343,434 research outputs found
Stenus absconditor Hu & Tang
No full text<i>Stenus absconditor</i> Hu & Tang, nomen nov. <p> <i>Stenus absconditus</i> Hu & Tang, 2018: 347.</p> <p> <b>Etymology.</b> The specific name “absconditor” means hidden.</p>Published as part of <i>Hu, Cheng-Zhi & Tang, Liang, 2019, A new name for Stenus absconditus Tang & Hu, 2018 (Coleoptera, Staphylinidae), pp. 443 in Zootaxa 4545 (3)</i> on page 443, DOI: 10.11646/zootaxa.4545.3.9, <a href="http://zenodo.org/record/2619006">http://zenodo.org/record/2619006</a>
A produção de conhecimentos no Serviço Social: uma análise no HU/UFSC
Get PDFTCC (graduação) - Universidade Federal de Santa Catarina, Centro Sócio Econômico, Curso de Serviço Social.O presente Trabalho de Conclusão de Curso, tem como objeto de estudo a produção de conhecimento no Serviço Social, utilizados diariamente pelas Assistentes Sociais do HU/UFSC. Pretende-se com este estudo investigar as modificações ocorridas nos conhecimentos no Serviço Social, que estiveram e estão presentes na atuação profissional do Assistente Social, bem como analisar suas influências no atendimento das demandas apresentadas neste espaço ocupacional. Para realização do trabalho, utilizamos a pesquisa bibliográfica, principalmente nas Revistas Serviço Social e Sociedade e Cadernos da ABESS/ABEPSS e ainda pesquisa documental, com intuito de coletar dados e proceder à análise de conteúdo, ambos com vistas a investigar a abordagem e compreensão dos temas usuário, família, saúde, prática profissional, metodologia e teoria. Observamos que além das transformações na própria profissão de Serviço Social, a qual passou a qualificar seu rigor teórico-metodológico a partir da década de 1990, também ocorreram mudanças na abordagem dos termos no interior do HU/UFSC o que auxiliou na inovação dos atendimentos aos usuários, destacando-se o reconhecimento do cidadão como cidadão de direitos
alexenge/hu-neuro-pipeline: v0.8.0
No full text<p><!-- Release notes generated using configuration in .github/release.yml at main --></p>
<h2>What's Changed</h2>
<h3> Breaking changes</h3>
<ul>
<li>Support different raw EEG input file types beyond BrainVision (Note: Input argument <code>vhdr_files</code> is now called <code>raw_files</code>!) by @alexenge in https://github.com/alexenge/hu-neuro-pipeline/pull/125</li>
<li>Change default for <code>ica_n_components</code> from <code>0.99</code> (i.e., 99% explained variance) to <code>None</code> (all components, usually number of channels minus one) by @alexenge in https://github.com/alexenge/hu-neuro-pipeline/pull/136</li>
</ul>
<h3> Exciting new features</h3>
<ul>
<li>Add functions to download sample data from the ERP CORE dataset by @alexenge in https://github.com/alexenge/hu-neuro-pipeline/pull/122</li>
<li>Support processing of non-BrainVision / non-Abdel Rahman Lab data (e.g., ERP CORE data) by @alexenge in https://github.com/alexenge/hu-neuro-pipeline/pull/127</li>
<li>Keep audio and pulse channels that are not in the montage as "misc" type by @kirstenstark in https://github.com/alexenge/hu-neuro-pipeline/pull/143</li>
<li>Add input argument <code>ref_channels</code> for custom re-referencing (<code>'average'</code> remains the default) by @alexenge in https://github.com/alexenge/hu-neuro-pipeline/pull/146</li>
<li>Improve dataset fetchers (offline mode, <code>path</code> argument, custom list of participants) by @alexenge in https://github.com/alexenge/hu-neuro-pipeline/pull/149</li>
</ul>
<h3> Bug fixes</h3>
<ul>
<li>Rename functions for getting sample datasets (now <code>datasets.get_ucap()</code> and <code>datasets.get_erpcore()</code>) by @alexenge in https://github.com/alexenge/hu-neuro-pipeline/pull/129</li>
<li>Make sure that automatic matching via <code>triggers_column</code> works for non-BrainVision data by @alexenge in https://github.com/alexenge/hu-neuro-pipeline/pull/138</li>
<li>Fix bad epoch rejection for epochs that already have bad epoch markers (e.g., <code>NO_DATA</code>) by @alexenge in https://github.com/alexenge/hu-neuro-pipeline/pull/140</li>
<li>Fix missing manifest files that broke the dataset fetchers by @alexenge in https://github.com/alexenge/hu-neuro-pipeline/pull/151</li>
</ul>
<h3> Documentation</h3>
<ul>
<li>Add ERP CORE example (processing N400 data in Python) to docs by @alexenge in https://github.com/alexenge/hu-neuro-pipeline/pull/130</li>
<li>Switch to MyST-NB (instead of nbsphinx) for rendering doc examples by @alexenge in https://github.com/alexenge/hu-neuro-pipeline/pull/132</li>
<li>Move documentation source files into new <code>doc/source/</code> sub-directory by @alexenge in https://github.com/alexenge/hu-neuro-pipeline/pull/134</li>
<li>Fix some issues in the docs (wrong input arguments, remove tables of content) by @alexenge in https://github.com/alexenge/hu-neuro-pipeline/pull/152</li>
</ul>
<p><strong>Full Changelog</strong>: https://github.com/alexenge/hu-neuro-pipeline/compare/v0.7.0...v0.8.0</p>
Xin wen de shan qing hua chu li yu yue bao ji yi cheng du de guan xi.
No full text胡文芳.論文(哲學碩士) -- 香港中文大學硏究院傳播學部, 1996.參考文献 : leaves 65-70.Hu Wenfang.Chapter 第一章 --- 硏究問題 --- p.3Chapter 第二章 --- 文獻探討 --- p.8Chapter 第三章 --- 研究假設 --- p.22Chapter 第四章 --- 硏究方法 --- p.26Chapter 第五章 --- 實驗結果 --- p.40Chapter 第六章 --- 討論及結語 --- p.60其他 參考資料 --- p.65附件 --- p.7
Phylogenetic tree depicting Wuhan-Hu-1 spike genes analyzed by SGS.
No full text55 control Wuhan-Hu-1 spike genes were amplified by nested PCR using S primers listed in S1 Table. Blue rectangle depicts the WT Wuhan-Hu-1 spike gene. Black rectangles depict the S genes that were amplified. (TIF)</p
Responses to axonal current injection in cortical layer 5 pyramidal neurons
No full textPatch-clamp recordings in cortical layer 5 pyramidal neurons performed by Wenqin Hu. A current pulse is either injected in the soma or in an axonal bleb and recorded simultaneously in the axonal bleb or the soma, respectively.
The data are related to figure 7 of the paper: Hu, W., & Bean, B. P. (2018). Differential control of axonal and somatic resting potential by voltage-dependent conductances in cortical layer 5 pyramidal neurons. Neuron, 97(6), 1315-1326.
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ChaoyiZhang20/Zhang-et-al_Neuron2021_Hailan-Hu-Lab: 2P data analysis code
No full text<p>Test
<a href="https://github.com/ChaoyiZhang20/Zhang-et-al_Neuron2021_Hailan-Hu-Lab/files/7386567/FastICA_2.5.zip">FastICA_2.5.zip</a></p>
Nazeris biwenxuani Hu & Li 2016
No full text<i>Nazeris biwenxuani</i> Hu & Li, 2016 (Fig. 7) <p> <b>Additional material examined. China: Xizang,</b> 2 males, 4 females, 'Bomi, 12.III.2017, Xiao-Bin Song leg.' (SNUC).</p> <p> <b>Comment.</b> The species is similar to <i>N. motuensis</i> Hu, Li & Zhao, 2008 in general appearance and separated by the much narrower apical excision of ventral process of aedeagus and much longer dorso-lateral apophyses.</p> <p> <b>Distribution and habitat data.</b> The species is known only from Bomi in east Xizang (Fig. 7). The specimens were collected by sifting decaying leaf litter in mixed forests at an altitude of 2600 m.</p>Published as part of <i>Hu, Jia-Yao & Pan, Zhao-Hui, 2018, New data of Nazeris Fauvel in Xizang, China (Coleoptera, Staphylinidae, Paederinae), pp. 147-150 in Zootaxa 4531 (1)</i> on page 147, DOI: 10.11646/zootaxa.4531.1.11, <a href="http://zenodo.org/record/2614370">http://zenodo.org/record/2614370</a>
Performance Evaluation of Distributed-Antenna Communications Systems Using Beam-Hopping
No full textDigital beamforming (DBF) techniques are capable of improving the performance of communications systems significantly. However, if the transmitted signals are conflicted with strong interference, especially, in the direction of the transmitted beams , these directional jamming signals will severely degrade the system performance. In order to efficiently mitigate the interference of the directional jammers, in this contribution a beam-hopping (BH) communications scheme is proposed. In the proposed BH communications scheme, only one pair of the beams is used for transmission and it hops from one to the next according to an assigned BH pattern. In this contribution a range of expressions in terms of the average SINR performance have been derived, when both the uplink and downlink are considered. The average SINR performance of the proposed BH scheme and that of the conventional single-beam (SB) as well as multiple-beam (MB) assisted beam-processing schemes have been investigated. Our analysis and results show that the proposed BH scheme is capable of efficiently combating the directional jamming, with the aid of utilizing the directional gain of the beams generated by both the transmitter and the receiver. Furthermore, the BH scheme is capable of reducing the intercept probability of the communications. Therefore, the proposed BH scheme is suitable for communications, when several distributed antenna arrays are available around a mobile
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