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This research employs machine learning (Mask Region-Based Convolutional Neural Networks [Mask R-CNN]) and cluster analysis (Density-based spatial clustering of applications with noise [DBSCAN]) to identify more than 20,000 relict charcoal hearths (RCHs) organized in large “fields” within and around State Game Lands (SGLs) in Pennsylvania. This research has two important threads that we hope will advance the archaeological study of landscapes. The first is the significant historical impact of charcoal production, a poorly understood industry of the late eighteenth to early twentieth century, on the historic and present landscape of the United States. Although this research focuses on charcoal production in Pennsylvania, it has broad application for both identifying and contextualizing historical charcoal production throughout the world and for better understanding modern charcoal production. The second thread is the use of open data, open source, and open access tools to conduct this analysis, as well as the open publication of the resultant data. Not only does this research demonstrate the significance of open access tools and data but the open publication of our code as well as our data allow others to replicate our work, to tweak our code and protocols for their own work, and reuse our results.
Both blood- and milk-based biomarkers have been analysed for decades in research settings, although often only in one herd, and without focus on the variation in the biomarkers that are specifically related to herd or diet. Biomarkers can be used to detect physiological imbalance and disease risk and may have a role in precision livestock farming (PLF). For use in PLF, it is important to quantify normal variation in specific biomarkers and the source of this variation. The objective of this study was to estimate the between- and within-herd variation in a number of blood metabolites (β-hydroxybutyrate (BHB), non-esterified fatty acids, glucose and serum IGF-1), milk metabolites (free glucose, glucose-6-phosphate, urea, isocitrate, BHB and uric acid), milk enzymes (lactate dehydrogenase and N-acetyl-β-D-glucosaminidase (NAGase)) and composite indicators for metabolic imbalances (Physiological Imbalance-index and energy balance), to help facilitate their adoption within PLF. Blood and milk were sampled from 234 Holstein dairy cows from 6 experimental herds, each in a different European country, and offered a total of 10 different diets. Blood was sampled on 2 occasions at approximately 14 days-in-milk (DIM) and 35 DIM. Milk samples were collected twice weekly (in total 2750 samples) from DIM 1 to 50. Multilevel random regression models were used to estimate the variance components and to calculate the intraclass correlations (ICCs). The ICCs for the milk metabolites, when adjusted for parity and DIM at sampling, demonstrated that between 12% (glucose-6-phosphate) and 46% (urea) of the variation in the metabolites’ levels could be associated with the herd-diet combination. Intraclass Correlations related to the herd-diet combination were generally higher for blood metabolites, from 17% (cholesterol) to approximately 46% (BHB and urea). The high ICCs for urea suggest that this biomarker can be used for monitoring on herd level. The low variance within cow for NAGase indicates that few samples would be needed to describe the status and potentially a general reference value could be used. The low ICC for most of the biomarkers and larger within cow variation emphasises that multiple samples would be needed - most likely on the individual cows - for making the biomarkers useful for monitoring. The majority of biomarkers were influenced by parity and DIM which indicate that these should be accounted for if the biomarker should be used for monitoring.
Through autonomic and affective mechanisms, adverse childhood experiences (ACEs) may disrupt the capacity to regulate negative emotions, increasing craving and exacerbating risk for opioid use disorder (OUD) among individuals with chronic pain who are receiving long-term opioid analgesic pharmacotherapy. This study examined associations between ACEs, heart rate variability (HRV) during emotion regulation, and negative emotional cue-elicited craving among a sample of female opioid-treated chronic pain patients at risk for OUD. A sample of women (N = 36, mean age = 51.2 ± 9.5) with chronic pain receiving long-term opioid analgesic pharmacotherapy (mean morphine equivalent daily dose = 87.1 ± 106.9 mg) were recruited from primary care and pain clinics to complete a randomized task in which they viewed and reappraised negative affective stimuli while HRV and craving were assessed. Both ACEs and duration of opioid use significantly predicted blunted HRV during negative emotion regulation and increased negative emotional cue-elicited craving. Analysis of study findings from a multiple-levels-of-analysis approach suggest that exposure to childhood abuse occasions later emotion dysregulation and appetitive responding toward opioids in negative affective contexts among adult women with chronic pain, and thus this vulnerable clinical population should be assessed for OUD risk when initiating a course of extended, high-dose opioids for pain management.
Unbalanced metabolic status in the weeks after calving predisposes dairy cows to metabolic and infectious diseases. Blood glucose, IGF-I, non-esterified fatty acids (NEFA) and β-hydroxybutyrate (BHB) are used as indicators of the metabolic status of cows. This work aims to (1) evaluate the potential of milk mid-IR spectra to predict these blood components individually and (2) to evaluate the possibility of predicting the metabolic status of cows based on the clustering of these blood components. Blood samples were collected from 241 Holstein cows on six experimental farms, at days 14 and 35 after calving. Blood samples were analyzed by reference analysis and metabolic status was defined by k-means clustering (k=3) based on the four blood components. Milk mid-IR analyses were undertaken on different instruments and the spectra were harmonized into a common standardized format. Quantitative models predicting blood components were developed using partial least squares regression and discriminant models aiming to differentiate the metabolic status were developed with partial least squares discriminant analysis. Cross-validations were performed for both quantitative and discriminant models using four subsets randomly constituted. Blood glucose, IGF-I, NEFA and BHB were predicted with respective R2 of calibration of 0.55, 0.69, 0.49 and 0.77, and R2 of cross-validation of 0.44, 0.61, 0.39 and 0.70. Although these models were not able to provide precise quantitative values, they allow for screening of individual milk samples for high or low values. The clustering methodology led to the sharing out of the data set into three groups of cows representing healthy, moderately impacted and imbalanced metabolic status. The discriminant models allow to fairly classify the three groups, with a global percentage of correct classification up to 74%. When discriminating the cows with imbalanced metabolic status from cows with healthy and moderately impacted metabolic status, the models were able to distinguish imbalanced group with a global percentage of correct classification up to 92%. The performances were satisfactory considering the variables are not present in milk, and consequently predicted indirectly. This work showed the potential of milk mid-IR analysis to provide new metabolic status indicators based on individual blood components or a combination of these variables into a global status. Models have been developed within a standardized spectral format, and although robustness should preferably be improved with additional data integrating different geographic regions, diets and breeds, they constitute rapid, cost-effective and large-scale tools for management and breeding of dairy cows.
Different diagnostic interviews are used as reference standards for major depression classification in research. Semi-structured interviews involve clinical judgement, whereas fully structured interviews are completely scripted. The Mini International Neuropsychiatric Interview (MINI), a brief fully structured interview, is also sometimes used. It is not known whether interview method is associated with probability of major depression classification.
To evaluate the association between interview method and odds of major depression classification, controlling for depressive symptom scores and participant characteristics.
Data collected for an individual participant data meta-analysis of Patient Health Questionnaire-9 (PHQ-9) diagnostic accuracy were analysed and binomial generalised linear mixed models were fit.
A total of 17 158 participants (2287 with major depression) from 57 primary studies were analysed. Among fully structured interviews, odds of major depression were higher for the MINI compared with the Composite International Diagnostic Interview (CIDI) (odds ratio (OR) = 2.10; 95% CI = 1.15–3.87). Compared with semi-structured interviews, fully structured interviews (MINI excluded) were non-significantly more likely to classify participants with low-level depressive symptoms (PHQ-9 scores ≤6) as having major depression (OR = 3.13; 95% CI = 0.98–10.00), similarly likely for moderate-level symptoms (PHQ-9 scores 7–15) (OR = 0.96; 95% CI = 0.56–1.66) and significantly less likely for high-level symptoms (PHQ-9 scores ≥16) (OR = 0.50; 95% CI = 0.26–0.97).
The MINI may identify more people as depressed than the CIDI, and semi-structured and fully structured interviews may not be interchangeable methods, but these results should be replicated.
Declaration of interest
Drs Jetté and Patten declare that they received a grant, outside the submitted work, from the Hotchkiss Brain Institute, which was jointly funded by the Institute and Pfizer. Pfizer was the original sponsor of the development of the PHQ-9, which is now in the public domain. Dr Chan is a steering committee member or consultant of Astra Zeneca, Bayer, Lilly, MSD and Pfizer. She has received sponsorships and honorarium for giving lectures and providing consultancy and her affiliated institution has received research grants from these companies. Dr Hegerl declares that within the past 3 years, he was an advisory board member for Lundbeck, Servier and Otsuka Pharma; a consultant for Bayer Pharma; and a speaker for Medice Arzneimittel, Novartis, and Roche Pharma, all outside the submitted work. Dr Inagaki declares that he has received grants from Novartis Pharma, lecture fees from Pfizer, Mochida, Shionogi, Sumitomo Dainippon Pharma, Daiichi-Sankyo, Meiji Seika and Takeda, and royalties from Nippon Hyoron Sha, Nanzando, Seiwa Shoten, Igaku-shoin and Technomics, all outside of the submitted work. Dr Yamada reports personal fees from Meiji Seika Pharma Co., Ltd., MSD K.K., Asahi Kasei Pharma Corporation, Seishin Shobo, Seiwa Shoten Co., Ltd., Igaku-shoin Ltd., Chugai Igakusha and Sentan Igakusha, all outside the submitted work. All other authors declare no competing interests. No funder had any role in the design and conduct of the study; collection, management, analysis and interpretation of the data; preparation, review or approval of the manuscript; and decision to submit the manuscript for publication.
To achieve their conservation goals individuals, communities and organizations need to acquire a diversity of skills, knowledge and information (i.e. capacity). Despite current efforts to build and maintain appropriate levels of conservation capacity, it has been recognized that there will need to be a significant scaling-up of these activities in sub-Saharan Africa. This is because of the rapid increase in the number and extent of environmental problems in the region. We present a range of socio-economic contexts relevant to four key areas of African conservation capacity building: protected area management, community engagement, effective leadership, and professional e-learning. Under these core themes, 39 specific recommendations are presented. These were derived from multi-stakeholder workshop discussions at an international conference held in Nairobi, Kenya, in 2015. At the meeting 185 delegates (practitioners, scientists, community groups and government agencies) represented 105 organizations from 24 African nations and eight non-African nations. The 39 recommendations constituted six broad types of suggested action: (1) the development of new methods, (2) the provision of capacity building resources (e.g. information or data), (3) the communication of ideas or examples of successful initiatives, (4) the implementation of new research or gap analyses, (5) the establishment of new structures within and between organizations, and (6) the development of new partnerships. A number of cross-cutting issues also emerged from the discussions: the need for a greater sense of urgency in developing capacity building activities; the need to develop novel capacity building methodologies; and the need to move away from one-size-fits-all approaches.
Our knowledge of the universe comes from recording the photon and particle fluxes incident on the Earth from space. We thus require sensitive measurement across the entire energy spectrum, using large telescopes with efficient instrumentation located on superb sites. Technological advances and engineering constraints are nearing the point where we are recording as many photons arriving at a site as is possible. Major advances in the future will come from improving the quality of the site. The ultimate site is, of course, beyond the Earth’s atmosphere, such as on the Moon, but economic limitations prevent our exploiting this avenue to the degree that the scientific community desires. Here we describe an alternative, which offers many of the advantages of space for a fraction of the cost: the Antarctic Plateau.
Being physically assaulted is known to increase the risk of the occurrence of post-traumatic stress disorder (PTSD) symptoms but it may also skew judgements about the intentions of other people. The objectives of the study were to assess paranoia and PTSD after an assault and to test whether theory-derived cognitive factors predicted the persistence of these problems.
At 4 weeks after hospital attendance due to an assault, 106 people were assessed on multiple symptom measures (including virtual reality) and cognitive factors from models of paranoia and PTSD. The symptom measures were repeated 3 and 6 months later.
Factor analysis indicated that paranoia and PTSD were distinct experiences, though positively correlated. At 4 weeks, 33% of participants met diagnostic criteria for PTSD, falling to 16% at follow-up. Of the group at the first assessment, 80% reported that since the assault they were excessively fearful of other people, which over time fell to 66%. Almost all the cognitive factors (including information-processing style during the trauma, mental defeat, qualities of unwanted memories, self-blame, negative thoughts about self, worry, safety behaviours, anomalous internal experiences and cognitive inflexibility) predicted later paranoia and PTSD, but there was little evidence of differential prediction.
Paranoia after an assault may be common and distinguishable from PTSD but predicted by a strikingly similar range of factors.
The formal commissioning of the IRWG occurred at the 1991 Buenos Aires General Assembly, following a Joint Commission meeting at the IAU GA in Baltimore in 1988 that identified the problems with ground-based infrared photometry. The meeting justification, papers, and conclusions, can be found in Milone (1989). In summary, the challenges involved how to explain the failure to achieve the milli-magnitude precision expected of infrared photometry and an apparent 3% limit on system transformability. The proposed solution was to redefine the broadband Johnson system, the passbands of which had proven so unsatisfactory that over time effectively different systems proliferated, although bearing the same “JHKLMNQ” designations; the new system needed to be better positioned and centered in the spectral windows of the Earth's atmosphere, and the variable water vapour content of the atmosphere needed to be measured in real time to better correct for atmospheric extinction.
Human serum high-density lipoprotein (HDL) is necessary and sufficient for the short-term maintenance of Plasmodium falciparum in in vitro culture. However, at high concentrations it is toxic to the parasite. A heat-labile component is apparently responsible for the stage-specific toxicity to parasites within infected erythrocytes 12–42 h after invasion, i.e. during trophozoite maturation. The effects of HDL on parasite metabolism (as determined by nucleic acid synthesis) are evident at about 30 h after invasion. Parasites treated with HDL show gross abnormalities by light and electron microscopy.
Electromigration (EM) failure statistics and the origin of the lognormal
deviation (σ) for Cu interconnects have been investigated by analyzing the
lifetime statistics and void size distributions at various stages during EM
testing. Experiments were performed on 0.18 μm wide Cu interconnects with
tests terminated after specific amounts of resistance increases, or after a
specified test time. Void size distributions of resistance-based, as well as
time-based EM tests were obtained using focused ion beam (FIB) microscopy.
The lifetime and void size distributions were found to follow lognormal
distribution functions. The σ values of EM lifetime and time-based void size
distributions decrease with higher percentages of resistance increase,
reaching an asymptotic value of σ ∼ 0.14. In contrast, σ values of
resistance-based void size distributions are significantly smaller and do
not show an obvious dependence on time. The statistics of resistance-based
void size distributions can mainly be accounted for by geometrical
variations of the void shape, while the statistics of time-based void size
distributions requires consideration of kinetic aspects of the EM process.
The σ values of EM lifetime distributions at long times can be simulated
based on measured void size distributions, taking into account geometrical
and experimental factors of EM. In contrast, for short times the statistics
of initial void formation and the kinetics of interfacial mass transport
have to be considered.
Dry etching of silver for the metallization in microelectronics is
investigated. Etching is performed using an electron-cyclotron-resonance
reactive-ion-beam-etching system (ECR-RIBE) in an Ar/CF4 or
Ar/CF4/O2 mixture. The etch characteristics are
strongly affected by ion energy (beam voltage and microwave energy); the
O2 concentration in the reactive mixture has only a small
effect. An anisotropic, smooth etch profile and clean surface are obtained.
Focused ion beam (FIB) and atomic force microscopy (AFM) have been used to
study the etched profile and the roughness, respectively.