Reducing variability in along-tract analysis with diffusion profile realignment

Diffusion weighted MRI (dMRI) provides a non invasive virtual reconstruction of the brain's white matter structures through tractography. Analyzing dMRI measures along the trajectory of white matter bundles can provide a more specific investigation than considering a region of interest or tract-averaged measurements. However, performing group analyses with this along-tract strategy requires correspondence between points of tract pathways across subjects. This is usually achieved by creating a new common space where the representative streamlines from every subject are resampled to the same number of points. If the underlying anatomy of some subjects was altered due to, e.g. disease or developmental changes, such information might be lost by resampling to a fixed number of points. In this work, we propose to address the issue of possible misalignment, which might be present even after resampling, by realigning the representative streamline of each subject in this 1D space with a new method, coined diffusion profile realignment (DPR). Experiments on synthetic datasets show that DPR reduces the coefficient of variation for the mean diffusivity, fractional anisotropy and apparent fiber density when compared to the unaligned case. Using 100 in vivo datasets from the HCP, we simulated changes in mean diffusivity, fractional anisotropy and apparent fiber density. Pairwise Student's t-tests between these altered subjects and the original subjects indicate that regional changes are identified after realignment with the DPR algorithm, while preserving differences previously detected in the unaligned case. This new correction strategy contributes to revealing effects of interest which might be hidden by misalignment and has the potential to improve the specificity in longitudinal population studies beyond the traditional region of interest based analysis and along-tract analysis workflows.Comment: v4: peer-reviewed round 2 v3 : deleted some old text from before peer-review which was mistakenly included v2 : peer-reviewed version v1: preprint as submitted to journal NeuroImag

Industrial Policy and Renewable Energy: Trade Conflicts

Governments use industrial policy to promote the development of new industries and the creation and adoption of new technologies. Such policy involves subsidies granted to producers and consumers, usually for the purpose of correcting a market failure. Concerning renewable energies such as wind energy and solar energy, China, the United States, and the European Union provide extensive support to producers and consumers. This support has resulted in trade frictions among these nations. This paper discusses the relationship between industrial policy and trade disputes in renewable energy

Музыкальный информационный поиск с запросом по напеву

In this paper the problems of Query by Humming in Music Information Retrieval systems are analyzed. A statistical approach to the problem of retrieval is presented. The processes of segmentation as well as of the extraction of pitch and duration data are described. From the extracted data the characteristic vector is formed for each segment. The method of using the vectors in melodic search if proposed

The Need for a Spiritual Reboot in the Youth of Great Commission Church

The decline of the youth attendance is evident in many Protestant churches. This research paper examined forty-three young believers from three Haitian Baptist churches, respectively, located in Brooklyn, Queens, and the Bronx. These data results help develop a suitable spiritual program that includes the six key influencing factors for spiritual growth: discipleship, mentoring, parental influence, church attendance, personal devotion, and ministerial involvement. This spiritual program was tested on a small group of young people from Great Commission Church in Queens. This research uses a mixed-method methodology, which is a combination of qualitative and quantitative methods to analyze the data. The results show that parental influence can help Haitian youth attend church, but it does not encourage discipleship, mentorship, and ministerial involvement in the church. Further studies should aim at understanding the extent of parental involvement needed to encourage Haitian youth to be involved in the church\u27s ministries

Sea ice dynamics across the Mid-Pleistocene transition in the Bering Sea.

Sea ice and associated feedback mechanisms play an important role for both long- and short-term climate change. Our ability to predict future sea ice extent, however, hinges on a greater understanding of past sea ice dynamics. Here we investigate sea ice changes in the eastern Bering Sea prior to, across, and after the Mid-Pleistocene transition (MPT). The sea ice record, based on the Arctic sea ice biomarker IP25 and related open water proxies from the International Ocean Discovery Program Site U1343, shows a substantial increase in sea ice extent across the MPT. The occurrence of late-glacial/deglacial sea ice maxima are consistent with sea ice/land ice hysteresis and land-glacier retreat via the temperature-precipitation feedback. We also identify interactions of sea ice with phytoplankton growth and ocean circulation patterns, which have important implications for glacial North Pacific Intermediate Water formation and potentially North Pacific abyssal carbon storage

Harmonization of diffusion MRI datasets with adaptive dictionary learning

Diffusion magnetic resonance imaging is a noninvasive imaging technique that can indirectly infer the microstructure of tissues and provide metrics which are subject to normal variability across subjects. Potentially abnormal values or features may yield essential information to support analysis of controls and patients cohorts, but subtle confounds affecting diffusion MRI, such as those due to difference in scanning protocols or hardware, can lead to systematic errors which could be mistaken for purely biologically driven variations amongst subjects. In this work, we propose a new harmonization algorithm based on adaptive dictionary learning to mitigate the unwanted variability caused by different scanner hardware while preserving the natural biological variability present in the data. Overcomplete dictionaries, which are learned automatically from the data and do not require paired samples, are then used to reconstruct the data from a different scanner, removing variability present in the source scanner in the process. We use the publicly available database from an international challenge to evaluate the method, which was acquired on three different scanners and with two different protocols, and propose a new mapping towards a scanner-agnostic space. Results show that the effect size of the four studied diffusion metrics is preserved while removing variability attributable to the scanner. Experiments with alterations using a free water compartment, which is not simulated in the training data, shows that the effect size induced by the alterations is also preserved after harmonization. The algorithm is freely available and could help multicenter studies in pooling their data, while removing scanner specific confounds, and increase statistical power in the process.Comment: v5 Peer review for Human Brain Mapping v4: Peer review round 2 v3: Peer reviewed version v2: Fix minor text issue + add supp materials v1: To be submitted to Neuroimag