Feasibility in the use of the UV-Visible region for the characterization of glucose in deionized water using Arduino 1 / Viabilidad en el uso de la región UV-Visible para la caracterización de glucosa en agua desionizada mediante Arduino 1

ABSTRACT With an estimated approximately 2 million deaths per year, diabetes is one of the top 5 deadliest noncommunicable diseases globally. Although this disease is not fatal, the degradation of the patient's health due to a bad plan to control their glucose levels can have a fatal outcome. In order to lay the foundations for the development of a device that allows estimating glucose levels in some body fluid, we present the results obtained not only for the estimation of glucose in deionized water, but also describe the development and configuration of the created device. After analyzing 50 signals obtained from 5 different glucose concentrations, the feasibility of using the developed device for the analysis is evident, since, considering the K-Nearest Neighbors (KNN) algorithm, all the signals were associated correctly to the glucose group to which they belong.

RESUMEN Con un estimado de aproximadamente 2 millones de muertes por año, la diabetes es una de las 5 enfermedades no transmisibles más mortales a nivel mundial. Aunque esta enfermedad no es mortal, el deterioro de la salud del paciente por un mal plan para controlar sus niveles de glucosa puede tener un desenlace fatal. Con el fin de sentar las bases para el desarrollo de un dispositivo que permita estimar los niveles de glucosa en algún fluido corporal, presentamos los resultados obtenidos no solo para la estimación de glucosa en agua desionizada, sino que también describimos el desarrollo y configuración del dispositivo creado. Luego de analizar 50 señales obtenidos a partir de 5 concentraciones de glucosa diferentes, se evidencia la factibilidad de utilizar el dispositivo desarrollado para el análisis, ya que, considerando el algoritmo K-Nearest Neighbors (KNN), todas las señales se asociaron correctamente al grupo de glucosa al que pertenecen.

Dental non-metric traits of Han and Zhuang people / 解剖学报

[Abstract] Objective To investigate the relationship between the Han, Zhuang and the World populations by comparing the frequency of dental non-metric traits. Methods From 2015 to 2019, ten dental non-metric traits were sampled from He’nan, Jiangsu and Guangxi Zhuang Autonmous Region, with sample size of 1785(674 He’ nan, 547 Jiangsu, 388 Guangxi Han, 176 Guangxi Zhuang). Principal component analysis, multidimensional scaling and neighbor network were carried out. Results East Asian populations could be clearly divided into two major groups, Northeast Asian and Southeast Asian. Han and Zhuang populations were close to the Northeast Asian populations, but were far from the Southeast Asian populations. There were also some north-south differences within Han populations. Conclusion Both Sundadonty and Sinodonty are existed in East Asian populations. Han and Zhuang populations dental non-metric traits are closer to the Sinodonty.

How Complex is COVID-19: Spatiotemporal Variation of Chaotic Nature of the Virus in Indian States

Like other pandemics, COVID‑19 also created a huge socioeconomic imbalance and distress in people. Often, every pandemic is characterized as chaotic and complex. Hence, the nature of the virus spread and deaths should be analyzed to prepare for the next similar pandemic. In this analysis, the popular and well‑known time series in chaos theory is implemented, and the results are deduced for the states of India. The phase space reconstruction algorithm is implemented, and false nearest neighbor (FNN) method is applied to determine the dimensionality, and also Lyapunov exponent of the time series is estimated. The chaotic nature of COVID‑19 cases showed a less severe and low complexity, with the FNN dimension range of 3–5, whereas the COVID‑19 deaths showed moderate complexity with FNN dimensions 2–7. Policymakers should take action on medical availability in rural states and control people’s movement in highly populated areas.

Identification of Medicinal Aconitum Species Based on ITS2 Sequences and Analysis of Genetic Relationship / 中国实验方剂学杂志

ObjectiveThe internal transcribed spacer （ITS） 2 region of ribosomal gene， a DNA barcode， was employed to identify 12 medicinal Aconitum species and the genetic relationship among the species was analyzed. MethodA total of 30 samples of the 12 species were collected. The DNA was extracted with spin column plant genomic DNA kit and the universal primers of ITS2 sequence were used for polymerase chain reaction （PCR） amplification， followed by electrophoresis detection and bi-directional sequencing. The yielded sequences were aligned and spliced by CodonCode Aligner 17.0 and sequence variation was analyzed by MEGA 7.0. The secondary structure was predicted by ITS2 Database and the neighbor-joining （NJ） method was applied to generate the phylogenetic tree. ResultThe ITS2 sequences of the 12 species were 220-221 bp， with the average guanine and cytosine （GC） content of 64.09%， 140 variable sites， 137 informative sites， and 81 conservative sites. The intraspecific genetic distance （K2P） was smaller than the interspecific genetic distance. According to the secondary structures of ITS2 sequences and NJ cluster analysis， A. scaposum， A. sinomontanum， and A. barbatum had close genetic relationship， while the rest nine showed close kinship， particularly A. soongaricum and A. yinschanicum. ConclusionITS2 sequence is of great value for the molecular identification and genetic relationship determination of Aconitum， which provides a new method for the study of ethnomedicine.

O próximo e o ódio: questões da psicanálise na atualidade / The neighbour and the hatred: Our time psychoanalysis' issues / El prójimo y el odio: cuestiones de psicoanálisis en la actualidad

Na contemporaneidade, acirram-se os efeitos estruturais do mal-estar da civilização discutidos por Freud. Nos deteremos naquele que advém da relação com o próximo. Quando a pulsão de morte reproduz uma forma de insatisfação reiterada, o tratamento desse excesso pode recair sobre o corpo do outro que guarda uma diferença de gozo. A maneira como o gozo íntimo ganha forma de estrangeiro habitando, como o pior, o próximo, configura uma suposição de suspeita que sustenta um modo de laço social. Lacan chega a falar que, na matriz de toda fraternidade, está a segregação. Formamos comunidades de gozo e excluímos toda a forma diferente de satisfação que nos ameace. Na atualidade, com o acúmulo do capital, aliado aos efeitos do avanço científico, algo se modificou no laço social e produziu, dessa matriz, uma nova gramática de inimigo, que denominamos sujeito suposto suspeito como um dos nomes do pior. Contra essa lógica, a emancipação e as saídas possíveis que a psicanálise aponta para uma vida em-comum, na solidão da responsabilidade do gozo de cada um, dizem respeito às soluções éticas que enfrentam, desde dentro, todo o idealismo superegóico.

In contemporary times, the structural effects discussed by Freud in the malaise of civilization are intensified. We will dwell on what comes from the relationship with the neighbor. When the death drive reproduces a form of repeated dissatisfaction, the treatment for this excess can fall on the body of the other who has a different satisfaction. The way intimate satisfaction takes shape as a foreigner inhabiting, like the worst, the neighbor, determines an assumption of suspicion that supports a mode of social bonding. Lacan even says that segregation is in the matrix of all fraternity. We create communities of satisfaction and exclude any different form of enjoyment that threatens us. Currently, the accumulation of capital mixed with the effects of scientific advancement brought changes to social bonding and produced, from this matrix, a new grammar for what's enemy. Suspected subject is a naming for the worse. Against this logic, the emancipation and the possible solutions that psychoanalysis suggests for a life in common, in the solitude and responsibility of each one's satisfaction, concerns the ethical solutions that face, from within, all the superegoic idealism.

En los tiempos contemporáneos, los efectos estructurales del malestar de la civilización discutidos por Freud se intensifican. Nos detendremos en el que proviene de la relación con los demás. Cuando el pulsion de la muerte reproduce una forma de insatisfacción repetida, el tratamiento de este exceso puede recaer en el cuerpo del otro, que tiene una diferencia de goce. El goce íntimo es proyectado como extranjero habitando en el prójimo, como si encarnara lo peor que proyectaba sobre él, configura una presunción de sospecha que sustenta un modo de vínculo social. Lacan llega al extremo de decir que la segregación está en el corazón de cada fraternidad. Formamos comunidades de goce y excluimos cualquier forma diferente de satisfacción que nos amenace. Hoy en día, con la acumulación de capital, combinada con los efectos del avance científico, algo ha cambiado en el vínculo social y ha producido, a partir de esta matriz, una nueva gramática del enemigo, que llamamos el sujeto supuesto sospechoso como uno de los nombres de lo peor. Contra esta lógica, la emancipación y las posibles soluciones que apunta el psicoanálisis en una vida común, en la soledad de la responsabilidad del goce de cada uno, conciernen a las soluciones éticas que enfrentan, desde adentro, todo idealismo superegoico.

Identification of Chinese medicine sea snake based on cytochrome B (Cytb) / 中国中药杂志

The identification of species primordium has been one of the hot issues in the identification of traditional Chinese medicine. Sea snake is one of the most valuable Chinese medicinal materials in China. In order to understand the origin and varieties of sea snake in the market, we studied the molecular identification of 46 sea snakes by cytochrome B(Cytb). After comparison and manual correction, the sequence length was 582 bp, and the content of A+T(58.9%) was higher than that of G+C(41.1%). There exist 197 variable sites and 179 parsimony-informative sites of the sequence. There are 44 kinds of sequence alignment with consistency equal to 100%, and 2 kinds equal to 96%. A total of 408 Cytb effective sequences were downloaded from GenBank database, with a total of 68 species. Phylogenetic tree of a total of 454 sea snake sequences with the samples in this study were constructed by neighbor-joining trees and Bayesian inference method, respectively, which can identify 42 samples of medicinal materials, while 4 samples can not be identified because of their low node support. The results showed that the species of the sea snake medicine were at least from 2 genera and 5 species, namely, Aipysurus eydouxii, Hydrophis curtus, H. caerulescen, H. curtus, H. ornatus and H. spiralis. This study suggested that the original species of commercial sea snake are very complex and can provide insight into the identification of sea snakes.

Detecting anomalous growth of skin lesion using threshold-based segmentation algorithm and Fuzzy K-Nearest Neighbor classifier

Context: Skin cancer is a complex and life-threatening disease caused primarily by genetic instability and accumulation of multiple molecular alternations. Aim: Currently, there is a great interest in the prospects of image processing to provide quantitative information about a skin lesion, that can be relevance for the clinical images and also used as a stand-alone cautioning tool. Setting and Design: To accomplish a powerful approach to recognize skin cancer without performing any unnecessary skin biopsies, this article presents a new hybrid technique for the classification of skin images using Firefly with K-Nearest Neighbor algorithm (FKNN). Materials and Methods: FKNN classifier is used to predict and classify skin cancer along with threshold-based segmentation and ABCD feature extraction. Image preprocessing and feature extraction techniques are mandatory for any image-based applications. Statistical Analysis Used: Initially, it is essential to eliminate the illumination variation and the other unwanted shadow areas present in the skin image, which is done by homomorphic filtering called preprocessing. Results: The comparison of our proposed method with other existing methods and a comprehensive discussion is explored based on the obtained results. Conclusion: The proposed FKNN provides a quantitative information about a skin lesion through hybrid KNN and firefly optimization that helps for recognizing the skin cancer efficiently than other technique with low computational complexity and time

Human activity recognition based on the inertial information and convolutional neural network / 生物医学工程学杂志

With the rapid improvement of the perception and computing capacity of mobile devices such as smart phones, human activity recognition using mobile devices as the carrier has been a new research hot-spot. The inertial information collected by the acceleration sensor in the smart mobile device is used for human activity recognition. Compared with the common computer vision recognition, it has the following advantages: convenience, low cost, and better reflection of the essence of human motion. Based on the WISDM data set collected by smart phones, the inertial navigation information and the deep learning algorithm-convolutional neural network (CNN) were adopted to build a human activity recognition model in this paper. The K nearest neighbor algorithm (KNN) and the random forest algorithm were compared with the CNN network in the recognition accuracy to evaluate the performance of the CNN network. The classification accuracy of CNN model reached 92.73%, which was much higher than KNN and random forest. Experimental results show that the CNN algorithm model can achieve more accurate human activity recognition and has broad application prospects in predicting and promoting human health.

Spatial and temporal distribution of Gymnorhamphichthys rondoni (Gymnotiformes: Rhamphichthyidae) in a long-term study of an Amazonian terra firme stream, Leticia - Colombia

Weakly electric fishes continually emit electric organ discharges (EOD) as a means of communication and localization of objects in their surroundings. Depending on water conductivity, the amplitude of the electric field generated is known to increase with decreases in electrical conductivity of the water. In Amazonian terra firme streams, water conductivity is extremely low and fluctuates constantly due to local and regional rains. In this context, the space between freely moving weakly electric fishes may be expected to decrease, on average, with an increase in water conductivity. To test this hypothesis, we recorded the positions at rest of the sand-dwelling fish Gymnorhamphichthys rondoni in a terra firme stream for several days in alternating months, over two years. Based on daily nearest neighbor distances among individual fish in a grid, we found a uniform temporal distribution pattern (which was not affected by water conductivity) indicative of site fidelity. Here we highlight the role of other factors that could influence resting site fidelity.(AU)

Los peces eléctricos emiten continuamente descargas con su órgano eléctrico (DOE) para comunicarse y localizar objetos a su alrededor. Dependiendo de la conductividad del agua, la amplitud del campo eléctrico generado aumenta con una disminución en la conductividad eléctrica del agua. En los arroyos de terra firme amazónicos, la conductividad eléctrica del agua es extremadamente baja y fluctua constantemente dependiendo de las lluvias locales y regionales. Teniendo esto en cuenta, esperamos que el espacio entre peces eléctricos débiles con libertad de movimiento disminuya, en promedio, de acuerdo al incremento en la conductividad del agua. Para evaluar esta hipótesis, registramos bajo condiciones naturales por varios dias en meses alternos y durante dos años las posiciones en reposo del pez Gymnorhamphichthys rondoni en un arroyo de terra firme. Con los valores de registro diario de la distancia al vecino mas cercano en peces individuales dentro de una grilla, encontramos un patrón de distribución temporal uniforme (que no fue afectado por la conductividad del agua) e indicativo de una fidelidad por los sitios de reposo. Entonces, nosotros resaltamos aquí el posible papel que otros factores pueden estar jugando para entender la fidelidad por sus sitios de reposo.(AU)

Identification of dysphonia related to parkinson’s disease using parametric and non parametric models / 国际药学研究杂志

Classification of Parametric and Non Parametric models is done by using the collected dataset of Parkinson's disease. Testing is done on Parkinson’s data set with two respective models to determine which model provides the higher classification accuracy. Logistic Regression technique is used to classify the Parkinson's data using non parametric modeling and K-Nearest Neighbors and Random Forest Algorithm is used to classify the training and test data of Parkinson’s disease for parametric model. Based on the data classification,, we obtain the result using parametric and non parametric models. Finally, Comparison is made on of both Parametric and Non Parametric model to evaluate the performance of the Parkinson's dataset.

Genetic polymorphisms and genetic relationship of 24 autosomal STR loci in Gelao and Miao population of Guizhou / 解放军医学杂志

Objective: To investigate the genetic polymorphisms of 24 autosomal short tandem repeats (STR) loci in Gelao and Miao populations dwelled in Guizhou province, and explore the population genetic relationships and evaluate their application value on forensic medicine. Methods: The DNA samples of 732 unrelated individuals (399 Guizhou Gelao population and 333 Guizhou Miao population) were amplified using SureID® PanGlobal kit, and the PCR products were analyzed by electrophoresis through 3500XL genetic analyzer. The fragment sizes of alleles were subsequently analyzed by GeneMapper ID-X v1.5. Allele frequencies and forensic genetic parameters of 24 STR loci were statistically analyzed and compared with the available data of other populations from different races and regions. Results: For Guizhou Gelao and Miao populations, the individual discrimination power (DP) ranged from 0.7833 to 0.9909 and 0.8010 to 0.9909, respectively; the polymorphic information content (PIC) ranged from 0.5608 to 0.9385 and 0.5677 to 0.9414, respectively; the total discrimination power (TDP) were 1-7.6036 × 10-30 and 1-6.8630 × 10-30, respectively, and the cumulative probability of exclusion (CPE) were 1-1.9608 × 10-11 and 1-1.9738 × 10-14, respectively. Analysis with the matrix of Nei's DA genetic distance indicated that the genetic distance was the smallest (0.0205) between Guizhou Gelao and Hubei Han populations, while was the largest (0.0449) between Guizhou Gelao and Yunnan Miao populations; the genetic distance was minimum (0.0033) between Guizhou Miao and Hunan Han populations, while was maximal (0.0363) between Guizhou Miao and Yunnan Miao. Conclusions: The 24 STR loci are abundant in genetic polymorphism in Guizhou Gelao and Miao populations. It is of great significance to study the genetic diversity of different ethnic groups in order to understand their origin, migration and interrelationship.

Population characteristics and threatened of wild Angelica sinensis in Gansu province / 中国中药杂志

The study aims to investigate spatial distribution pattern and age structure of wild Angelica sinensis in Gansu province.Ten plots each with an area of 100 m2 were set and the spatial coordinates of all wild A. sinensis individuals were measured within each plot. Based on plant individual mapping data,we explored the spatial distribution pattern and its differences between different life history stages of wild A. sinensis in Gansu province by using nearest neighbor distance statistics. Correlation analysis were carried out to explore the relationship between spatial aggregation degree and topographic factors. We also distinguished individuals to three life history stages( i.e. seedlings,adults and boltings) and then test the differences among/between them using nonparametric test.(1)We found that the dominant spatial distribution pattern of wild A. sinensis population in Gansu was aggregated distribution. There was no significant correlation between spatial aggregation degree of wild A. sinensis and altitude,slope and aspect. There was no significant difference between the average distance from seedlings to their nearest bolting individuals; the average distance from adult individuals to their nearest seedlings was significantly larger than the average distance from adult individuals to their nearest adult individuals; and the average distance from bolting individuals to their nearest adult individuals was significantly smaller than the average distance from bolting individuals to their nearest bolting individuals.(2)The age structure was showed as a declining population,characterized by less seedlings and bolting individuals,while more adult individuals within population. The population characteristics of wild A. sinensis,characterized by aggregated distribution pattern and senescent type of age structure,are disadvantage to its population development. The factors,such as habitat specialization,human activities and intraspecific competition,which shapes the current population characteristics,may increase the threatened status of wild A. sinensis. We suggest to strengthen the protection of wild A. sinensis.

Automatic clustering method of flow cytometry data based on -distributed stochastic neighbor embedding / 生物医学工程学杂志

The traditional method of multi-parameter flow data clustering in flow cytometry is to mainly use professional software to manually set the door and circle out the target cells for analysis. The analysis process is complex and professional. Based on this, a clustering algorithm, which is based on -distributed stochastic neighbor embedding ( -SNE) algorithm for multi-parameter stream data, is proposed in the paper. In this algorithm, the Euclidean distance of sample data in high dimensional space is transformed into conditional probability to represent similarity, and the data is reduced to low dimensional space. In this paper, the stained human peripheral blood cells were treated by flow cytometry, and the processed data were derived as experimental sample data. The -SNE algorithm is compared with the kernel principal component analysis (KPCA) dimensionality reduction algorithm, and the main component data obtained by the dimensionality reduction are classified using -means algorithm. The results show that the -SNE algorithm has a good clustering effect on the cell population with asymmetric and trailing distribution, and the clustering accuracy can reach 92.55%, which may be helpful for automatic analysis of multi-color multi-parameter flow data.

Comparison of decoding performance between spike and local field potential signals during goal-directed decision-making task of pigeons / 生物医学工程学杂志

Both spike and local field potential (LFP) signals are two of the most important candidate signals for neural decoding. At present there are numerous studies on their decoding performance in mammals, but the decoding performance in birds is still not clear. We analyzed the decoding performance of both signals recorded from nidopallium caudolaterale area in six pigeons during the goal-directed decision-making task using the decoding algorithm combining leave-one-out and -nearest neighbor (LOO- NN). And the influence of the parameters, include the number of channels, the position and size of decoding window, and the nearest neighbor value, on the decoding performance was also studied. The results in this study have shown that the two signals can effectively decode the movement intention of pigeons during the this task, but in contrast, the decoding performance of LFP signal is higher than that of spike signal and it is less affected by the number of channels. The best decoding window is in the second half of the goal-directed decision-making process, and the optimal decoding window size of LFP signal (0.3 s) is shorter than that of spike signal (1 s). For the LOO- NN algorithm, the accuracy is inversely proportional to the value. The smaller the value is, the larger the accuracy of decoding is. The results in this study will help to parse the neural information processing mechanism of brain and also have reference value for brain-computer interface.

Prediction of protein subcellular locations by ensemble of improved K-nearest neighbor / 生物工程学报

Adaboost algorithm with improved K-nearest neighbor classifiers is proposed to predict protein subcellular locations. Improved K-nearest neighbor classifier uses three sequence feature vectors including amino acid composition, dipeptide and pseudo amino acid composition of protein sequence. K-nearest neighbor uses Blast in classification stage. The overall success rates by the jackknife test on two data sets of CH317 and Gram1253 are 92.4% and 93.1%. Adaboost algorithm with the novel K-nearest neighbor improved by Blast is an effective method for predicting subcellular locations of proteins.

Molecular Epidemiology of Mycobacterium leprae as Determined by Structure-Neighbor Clustering in Korea found cases / 나학회지

BACKGROUND: It has proven challenging to investigate the molecular epidemiology of Mycobacterium leprae, the causative agent of leprosy, due to difficulties with culturing of the organism and a lack of genetic heterogeneity between strains. Recently, A panel of variable-number tandem-repeat (VNTR) markers and an alternative method, structure-neighbor clustering, which assigns isolates with the most similar genotypes to the same groups and, subsequently, subgroups, without inferring how the strains descended from a common ancestor have been developed. METHODS: A total of 29 samples from Korea found cases were studied by 14 VTRN typing and an alternative method, structure-neighbor clustering with 13 and 14 VNTRs by Structure Program(k=10). RESULTS: Only 286 cases of 522 total cases(including database of Bellingham Research Institute) showed p>0.8(in 13 and 14 VNTRs). Almost Korea found cases(18 cases) were included in group 3(13 VNTRs), in group 9(14 VNTRs)(by Structure Program, k=10). CONCLUSIONS: The structure-neighbor clustering by Structure Program with panels of VNTR is a useful approach for investigating the molecular epidemiology of Mycobacterium leprae.

Proposing the novelty classifier for face recognition

INTRODUCTION: Face recognition, one of the most explored themes in biometry, is used in a wide range of applications: access control, forensic detection, surveillance and monitoring systems, and robotic and human machine interactions. In this paper, a new classifier is proposed for face recognition: the novelty classifier. METHODS: The performance of a novelty classifier is compared with the performance of the nearest neighbor classifier. The ORL face image database was used. Three methods were employed for characteristic extraction: principal component analysis, bi-dimensional principal component analysis with dimension reduction in one dimension and bi-dimensional principal component analysis with dimension reduction in two directions. RESULTS: In identification mode, the best recognition rate with the leave-one-out strategy is equal to 100%. In the verification mode, the best recognition rate was also 100%. For the half-half strategy, the best recognition rate in the identification mode is equal to 98.5%, and in the verification mode, 88%. CONCLUSION: For face recognition, the novelty classifier performs comparable to the best results already published in the literature, which further confirms the novelty classifier as an important pattern recognition method in biometry.

Método de mineração de dados para identificação de câncer de mama baseado na seleção de variáveis / A data mining method for breast cancer identification based on a selection of variables

Na maioria dos países, o câncer de mama entre as mulheres é predominante. Se diagnosticado precocemente, apresenta alta probabilidade de cura. Diversas abordagens baseadas em Estatística foram desenvolvidas para auxiliar na sua detecção precoce. Este artigo apresenta um método para a seleção de variáveis para classificação dos casos em duas classes de resultado, benigno ou maligno, baseado na análise citopatológica de amostras de célula da mama de pacientes. As variáveis são ordenadas de acordo com um novo índice de importância de variáveis que combina os pesos de importância da Análise de Componentes Principais e a variância explicada a partir de cada componente retido. Observações da amostra de treino são categorizadas em duas classes através das ferramentas k-vizinhos mais próximos e Análise Discriminante, seguida pela eliminação da variável com o menor índice de importância. Usa-se o subconjunto com a máxima acurácia para classificar as observações na amostra de teste. Aplicando ao Wisconsin Breast Cancer Database, o método proposto apresentou uma média de 97,77% de acurácia de classificação, retendo uma média de 5,8 variáveis.

In the majority of countries, breast cancer among women is highly prevalent. If diagnosed in the early stages, there is a high probability of a cure. Several statistical-based approaches have been developed to assist in early breast cancer detection. This paper presents a method for selection of variables for the classification of cases into two classes, benign or malignant, based on cytopathological analysis of breast cell samples of patients. The variables are ranked according to a new index of importance of variables that combines the weighting importance of Principal Component Analysis and the explained variance based on each retained component. Observations from the test sample are categorized into two classes using the k-Nearest Neighbor algorithm and Discriminant Analysis, followed by elimination of the variable with the index of lowest importance. The subset with the highest accuracy is used to classify observations in the test sample. When applied to the Wisconsin Breast Cancer Database, the proposed method led to average of 97.77% in classification accuracy while retaining an average of 5.8 variables.

Identification of Lacrymaria velutina (Pers. Ex Fr.) Konrad & Maubl. from Micheon-myeon, Jinju-city, Korea

We identified Lacrymaria velutina of the Coprinaceae in Korea. The unusually large and sturdy fruiting body, fibrillose to fibrillose-scaly cap and stalk without a volva with an obscure superior hairy ring zone or hairy annulus, and blackish brown, warted spores distinguished this species from closely related Psathyrella species. An illustrated account of the microscopic traits is presented. Fruiting bodies with obtusely hemispherical caps, 2.5~6 cm, becoming convex with age; surface dry, densely fibrillose-scaly with split margin; stipe, 4.5~6 cm, equal, hollow, fibrillose, dry, whitish above the superior ring zone, light brown below; crowded gills, adnexed, dark black at maturity. Pileipellis typically cellular with the gill edge appearing white and beaded. Blackish brown basidiospores that discolor in concentrated sulfuric acid. Spores elliptical, warted, 9~11 x 6~8 microm, with prominent snout-like germpores. Cheilocystidia abundant, 57~68 x 19~25 microm, and narrowly elongated clavate, often clustered in threes or fours. Pleurocystidia rarely present, 45~47.5 x 12~13 microm, and clavate to utriform. This trait distinguishes our sample as L. velutina from other Psathyrella spp. of the Coprinaceae, which have smooth spores. This taxon was clarified by the observation that Psathyrella spores fade in concentrated sulfuric acid. A molecular phylogenetic study revealed that our specimen was Lacrymria velutipes, which is closely related to Lacrymaria lacrymabunda. Moreover, those two species are clearly distinguishable from other Psathyrella species, which agreed with the morphologically distinctive traits described above. We believe that this is the first report of this taxon, which has not been described in Korea.

Solving shortest circuit problem of military health support based on partheno-genetic algorithm / 第二军医大学学报

Objective: To propose an effective algorithm for solving the shortest circuit problem of military health support. Methods: Partheno-genetic algorithm (PGA), which only used mutation operation and selection operation, was adopted in the present study. The algorithm was based on K-random-nearer-neighbor algorithm combined with two-random-point exchange, two-neighbor-point exchange, circular-based part inversion and random insertion mutation operations. Furthermore, greedy strategy was applied in selection to improve the hill-climbing capability of PGA. Results The simulation results of CTSP31 and standard dataset from TSP library indicated that the PGA was more effective than existing algorithms from the literature. Conclusion: PGA can serve as a basis for further development of a computer-assisted program, and it provides optimized decision-making scheme for improving the quality and speed of military medical service disposition.