombs and the presence of broadband seismic stations lead us to reconstruct the plumbing system of the volcano through an interdisciplinary study. A petrologic study of the summit bombs uses pyroxene, plagioclase and glass compositions to obtain pressures and temperatures of magma storage as well as identify pre‐eruptive processes. Two‐pyroxene geothermobarometry provides pre‐eruptive crystallization pressure estimates of 4–7 kbar (∼15–26 km). Compositional and textural analyses of plagioclase and pyroxene crystals indicate that mafic magma recharge was followed by mixing with the resident magma and renewed crystallization prior to eruption. In order to further image the magma reservoir, we performed a joint inversion of teleseismic receiver functions and surface waves (H/V ratio). The inversion reveals a low velocity zone (LVZ) at depths of 15–21 km that has 7 ± 3% shear velocity reduction, corresponding to an estimated melt fraction of 5 ± 2%. The depth of this LVZ overlaps with the depth of magma storage estimated from petrology, constraining it with high confidence. Such a combined interdisciplinary study provides valuable information for evaluating future periods of unrest, laying out a framework for the interpretation of incoming monitoring data and signals to look out for in order to improve eruption forecasts.
Angiotensin-Converting Enzyme Inhibitor Induced Cough in Chinese Patients: a Systematic Review and Meta-analysis.

PURPOSE To determine the risk of angiotensin converting enzyme inhibitor (ACEI)-induced cough compared to non-ACEI cough among Chinese patients. METHODS A comprehensive search was conducted including randomized controlled trials, case-control studies and observational studies that compared ACEI treatment with control treatment in MEDLINE, EMBASE, CINAHL, Scopus, Google Scholar and ProQuest Dissertations & Theses Global. The studies which contained: Chinese population, ACEI, non-ACEI, and indications for the treatment of ACEI were included. The pooled risk ratios (RRs) and 95% confidence intervals (CIs) were calculated to compare the relative risk of cough between ACEIs and non-ACEI drugs based on the events of reported cough in each study. RESULTS Eleven randomized controlled trials were included with a total of 1815 patients. The total number of cough events in ACEI treatment was 101 in 930 patients (11%) and 20 in 885 patients (2%) in the Non-ACEI treatment. The pooled RR was 5.16 (95% CI: 3.39-7.85) under fixed model. The discontinuation number of single ACEI treatment due to coughing side effect was 21 and the withdrawal rate was 4.13%. Only two patients discontinued non-ACEIs treatment due to the intolerable cough and the withdrawal rate was 0.34%. The overall RR of withdrawal related to cough was 7.06 (95% CI: 2.49-20.04). CONCLUSIONS The pooled risk of the incidence of ACEI-induced cough was about five times higher than that of non-ACEI-induced cough in Chinese population. The risk of withdrawal events related to cough in the single ACEI treatment was seven times of that in the non-ACEI treatment.
Early prediction of clinical response to anti-TNF treatment using multi-omics and machine learning in rheumatoid arthritis

Abstract Objectives Advances in immunotherapy by blocking TNF have remarkably improved treatment outcomes for Rheumatoid arthritis (RA) patients. Although treatment specifically targets TNF, the downstream mechanisms of immune suppression are not completely understood. The aim of this study was to detect biomarkers and expression signatures of treatment response to TNF inhibition. Methods Peripheral blood mononuclear cells (PBMCs) from 39 female patients were collected before anti-TNF treatment initiation (day 0) and after 3 months. The study cohort included patients previously treated with MTX who failed to respond adequately. Response to treatment was defined based on the EULAR criteria and classified 23 patients as responders and 16 as non-responders. We investigated differences in gene expression in PBMCs, the proportion of cell types and cell phenotypes in peripheral blood using flow cytometry and the level of proteins in plasma. Finally, we used machine learning models to predict non-response to anti-TNF treatment. Results The gene expression analysis in baseline samples revealed notably higher expression of the gene EPPK1 in future responders. We detected the suppression of genes and proteins following treatment, including suppressed expression of the T cell inhibitor gene CHI3L1 and its protein YKL-40. The gene expression results were replicated in an independent cohort. Finally, machine learning models mainly based on transcriptomic data showed high predictive utility in classifying non-response to anti-TNF treatment in RA. Conclusions Our integrative multi-omics analyses identified new biomarkers for the prediction of response, found pathways influenced by treatment and suggested new predictive models of anti-TNF treatment in RA patients.