987 research outputs found
Lakota Times Indian Country Today Cumulative Index: January 1991 - December 1995
This index provides subject access to the Lakota Times and Indian Country Today cumulating the annual indexes covering 1991 through 1995. The Lakota Times changed its title to Indian Country Today in October, 1992. In 1995, Indian Country Today began publishing a separate Southwest edition. This index covers the Northern Plains edition only
Locomotor adaptation to a powered ankle-foot orthosis depends on control method
<p>Abstract</p> <p>Background</p> <p>We studied human locomotor adaptation to powered ankle-foot orthoses with the intent of identifying differences between two different orthosis control methods. The first orthosis control method used a footswitch to provide bang-bang control (a kinematic control) and the second orthosis control method used a proportional myoelectric signal from the soleus (a physiological control). Both controllers activated an artificial pneumatic muscle providing plantar flexion torque.</p> <p>Methods</p> <p>Subjects walked on a treadmill for two thirty-minute sessions spaced three days apart under either footswitch control (n = 6) or myoelectric control (n = 6). We recorded lower limb electromyography (EMG), joint kinematics, and orthosis kinetics. We compared stance phase EMG amplitudes, correlation of joint angle patterns, and mechanical work performed by the powered orthosis between the two controllers over time.</p> <p>Results</p> <p>During steady state at the end of the second session, subjects using proportional myoelectric control had much lower soleus and gastrocnemius activation than the subjects using footswitch control. The substantial decrease in triceps surae recruitment allowed the proportional myoelectric control subjects to walk with ankle kinematics close to normal and reduce negative work performed by the orthosis. The footswitch control subjects walked with substantially perturbed ankle kinematics and performed more negative work with the orthosis.</p> <p>Conclusion</p> <p>These results provide evidence that the choice of orthosis control method can greatly alter how humans adapt to powered orthosis assistance during walking. Specifically, proportional myoelectric control results in larger reductions in muscle activation and gait kinematics more similar to normal compared to footswitch control.</p
The geography of recent genetic ancestry across Europe
The recent genealogical history of human populations is a complex mosaic
formed by individual migration, large-scale population movements, and other
demographic events. Population genomics datasets can provide a window into this
recent history, as rare traces of recent shared genetic ancestry are detectable
due to long segments of shared genomic material. We make use of genomic data
for 2,257 Europeans (the POPRES dataset) to conduct one of the first surveys of
recent genealogical ancestry over the past three thousand years at a
continental scale. We detected 1.9 million shared genomic segments, and used
the lengths of these to infer the distribution of shared ancestors across time
and geography. We find that a pair of modern Europeans living in neighboring
populations share around 10-50 genetic common ancestors from the last 1500
years, and upwards of 500 genetic ancestors from the previous 1000 years. These
numbers drop off exponentially with geographic distance, but since genetic
ancestry is rare, individuals from opposite ends of Europe are still expected
to share millions of common genealogical ancestors over the last 1000 years.
There is substantial regional variation in the number of shared genetic
ancestors: especially high numbers of common ancestors between many eastern
populations likely date to the Slavic and/or Hunnic expansions, while much
lower levels of common ancestry in the Italian and Iberian peninsulas may
indicate weaker demographic effects of Germanic expansions into these areas
and/or more stably structured populations. Recent shared ancestry in modern
Europeans is ubiquitous, and clearly shows the impact of both small-scale
migration and large historical events. Population genomic datasets have
considerable power to uncover recent demographic history, and will allow a much
fuller picture of the close genealogical kinship of individuals across the
world.Comment: Full size figures available from
http://www.eve.ucdavis.edu/~plralph/research.html; or html version at
http://ralphlab.usc.edu/ibd/ibd-paper/ibd-writeup.xhtm
Identity-by-descent filtering as a tool for the identification of disease alleles in exome sequence data from distant relatives
Large-scale, deep resequencing may be the next logical step in the genetic investigation of common complex diseases. Because each individual is likely to carry many thousands of variants, the identification of causal alleles requires an efficient strategy to reduce the number of candidate variants. Under many genetic models, causal alleles can be expected to reside within identity-by-descent (IBD) regions shared by affected relatives. In distant relatives, IBD regions constitute a small portion of the genome and can thus greatly reduce the search space for causal alleles. However, the effectiveness of this strategy is unknown. We test the simulated mini-exome data set in extended pedigrees provided by Genetic Analysis Workshop 17. At the fourth- and fifth-degree level of relatedness, case-case pairs shared between 1% and 9% of the genome identical by descent. As expected, no genes were shared identical by descent by all case subjects, but 43 genes were shared by many case subjects across at least 50 replicates. We filtered variants in these genes based on population frequency, function, informativeness, and evidence of association using the family-based association test. This analysis highlighted five genes previously implicated in triglyceride, lipid, and cholesterol metabolism. Comparison with the list of true risk alleles revealed that strict IBD filtering followed by association testing of the rarest alleles was the most sensitive strategy. IBD filtering may be a useful strategy for narrowing down the list of candidate variants in exome data, but the optimal degree of relatedness of affected pairs will depend on the genetic architecture of the disease under study
Genetics of callous-unemotional behavior in children
Callous-unemotional behavior (CU) is currently under consideration as a subtyping index for conduct disorder diagnosis. Twin studies routinely estimate the heritability of CU as greater than 50%. It is now possible to estimate genetic influence using DNA alone from samples of unrelated individuals, not relying on the assumptions of the twin method. Here we use this new DNA method (implemented in a software package called Genome-wide Complex Trait Analysis, GCTA) for the first time to estimate genetic influence on CU. We also report the first genome-wide association (GWA) study of CU as a quantitative trait. We compare these DNA results to those from twin analyses using the same measure and the same community sample of 2,930 children rated by their teachers at ages 7, 9 and 12. GCTA estimates of heritability were near zero, even though twin analysis of CU in this sample confirmed the high heritability of CU reported in the literature, and even though GCTA estimates of heritability were substantial for cognitive and anthropological traits in this sample. No significant associations were found in GWA analysis, which, like GCTA, only detects additive effects of common DNA variants. The phrase ‘missing heritability’ was coined to refer to the gap between variance associated with DNA variants identified in GWA studies versus twin study heritability. However, GCTA heritability, not twin study heritability, is the ceiling for GWA studies because both GCTA and GWA are limited to the overall additive effects of common DNA variants, whereas twin studies are not. This GCTA ceiling is very low for CU in our study, despite its high twin study heritability estimate. The gap between GCTA and twin study heritabilities will make it challenging to identify genes responsible for the heritability of CU
The Role of Individual Variables, Organizational Variables and Moral Intensity Dimensions in Libyan Management Accountants’ Ethical Decision Making
This study investigates the association of a broad set of variables with the ethical decision making of management accountants in Libya. Adopting a cross-sectional methodology, a questionnaire including four different ethical scenarios was used to gather data from 229 participants. For each scenario, ethical decision making was examined in terms of the recognition, judgment and intention stages of Rest’s model. A significant relationship was found between ethical recognition and ethical judgment and also between ethical judgment and ethical intention, but ethical recognition did not significantly predict ethical intention—thus providing support for Rest’s model. Organizational variables, age and educational level yielded few significant results. The lack of significance for codes of ethics might reflect their relative lack of development in Libya, in which case Libyan companies should pay attention to their content and how they are supported, especially in the light of the under-development of the accounting profession in Libya. Few significant results were also found for gender, but where they were found, males showed more ethical characteristics than females. This unusual result reinforces the dangers of gender stereotyping in business. Personal moral philosophy and moral intensity dimensions were generally found to be significant predictors of the three stages of ethical decision making studied. One implication of this is to give more attention to ethics in accounting education, making the connections between accounting practice and (in Libya) Islam. Overall, this study not only adds to the available empirical evidence on factors affecting ethical decision making, notably examining three stages of Rest’s model, but also offers rare insights into the ethical views of practising management accountants and provides a benchmark for future studies of ethical decision making in Muslim majority countries and other parts of the developing world
Computer vision and machine learning for robust phenotyping in genome-wide studies
Traditional evaluation of crop biotic and abiotic stresses are time-consuming and labor-intensive limiting the ability to dissect the genetic basis of quantitative traits. A machine learning (ML)-enabled image-phenotyping pipeline for the genetic studies of abiotic stress iron deficiency chlorosis (IDC) of soybean is reported. IDC classification and severity for an association panel of 461 diverse plant-introduction accessions was evaluated using an end-to-end phenotyping workflow. The workflow consisted of a multi-stage procedure including: (1) optimized protocols for consistent image capture across plant canopies, (2) canopy identification and registration from cluttered backgrounds, (3) extraction of domain expert informed features from the processed images to accurately represent IDC expression, and (4) supervised ML-based classifiers that linked the automatically extracted features with expert-rating equivalent IDC scores. ML-generated phenotypic data were subsequently utilized for the genome-wide association study and genomic prediction. The results illustrate the reliability and advantage of ML-enabled image-phenotyping pipeline by identifying previously reported locus and a novel locus harboring a gene homolog involved in iron acquisition. This study demonstrates a promising path for integrating the phenotyping pipeline into genomic prediction, and provides a systematic framework enabling robust and quicker phenotyping through ground-based systems
Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders
Personality is influenced by genetic and environmental factors1
and associated with mental health. However, the underlying
genetic determinants are largely unknown. We identified six
genetic loci, including five novel loci2,3, significantly associated
with personality traits in a meta-analysis of genome-wide
association studies (N = 123,132–260,861). Of these genomewide
significant loci, extraversion was associated with variants
in WSCD2 and near PCDH15, and neuroticism with variants
on chromosome 8p23.1 and in L3MBTL2. We performed a
principal component analysis to extract major dimensions
underlying genetic variations among five personality traits
and six psychiatric disorders (N = 5,422–18,759). The first
genetic dimension separated personality traits and psychiatric
disorders, except that neuroticism and openness to experience
were clustered with the disorders. High genetic correlations
were found between extraversion and attention-deficit–
hyperactivity disorder (ADHD) and between openness and
schizophrenia and bipolar disorder. The second genetic
dimension was closely aligned with extraversion–introversion
and grouped neuroticism with internalizing psychopathology
(e.g., depression or anxiety)
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