Near-critical fluids subject to simultaneous thermal quench and an imposed external acceleration field are reported to develop ‘sink zones’, where the temperature in the bulk falls below the imposed boundary value. This anomalous cooling effect persists for a long period of time corresponding to the diffusive elimination of the cold boundary layer. The sink-zone phenomenon has been captured previously in numerical simulations (Zappoli et al., J. Fluid Mech, vol. 316, 1996, pp. 53–72; Sharma et al., Phys. Rev E, vol. 96, 2017, 063102; Sharma et al., Phys. Fluids, vol. 29, 2017, 126103) and was observed experimentally (Beysens et al., Phys. Rev. E, vol. 84, 2011, 051201). The present work provides a detailed and thorough theoretical analysis and interpretation based on matched asymptotic expansions. By examining the one-dimensional transient flow and temperature with a mean-field approach, we provide further insight into this striking phenomenon, showing that the behaviour involved is unique to highly compressible near-critical van der Waals gases. We also show that the sub-cooling phenomenon cannot be predicted in perfect gases unless very extreme conditions are applied.

Focusing on seven major agricultural commodities with a long history of trade, this study employs data-driven analytics to decipher patterns of trade, namely using supervised machine learning (ML), as well as neural networks. The supervised ML and neural network techniques are trained on data until 2010 and 2014, respectively. Results show the high relevance of ML models to forecasting trade patterns in near- and long-term relative to traditional approaches, which are often subjective assessments or time-series projections. While supervised ML techniques quantified key economic factors underlying agricultural trade flows, neural network approaches provide better fits over the long term.

In the flamelet regime of turbulent premixed combustion the enhancement in the burning rates originates primarily from surface wrinkling. In this work we investigate the Reynolds number dependence of burning rates of spherical turbulent premixed methane/air flames in decaying isotropic turbulence with direct numerical simulations. Several simulations are performed by varying the Reynolds number, while keeping the Karlovitz number the same, and the temporal evolution of the flame surface is compared across cases by combining the probability density function of the radial distance of the flame surface from the origin with the surface density function formalism. Because the mean area of the wrinkled flame surface normalized by the area of a sphere with radius equal to the mean flame radius is proportional to the product of the turbulent flame brush thickness and peak surface density within the brush, the temporal evolution of the brush and peak surface density are investigated separately. The brush thickness is shown to scale with the integral scale of the flow, evolving due to decaying velocity fluctuations and stretch. When normalized by the integral scale, the wrinkling scale defined as the inverse of the peak surface density is shown to scale with Reynolds number across simulations and as turbulence decays. As a result, the area ratio and the burning rate are found to increase as ${Re}_{\lambda }^{1.13}$, in agreement with recent experiments on spherical turbulent premixed flames. We observe that the area ratio does not vary with turbulent intensity when holding the Reynolds number constant.

The emphasis on team science in clinical and translational research increases the importance of collaborative biostatisticians (CBs) in healthcare. Adequate training and development of CBs ensure appropriate conduct of robust and meaningful research and, therefore, should be considered as a high-priority focus for biostatistics groups. Comprehensive training enhances clinical and translational research by facilitating more productive and efficient collaborations. While many graduate programs in Biostatistics and Epidemiology include training in research collaboration, it is often limited in scope and duration. Therefore, additional training is often required once a CB is hired into a full-time position. This article presents a comprehensive CB training strategy that can be adapted to any collaborative biostatistics group. This strategy follows a roadmap of the biostatistics collaboration process, which is also presented. A TIE approach (Teach the necessary skills, monitor the Implementation of these skills, and Evaluate the proficiency of these skills) was developed to support the adoption of key principles. The training strategy also incorporates a “train the trainer” approach to enable CBs who have successfully completed training to train new staff or faculty.

In this paper, three compact, high-efficiency, gain enhanced antennas, and corresponding rectifiers have been proposed for GSM1800, 3G, and 4G-LTE energy harvesting applications. The inverted L-stub is placed on the ground plane of the monopole antenna to get the desired frequency band of GSM1800 MHz. The feed length variation method has been adopted for the slot antennas to obtain the required frequency of 3G and 4G-LTE cellular bands. The performance of antennas is analyzed with the inverted L-stub, feed length variation, and the reflector distance. The maximum gain achieved with the reflector positioned at a distance of λ/4 from the antenna backside is three times greater than the gain obtained without the reflector. The prototype antennas and rectifiers have been simulated, fabricated, measured various parameters, and compared with the simulation results. The antennas provide more than 82% radiation efficiency and an enhanced gain of greater than 5.6 dB. The peak efficiency of rectifiers of more than 30% has been achieved. The aforementioned three antennas are integrated with their corresponding rectifiers for operating at 1.8, 2.1, and 2.3 GHz frequencies. The proposed rectennas are formidably suitable for the reception of RF power from the cellular bands.

This study examined the effect of the Safe Adolescent Transition and Health Initiative (SATHI) programme on the use of maternal care services among rural, pregnant adolescents in India. This was an intensive community-based, multi-site intervention project conducted in Maharashtra state between 2008 and 2011. Its aims were to improve the reproductive health of married adolescent girls and avert the adverse consequences of early motherhood. It had a quasi-experimental, case-control, pre-post design to enable rigorous evaluation. This study used cross-sectional data from 644 married girls aged under 19 years at baseline and 802 at endline to assess the maternal care outcomes of antenatal care, delivery and postnatal services and nutrition during pregnancy. Difference-in-differences analysis showed that all outcomes improved significantly in the study sites between baseline and endline, and the improvement in study sites was significantly larger than in the control sites. Multivariate analysis showed a statistically significant dose–response effect of intervention participation for antenatal care, pregnancy nutrition and postnatal care. Study participation was not statistically significantly associated with higher rates of safe or institutional delivery. The analysis suggests that training and supporting community health workers to work with married adolescent girls using interpersonal communication and interacting frequently with them and their families and communities can significantly improve the use of maternal care services among this population. With almost a million community health workers and 200,000 auxiliary nurse midwives at the community level providing primary level care in India, this intervention offers a proven strategy to replicate and scale-up to reach large numbers of married adolescent girls who do not currently use maternal care services.

No externally validated tests are available for routine use to confirm clinical diagnosis of major psychiatric disorders. Eye movement abnormalities that distinguish schizophrenia and bipolar disorder have only recently been described. Evidence of oculomotor dysfunction specific to endogenous major depressive disorder (MDD) would represent discovery of a significant endophenotypic interface between psychotic and affective disorders. Out-patients meeting DSM criteria for MDD (n=68, F:M=40:28, median age=49 (IQR 38-57) years) participated in a series of tasks while eye movements were recorded using an EyeLink 1000 infra-red video tracker. Patients' characteristics at time of assessment included median illness duration of 13 years (IQR= 7-23; n=53 available cases), HADS anxiety=11 (IQR 7-15) and depression=9 (IQR 4-11), BDI=27 (IQR 16-33), BPRS= 25 (IQR 20-29) and estimated IQ= 106 (IQR 96-118; n=42). Performance measures from smooth pursuit, picture viewing, and steady fixation were analysed alongside data from controls, schizophrenia, and bipolar disorder cases. A neural network was able to delineate the clinical and control groups with sensitivity=90.4% and specificity=97.1%. Multivariate tests of group differences post hoc revealed that MDD cases were on average poorest in maintaining steady gaze during the fixation task, mirroring the neuropsychological evidence for dysregulation of executive function in prefrontal brain regions. Bipolar and unipolar affective cases performed similarly on smooth pursuit and picture viewing tests, but were systematically different from schizophrenia and control groups. If differences are replicated in further cases, the MDD eye movement marker could be an important tool for psychiatric research, allowing for easier delineation of the major disorders.

Major depressive disorder (MDD) affects at some point in their lives a tenth of the world's population with a higher incidence in females than males. Like all clinical disorders encountered in adult psychiatry, a diagnosis of MDD is symptom-based and has not been externally validated. Eye movement dysfunctions (EMDs) in the functional psychoses have been extensively reported and their potential as biomarkers highlighted but it is unclear whether there are patterns of EMDs specific to MDD. Abnormal EMs in bipolar affective cases have been observed during face and picture viewing, saccadic control and smooth pursuit tasks. However most studies reporting EMs in affective disorders, have not distinguished between unipolar/MDD and bipolar cases. to address this problem we have compared performance on a broad range of EM tests in patients meeting DSM-IV criteria for MDD with identical measures made in a large sample of bipolar, schizophrenia and undiagnosed individuals. Remarkably a network classifier was able to delineate controls and each patient group using EM performance measures with exceptional sensitivity (94%) and specificity (98%). What is more, probability of illness category was not associated with demographic, symptom, neuropsychological or medication variables. It therefore appears that a unique multivariate eye movement phenotype may be associated with MDD. If verified in further MDD cases these findings could be an enormous advance in helping to assess and/or diagnose individuals with symptoms of MDD or at risk of developing MDD.

For the first time in the literature, experimental determination of entire sets of exact interdiffusion coefficients in quaternary and quinary alloy systems is reported. Using the method of body-diagonal diffusion couple, a set of nine quaternary interdiffusion coefficients were evaluated in Fe–Ni–Co–Cr and a set of sixteen quinary interdiffusion coefficients were determined in a Fe–Ni–Co–Cr–Mn system, both at approximately equimolar compositions. Regions of uphill interdiffusion and zero flux planes were observed for nickel and cobalt in quinary couples, indicating the existence of strong diffusional interactions in Fe–Ni–Co–Cr–Mn alloys. The strong diffusional interactions were also manifested in the large magnitudes of cross coefficients in both the systems. The existence of strong diffusional interactions in high-entropy alloys (HEAs) as observed through experimentally determined interdiffusion coefficients in this study establishes beyond doubt the fact that cross interdiffusion coefficients cannot be ignored in HEAs.

Wildlife is an essential component of all ecosystems. Most places in the globe do not have local, timely information on which species are present or how their populations are changing. With the arrival of new technologies, camera traps have become a popular way to collect wildlife data. However, data collection has increased at a much faster rate than the development of tools to manage, process and analyse these data. Without these tools, wildlife managers and other stakeholders have little information to effectively manage, understand and monitor wildlife populations. We identify four barriers that are hindering the widespread use of camera trap data for conservation. We propose specific solutions to remove these barriers integrated in a modern technology platform called Wildlife Insights. We present an architecture for this platform and describe its main components. We recognize and discuss the potential risks of publishing shared biodiversity data and a framework to mitigate those risks. Finally, we discuss a strategy to ensure platforms like Wildlife Insights are sustainable and have an enduring impact on the conservation of wildlife.