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Getting Clojure : build your functional skills one idea at a time
\"Learning Clojure involves much more than just learning the mechanics. To really get Clojure you need to understand the ideas underlying its structure and features. This accessible introduction to Clojure focuses on the ideas behind the language as well as the practical details of writing code. Explore the syntax and the mechanics behind each language feature, and then dig into the deeper questions: What is the thinking behind the feature? How does it fit with the rest of the language? Learn Clojure's simple syntax, and why that syntax is integral to the way the language is constructed. Discover why Clojure's immutable data structures lead to more reliable programs. See how easy it is to write Clojure functions and how you can use them to build complex and capable systems. Use real-world examples to see the challenges of programming through the eye of experienced Clojure developers.\"-- Provided by publisher
Book
Object Recognition, Segmentation, and Classification of Mobile Laser Scanning Point Clouds: A State of the Art Review
Mobile Laser Scanning (MLS) is a versatile remote sensing technology based on Light Detection and Ranging (lidar) technology that has been utilized for a wide range of applications. Several previous reviews focused on applications or characteristics of these systems exist in the literature, however, reviews of the many innovative data processing strategies described in the literature have not been conducted in sufficient depth. To this end, we review and summarize the state of the art for MLS data processing approaches, including feature extraction, segmentation, object recognition, and classification. In this review, we first discuss the impact of the scene type to the development of an MLS data processing method. Then, where appropriate, we describe relevant generalized algorithms for feature extraction and segmentation that are applicable to and implemented in many processing approaches. The methods for object recognition and point cloud classification are further reviewed including both the general concepts as well as technical details. In addition, available benchmark datasets for object recognition and classification are summarized. Further, the current limitations and challenges that a significant portion of point cloud processing techniques face are discussed. This review concludes with our future outlook of the trends and opportunities of MLS data processing algorithms and applications.
Journal Article
Inversions of landslide strength as a proxy for subsurface weathering
Distributions of landslide size are hypothesized to reflect hillslope strength, and consequently weathering patterns. However, the association of weathering and critical zone architecture with mechanical strength properties of parent rock and soil are poorly-constrained. Here we use three-dimensional stability to analyze 7330 landslides in western Oregon to infer combinations of strength - friction angles and cohesion - through analysis of both failed and reconstructed landslide terrain. Under a range of conditions, our results demonstrate that the failure envelope that relates shear strength and normal stress in landslide terrain is nonlinear owing to an exchange in strength with landslide thickness. Despite the variability in material strength at large scales, the observed gradient in proportional cohesive strength with landslide thickness may serve as a proxy for subsurface weathering. We posit that the observed relationships between strength and landslide thickness are associated with the coalescence of zones of low shear strength driven by fractures and weathering, which constitutes a first-order control on the mechanical behavior of underlying soil and rock mass.
Bedrock weathering is associated with landslides, and also manifests as a change in the strength of subsurface materials. This study analyzes inventoried landslides to explore relationships between strength and landslide depth as a potential reflection of subsurface weathering at large scales.
Journal Article
Enhancing genetic gain in the era of molecular breeding
As one of the important concepts in conventional quantitative genetics and breeding, genetic gain can be defined as the amount of increase in performance that is achieved annually through artificial selection. To develop products that meet the increasing demand of mankind, especially for food and feed, in addition to various industrial uses, breeders are challenged to enhance the potential of genetic gain continuously, at ever higher rates, while they close the gaps that remain between the yield potential in breeders’ demonstration trials and the actual yield in farmers’ fields. Factors affecting genetic gain include genetic variation available in breeding materials, heritability for traits of interest, selection intensity, and the time required to complete a breeding cycle. Genetic gain can be improved through enhancing the potential and closing the gaps, which has been evolving and complemented with modern breeding techniques and platforms, mainly driven by molecular and genomic tools, combined with improved agronomic practice. Several key strategies are reviewed in this article. Favorable genetic variation can be unlocked and created through molecular and genomic approaches including mutation, gene mapping and discovery, and transgene and genome editing. Estimation of heritability can be improved by refining field experiments through well-controlled and precisely assayed environmental factors or envirotyping, particularly for understanding and controlling spatial heterogeneity at the field level. Selection intensity can be significantly heightened through improvements in the scale and precision of genotyping and phenotyping. The breeding cycle time can be shortened by accelerating breeding procedures through integrated breeding approaches such as marker-assisted selection and doubled haploid development. All the strategies can be integrated with other widely used conventional approaches in breeding programs to enhance genetic gain. More transdisciplinary approaches, team breeding, will be required to address the challenge of maintaining a plentiful and safe food supply for future generations. New opportunities for enhancing genetic gain, a high efficiency breeding pipeline, and broad-sense genetic gain are also discussed prospectively.
Journal Article
A call to action and a lifecourse strategy to address the global burden of raised blood pressure on current and future generations: the Lancet Commission on hypertension
The aim of the Lancet Commission on hypertension is to identify key actions to improve the management of blood pressure both at the population and the individual level, and to generate a campaign to adopt the suggested actions at national levels to reduce the impact of elevated blood pressure globally. The first task of the Commission is this report, which briefly reviews the available evidence for prevention, identification, and treatment of elevated blood pressure, hypertension, and its cardiovascular complications.
Journal Article
Impact of Age and Gender on the Prevalence and Prognostic Importance of the Metabolic Syndrome and Its Components in Europeans. The MORGAM Prospective Cohort Project
To investigate the influence of age and gender on the prevalence and cardiovascular disease (CVD) risk in Europeans presenting with the Metabolic Syndrome (MetS).
Using 36 cohorts from the MORGAM-Project with baseline between 1982-1997, 69094 men and women aged 19-78 years, without known CVD, were included. During 12.2 years of follow-up, 3.7%/2.1% of men/women died due to CVD. The corresponding percentages for fatal and nonfatal coronary heart disease (CHD) and stroke were 8.3/3.8 and 3.1/2.5.
The prevalence of MetS, according to modified definitions of the International Diabetes Federation (IDF) and the revised National Cholesterol Education Program-Adult Treatment Panel III (NCEP-ATPIII), increased across age groups for both genders (P<0.0001); with a 5-fold increase in women from ages 19-39 years to 60-78 years (7.4%/7.6% to 35.4%/37.6% for IDF/NCEP-ATPIII) and a 2-fold increase in men (5.3%/10.5% to 11.5%/21.8%). Using multivariate-adjusted Cox regressions, the associations between MetS and all three CVD events were significant (P<0.0001). For IDF/NCEP-ATPIII in men and women, hazard ratio (HR) for CHD was 1.60/1.62 and 1.93/2.03, for CVD mortality 1.73/1.65 and 1.77/2.06, and for stroke 1.51/1.53 and 1.58/1.77. Whereas in men the HRs for CVD events were independent of age (MetS*age, P>0.05), in women the HRs for CHD declined with age (HRs 3.23/3.98 to 1.55/1.56; MetS*age, P=0.01/P=0.001 for IDF/NCEP-ATPIII) while the HRs for stroke tended to increase (HRs 1.31/1.25 to 1.55/1.83; MetS*age, P>0.05).
In Europeans, both age and gender influenced the prevalence of MetS and its prognostic significance. The present results emphasise the importance of being critical of MetS in its current form as a marker of CVD especially in women, and advocate for a redefinition of MetS taking into account age especially in women.
Journal Article
The influence of computer‐assisted obligatory processing tasks on L2 Spanish object pronouns
Evidence that L2 learners of Spanish overgeneralize indirect object pronouns (OPs) to direct object contexts with human referents and direct OPs to indirect object contexts with nonhuman referents has been provided by Zyzik (2006), Malovrh (2008), and Olsen and Juffs (2022). However, the effect of instruction on this phenomenon has not been investigated. This study addresses the influence of instruction on preempting (Rutherford, 1989) an Animacy‐based system in L2 learners of Spanish by investigating whether instruction led learners to use a Case‐based OP system rather than an Animacy‐based system and at what level instruction was most beneficial. Data were collected from 115 L2 learners divided into two groups (instructed and control) who completed comprehension and production tasks at two different times (pretest, posttest). Between the pretest and posttest, learners in the instructed group received instruction on Spanish OPs using the PACE model for grammar instruction. Results from mixed analysis of variances indicate preemption of an Animacy‐based system in both learner groups. This finding is taken as evidence that the tasks themselves led learners to change their OP systems by forcing learners to process the object pronouns and notice additional possible contexts. Instruction is often assumed to lead to language learning, but there are many unanswered questions surrounding how instruction affects language development. How does instruction affect the interlanguage grammar? Are there particular instructional techniques that are more effective for helping learners acquire certain form‐meaning mappings? This article explores the effect of instruction on L2 Spanish object pronouns.
Journal Article
Fixed-dose combination antihypertensive medications
Combining two medicines in a single pill can be cost-neutral and has important benefits for patients and for health systems, including improved patient adherence to daily medication regimens, which may improve clinical outcomes;2 improved blood pressure control rates and shortened time to blood pressure control;3 and more efficient hypertension management for health systems by simplifying drug supply and procurement logistics. In an analysis of more than 30 initial dual versus initial monotherapy trials, withdrawals due to adverse events were uncommon with two-drug combinations of a low-to-standard dose, with no significant difference in adverse events compared with those associated with standard-dose monotherapy.3 As organisations with a shared goal of improving hypertension control worldwide, the American Heart Association, European Society of Hypertension, International Society of Hypertension, Lancet Commission on Hypertension Group, Latin American Society of Hypertension, Resolve to Save Lives, World Heart Federation, World Hypertension League, and World Stroke Organization commend WHO for making single-pill combination antihypertensive medications more widely available by including them in the WHO Essential Medicines List. ACC/AHA 2017 ESC/ESH 2018 India 2013 China 2010 Thailand 2015 LASH 2017 WHO HEARTS When to use two blood pressure lowering drugs Not controlled on monotherapy Yes Yes Yes Yes Yes Yes Yes Initial treatment for all individuals No Yes* No No No Yes No Initial treatment for selected individuals, eg, those who are >20/10 mm Hg from goal† or at high cardiovascular risk Yes Yes Yes Yes Yes Yes* Yes When to use single-pill combinations Recommended to substitute for separate pills to improve adherence Yes Yes Yes Yes NR Yes NR Table Selected hypertension guidelines' recommendations for dual combination and fixed-dose combinations
Journal Article
Genome-Wide Association Mapping and Genomic Prediction Analyses Reveal the Genetic Architecture of Grain Yield and Flowering Time Under Drought and Heat Stress Conditions in Maize
Drought stress (DS) is a major constraint to maize yield production. Heat stress (HS) alone and in combination with DS are likely to become the increasing constraints. Association mapping and genomic prediction (GP) analyses were conducted in a collection of 300 tropical and subtropical maize inbred lines to reveal the genetic architecture of grain yield and flowering time under well-watered (WW), DS, HS, and combined DS and HS conditions. Out of the 381,165 genotyping-by-sequencing SNPs, 1549 SNPs were significantly associated with all the 12 trait-environment combinations, the average PVE (phenotypic variation explained) by these SNPs was 4.33%, and 541 of them had a PVE value greater than 5%. These significant associations were clustered into 446 genomic regions with a window size of 20 Mb per region, and 673 candidate genes containing the significantly associated SNPs were identified. In addition, 33 hotspots were identified for 12 trait-environment combinations and most were located on chromosomes 1 and 8. Compared with single SNP-based association mapping, the haplotype-based associated mapping detected fewer number of significant associations and candidate genes with higher PVE values. All the 688 candidate genes were enriched into 15 gene ontology terms, and 46 candidate genes showed significant differential expression under the WW and DS conditions. Association mapping results identified few overlapped significant markers and candidate genes for the same traits evaluated under different managements, indicating the genetic divergence between the individual stress tolerance and the combined drought and HS tolerance. The GP accuracies obtained from the marker-trait associated SNPs were relatively higher than those obtained from the genome-wide SNPs for most of the target traits. The genetic architecture information of the grain yield and flowering time revealed in this study, and the genomic regions identified for the different trait-environment combinations are useful in accelerating the efforts on rapid development of the stress-tolerant maize germplasm through marker-assisted selection and/or genomic selection.
Journal Article
An Efficient Framework for Mobile Lidar Trajectory Reconstruction and Mo-norvana Segmentation
Mobile laser scanning (MLS, or mobile lidar) is a 3-D data acquisition technique that has been widely used in a variety of applications in recent years due to its high accuracy and efficiency. However, given the large data volume and complexity of the point clouds, processing MLS data can be still challenging with respect to effectiveness, efficiency, and versatility. This paper proposes an efficient MLS data processing framework for general purposes consisting of three main steps: trajectory reconstruction, scan pattern grid generation, and Mo-norvana (Mobile Normal Variation Analysis) segmentation. We present a novel approach to reconstructing the scanner trajectory, which can then be used to structure the point cloud data into a scan pattern grid. By exploiting the scan pattern grid, point cloud segmentation can be performed using Mo-norvana, which is developed based on our previous work for processing Terrestrial Laser Scanning (TLS) data, normal variation analysis (Norvana). In this work, with an unorganized MLS point cloud as input, the proposed framework can complete various tasks that may be desired in many applications including trajectory reconstruction, data structuring, data visualization, edge detection, feature extraction, normal estimation, and segmentation. The performance of the proposed procedures are experimentally evaluated both qualitatively and quantitatively using multiple MLS datasets via the results of trajectory reconstruction, visualization, and segmentation. The efficiency of the proposed method is demonstrated to be able to handle a large dataset stably with a fast computation speed (about 1 million pts/sec. with 8 threads) by taking advantage of parallel programming.
Journal Article