Rural development analysis: direction identification measurement and interpretation for public policy purpose applied to four Tennessee counties

The widespread interest In rural development in recent years has led to programs and activities in rural areas but very limited evidence of success in resolving the problems for which they were designed. The present study presents an approach to identification of the needs of the people living in a rural area, objective measurement of the direction of change and current status of the areas identified as needing improvement, and an indication of the effect on other areas of living of the improvement in any one. Rural development is defined as the improvement of any one or more facets of rural living when there is no concomitant resultant deterioration of other facets. The data base for the study included interviews from a random area sample of rural households in four Tennessee counties plus interviews from a purposely selected group identified as knowledgeables because of positions occupied and their long term residence in the county. In addition secondary data from the censuses of population, agriculture, housing and governments and selected state sources were utilized. Areas were identified as needing improvement if the sample respondents classified them as having gotten worse since 1960 or rated them as only fair or poor in 1972 or if the constructed indicators showed a downward trend. Least squares regression analysis was applied to identify the interactional relationship between each facet and the socio-economic characteristics of rural people. A rate of change matrix was constructed for each county based on the Indicators developed for each facet of the socioeconomic environment and each socioeconomic characteristic of the county residents Included In the study with entries other than zero being made only where significant relationships were found based on the sample survey. From the rate of change matrix the effect of Improvement In any one facet on other facets was determined and Identification made of the trade off and supplementary relationships between facets. The results of the study provide a guide to those concerned with development In the study counties and a procedure which could be followed In any locality. The study also Identified gaps in the data base needed for the construction of useful social Indicators with the most glaring gaps relating to churches and religious involvement. Other data short areas Included Informal social participation, recreation and certain family characteristics such as health condition of family members and specific age structure within the household. Comparison of the four study counties showed differing patterns of trade off and supplementary relations between the various facets of the socioeconomic environment which appeared to be related to the differing degrees of Industrialization In the counties

Development of Competency Indexes to Assess Nursing Postgraduate's Tutor

The aim of this study was to develop competency indexes assessing nursingpostgraduate's tutor in China. Based on Iceberg competency theory, a Delphisurvey was carried out. 30 nursing experts in 16 provinces of China wereinvited to rate the importance of indexes and give some comments on thecontent. There were 22 experts taking part in two rounds Delphi study. AKendall's W test also demonstrated experts were well coordinated. Duringthe first round, overall mean scores were high, except for 1 tertiary index.We also added and moved some indexes building on the experts'suggestions. After two rounds, we developed competency indexesappropriate to assess tutots' competencies, consisting of 5 preliminaryindexes, 13 secondary indexes and 68 tertiary indexes. The competencyindexes were validated and scientific, it can be used to assess tutors in China

Observation of Ultrahigh Mobility Surface States in a Topological Crystalline Insulator by Infrared Spectroscopy

Topological crystalline insulators (TCIs) possess metallic surface states protected by crystalline symmetry, which are a versatile platform for exploring topological phenomena and potential applications. However, progress in this field has been hindered by the challenge to probe optical and transport properties of the surface states owing to the presence of bulk carriers. Here we report infrared (IR) reflectance measurements of a TCI, (001) oriented $Pb_{1-x}Sn_{x}Se$ in zero and high magnetic fields. We demonstrate that the far-IR conductivity is unexpectedly dominated by the surface states as a result of their unique band structure and the consequent small IR penetration depth. Moreover, our experiments yield a surface mobility of 40000 $cm^{2}/(Vs)$, which is one of the highest reported values in topological materials, suggesting the viability of surface-dominated conduction in thin TCI crystals. These findings pave the way for exploring many exotic transport and optical phenomena and applications predicted for TCIs

Improving protein secondary structure prediction based on short subsequences with local structure similarity

<p>Abstract</p> <p>Background</p> <p>When characterizing the structural topology of proteins, protein secondary structure (PSS) plays an important role in analyzing and modeling protein structures because it represents the local conformation of amino acids into regular structures. Although PSS prediction has been studied for decades, the prediction accuracy reaches a bottleneck at around 80%, and further improvement is very difficult.</p> <p>Results</p> <p>In this paper, we present an improved dictionary-based PSS prediction method called SymPred, and a meta-predictor called SymPsiPred. We adopt the concept behind natural language processing techniques and propose synonymous words to capture local sequence similarities in a group of similar proteins. A synonymous word is an <it>n-</it>gram pattern of amino acids that reflects the sequence variation in a protein’s evolution. We generate a protein-dependent synonymous dictionary from a set of protein sequences for PSS prediction.</p> <p>On a large non-redundant dataset of 8,297 protein chains (<it>DsspNr-25</it>), the average <it>Q</it>₃ of SymPred and SymPsiPred are 81.0% and 83.9% respectively. On the two latest independent test sets (<it>EVA Set_1</it> and <it>EVA_Set2</it>), the average <it>Q</it>₃ of SymPred is 78.8% and 79.2% respectively. SymPred outperforms other existing methods by 1.4% to 5.4%. We study two factors that may affect the performance of SymPred and find that it is very sensitive to the number of proteins of both known and unknown structures. This finding implies that SymPred and SymPsiPred have the potential to achieve higher accuracy as the number of protein sequences in the NCBInr and PDB databases increases.</p> <p>Conclusions</p> <p>Our experiment results show that local similarities in protein sequences typically exhibit conserved structures, which can be used to improve the accuracy of secondary structure prediction. For the application of synonymous words, we demonstrate an example of a sequence alignment which is generated by the distribution of shared synonymous words of a pair of protein sequences. We can align the two sequences nearly perfectly which are very dissimilar at the sequence level but very similar at the structural level. The SymPred and SymPsiPred prediction servers are available at <url>http://bio-cluster.iis.sinica.edu.tw/SymPred/</url>.</p

Functional Anatomy of Recognition of Chinese Multi-Character Words: Convergent Evidence from Effects of Transposable Nonwords, Lexicality, and Word Frequency

This fMRI study aimed to identify the neural mechanisms underlying the recognition of Chinese multi-character words by partialling out the confounding effect of reaction time (RT). For this purpose, a special type of nonword—transposable nonword—was created by reversing the character orders of real words. These nonwords were included in a lexical decision task along with regular (non-transposable) nonwords and real words. Through conjunction analysis on the contrasts of transposable nonwords versus regular nonwords and words versus regular nonwords, the confounding effect of RT was eliminated, and the regions involved in word recognition were reliably identified. The word-frequency effect was also examined in emerged regions to further assess their functional roles in word processing. Results showed significant conjunctional effect and positive word-frequency effect in the bilateral inferior parietal lobules and posterior cingulate cortex, whereas only conjunctional effect was found in the anterior cingulate cortex. The roles of these brain regions in recognition of Chinese multi-character words were discussed

Structural insights into the gating of DNA passage by the topoisomerase II DNA-gate.

Type IIA topoisomerases (Top2s) manipulate the handedness of DNA crossovers by introducing a transient and protein-linked double-strand break in one DNA duplex, termed the DNA-gate, whose opening allows another DNA segment to be transported through to change the DNA topology. Despite the central importance of this gate-opening event to Top2 function, the DNA-gate in all reported structures of Top2-DNA complexes is in the closed state. Here we present the crystal structure of a human Top2 DNA-gate in an open conformation, which not only reveals structural characteristics of its DNA-conducting path, but also uncovers unexpected yet functionally significant conformational changes associated with gate-opening. This structure further implicates Top2's preference for a left-handed DNA braid and allows the construction of a model representing the initial entry of another DNA duplex into the DNA-gate. Steered molecular dynamics calculations suggests the Top2-catalyzed DNA passage may be achieved by a rocker-switch-type movement of the DNA-gate

Protein subcellular localization prediction of eukaryotes using a knowledge-based approach

<p>Abstract</p> <p>Background</p> <p>The study of protein subcellular localization (PSL) is important for elucidating protein functions involved in various cellular processes. However, determining the localization sites of a protein through wet-lab experiments can be time-consuming and labor-intensive. Thus, computational approaches become highly desirable. Most of the PSL prediction systems are established for single-localized proteins. However, a significant number of eukaryotic proteins are known to be localized into multiple subcellular organelles. Many studies have shown that proteins may simultaneously locate or move between different cellular compartments and be involved in different biological processes with different roles.</p> <p>Results</p> <p>In this study, we propose a knowledge based method, called KnowPred_site, to predict the localization site(s) of both single-localized and multi-localized proteins. Based on the local similarity, we can identify the "related sequences" for prediction. We construct a knowledge base to record the possible sequence variations for protein sequences. When predicting the localization annotation of a query protein, we search against the knowledge base and used a scoring mechanism to determine the predicted sites. We downloaded the dataset from ngLOC, which consisted of ten distinct subcellular organelles from 1923 species, and performed ten-fold cross validation experiments to evaluate KnowPred_site's performance. The experiment results show that KnowPred_siteachieves higher prediction accuracy than ngLOC and Blast-hit method. For single-localized proteins, the overall accuracy of KnowPred_siteis 91.7%. For multi-localized proteins, the overall accuracy of KnowPred_siteis 72.1%, which is significantly higher than that of ngLOC by 12.4%. Notably, half of the proteins in the dataset that cannot find any Blast hit sequence above a specified threshold can still be correctly predicted by KnowPred_site.</p> <p>Conclusion</p> <p>KnowPred_sitedemonstrates the power of identifying related sequences in the knowledge base. The experiment results show that even though the sequence similarity is low, the local similarity is effective for prediction. Experiment results show that KnowPred_siteis a highly accurate prediction method for both single- and multi-localized proteins. It is worth-mentioning the prediction process of KnowPred_siteis transparent and biologically interpretable and it shows a set of template sequences to generate the prediction result. The KnowPred_siteprediction server is available at <url>http://bio-cluster.iis.sinica.edu.tw/kbloc/</url>.</p

A rare, highly aggressive primitive neuroectodermal tumor of the kidney: Case report and literature review

AbstractWe report a case of a 14-year-old boy who initially suffered from a sudden onset of abdominal pain for 2 weeks with a protrusive soft mass over the left upper abdomen. No obvious symptomatic symptoms or body weight loss were observed. However, early lung metastasis was detected after an initial computed tomographic examination. Even after we performed salvage en bloc resection of the huge retroperitoneal tumor after primary neoadjuvant chemotherapy, the final outcome was still poor. A diagnosis according to radiologic findings was uncharacteristic. Finally, a pathologic diagnosis based on histologic and immunohistochemical results revealed a rare renal peripheral primitive neuroectodermal tumor

Correction : Radtke et al. Plasma Treatments and Light Extraction from Fluorinated CVD-Grown (400) Single Crystal Diamond Nanopillars. C 2020, 6, 37

The authors would like to update the XPS spectrum in Figure 3c [...