Clone Selection Artificial Intelligence Algorithm-Based Positron Emission Tomography-Computed Tomography Image Information Data Analysis for the Qualitative Diagnosis of Serous Cavity Effusion in Patients with Malignant Tumors

This study aimed to investigate the application of positron emission tomography- (PET-) computed tomography (CT) image information data combined with serous cavity effusion based on clone selection artificial intelligence algorithm in the diagnosis of patients with malignant tumors. A total of 97 patients with PET-CT scanning and empirically confirmed as serous cavity effusion were retrospectively analyzed in this study. The clone selection artificial intelligence algorithm was applied to register the PET-CT images, and the patients were rolled into a benign effusion group and a malignant effusion group according to the benign and malignant conditions of the serous cavity effusion. Besides, the causes of patients from the two groups were analyzed, and there was a comparison of their physiological conditions. Subsequently, CT values of different KeV, lipid/water, water/iodine, and water/calcium concentrations were measured, and the differences of the above quantitative parameters between benign and malignant serous cavity effusion were compared, as well as the registration results of the clone algorithm. The results showed that the registration time and misalignment times of clonal selection algorithm (13.88, 0) were lower than those of genetic algorithm (18.72, 8). There were marked differences in CT values of 40–60 keV and 130–140 keV between the two groups. The concentrations of lipid/water, water/iodine, and water/calcium in basal substances of the malignant effusion group were obviously higher than the concentrations of the benign effusion group ( P < 0.05 ). Benign and malignant effusions presented different manifestations in PET-CT, which was conducive to the further diagnosis of malignant tumors. Based on clone selection artificial intelligence algorithm, PET-CT could provide a new multiparameter method for the identification of benign and malignant serous cavity effusions and benign and malignant tumors.

Ampelographic features of biotypes of ‘Saperavi’ grape variety

Целью работы является установление отличий выделенных биотипов сорта Саперави по основным ампелографическим признакам, а также обсуждение использования термина «биотип» в виноградарстве и возможности практического применения биотипов винограда. В результате исследования насаждений сорта Саперави выделено 4 биотипа, включая контрольный биотип. Биотип I: гроздь ветвистая, коническая, рыхлая, средней величины, длина грозди 13-15 см, масса грозди 180-220 г, ягода мелкая и округлая. Биотип II: гроздь ветвистая, коническая, рыхлая, длина грозди 16-18 см, масса грозди 270-320 г, ягода средней величины и продолговатая. Биотип III: гроздь ветвистая, ширококоническая, большая, длина грозди 19-21 см, масса грозди 500-600 г, ягода крупная и овальная. Биотип IV (контроль): гроздь ветвистая, коническая, рыхлая, длина грозди 17-19 см, масса грозди 330-450 г, ягода средней величины и овальной формы. Среди изученных биотипов наиболее перспективным является биотип III по признакам величины, плотности и массы грозди, размера ягоды и выхода сусла. «Биотип» - это термин, употребляемый для альтернативного обозначения клона, группы клонов или сорта винограда, используемого в определенном регионе. Концепция биотипа находит свое применение в экспериментальных исследованиях и в клоновом отборе при необходимости подчеркнуть уровень изменчивости более высокой, чем у сорта или клона. Полученные результаты могут использоваться при возделывании сорта Саперави в виноградарских хозяйствах, а также в виноделии. Determination of the differences between the selected biotypes of ‘Saperavi’ variety according to the main ampelographic traits, as well as discussing the use of the term “biotype” in viticulture and the possibility of practical application of grape biotypes are the aims of the work. As a result of the study of ‘Saperavi’ variety vineyards, 4 biotypes were identified, including the control one. Biotype I: the bunch is branched, conical, loose, of a medium size, the bunch length is 13-15 cm, the bunch weight is 180-220 g, the berry is small and round. Biotype II: the bunch is branched, conical and loose, the bunch length is 16-18 cm, the bunch weight is 270-320 g; the berry is medium-sized and oblong. Biotype III: the bunch is branched, broad-conical and large, the bunch length is 19-21 cm, the bunch weight is 500-600 g; the berry is large and oval. Biotype IV (control): the bunch is branched, conical, loose, the bunch length is 17-19 cm, the bunch weight is 330-450 g; the berry is of medium size and oval. Biotype III was the most promising one among the studied biotypes according to the size, density and bunch weight, the berry size and the yield of must. “Biotype” is a term used to alternatively denote a clone, group of clones or grape variety used in a certain region. The concept of a biotype finds its application in experimental studies and in clone selection, if necessary to emphasize the level of variability higher than that of a variety or clone. The results obtained can be used in the cultivation of ‘Saperavi’ variety in vineyards, as well as in winemaking.

An integrated model for maintenance policies and production scheduling based on immune–culture algorithm

The development of integrated modelling for maintenance policies of multi-component repairable system and production scheduling is challenging for two reasons. First, capturing dependency of this multi-component repairable system is difficult because different failure types associated with different components are under competing risks and their complicated relationships may lead to overall system dependency. Second, the integrated model is difficult to optimize because it is an NP-hard problem that exact optimization methods are intractable. For coping with these two difficulties, we propose a parametric statistical model using copula function to capture the overall system dependency. Under partially perfect maintenance policy at component-level, the likelihood functions for observed failures are derived and maximum likelihood method is used to estimate unknown parameters. Then relying on this parametric statistical model, the system hazard function is derived to depict the reliability-based imperfect preventive maintenance policy at system-level. Finally, to obtain the optimal solution(s) of the integrated model, we design an adaptive immune clone selection–culture algorithm, which is inspired from immune clone selection algorithm and culture algorithm. Results of the case study validate that our proposed maintenance policies and methodology have great advantages over the component-level or system-level maintenance policy and immune clone selection algorithm.

Генетическая интерпретация клоновой селекции винограда

Проведен обзор научно-исследовательских работ по методологии клоновой селекции винограда. Анализируются различные определения термина «клон винограда». Рассмотрены возможные причины возникновения клонов: точковые мутации, поликлональное происхождение, модификации. Поддерживающий отбор, используемый для сохранения чистоты, типичности сорта и его хозяйственно ценных свойств, способствует очищению сорта от отрицательных клонов и созданию выровненных насаждений. Для улучшения существующих сортов винограда используется направленный отбор и размножение нетипичных, ценных в биолого-хозяйственном отношении форм растений. Также одной из задач отбора должна быть задача восстановления сортов. Идентификация отличий нового клона нуждается в индивидуальном подходе в зависимости от свойства: мутации и полиплоидия, качественные и количественные признаки . У винограда химерность тканей и клеток является распространенным явлением, многие сорта виноградной лозы являются периклинальными химерами. Приведены варианты отличий маточного куста от исходного сорта, необходимых и достаточных для выделения клона в первом вегетативном поколении. С генетической точки зрения, к основным признакам для клонового отбора винограда обоснованно следует отнести признаки, наследование которых установлено и существенно. Поскольку при работе с клонами приходится принимать во внимание большое количество признаков, представляется эффективным использование многомерных моделей изменчивости. Отмечена перспективность развития методов молекулярной генетики, позволяющих идентифицировать плоидность и генетические различия между растениями, но изучение клонов такими методами пока не получило широкого распространения. Рассматриваются возможности использования в клоновой селекции винограда биотехнологических методов. Недостатком клонового отбора является однородность виноградников и продукции в дополнение к генетической эрозии. Поэтому изменчивость в пределах отдельных сортов должна поддерживаться путем отбора различных клонов, и в виноградарстве, наряду с клоновой селекцией, обязательно должна иметь место генеративная селекция. Таким образом, клон в виноградарстве - это идентичное по генотипу и фенотипу вегетативное потомство растения, выделенного в насаждениях какого-либо сорта винограда и отличающегося от типичных кустов исходного сорта по характеристикам, сохраняющимся при вегетативном размножении. Клоновая селекция винограда перспективна, чему способствуют генетические особенности этой культуры: большая частота спонтанных мутантов, наличие сортов с достаточно широкой генетической изменчивостью, вегетативное размножение, позволяющее сохранять каждое отклонение на неограниченное время.A review of research work on the methodology of clone selection of grapes was carried out. Various definitions of the term ‘grape clone’ are analyzed. Possible causes for the emergence of clones are discussed: point mutations, polyclonal origin, modifications. Recurrent selection used to preserve the purity and typicality of a variety and its economically valuable traits promotes cleansing the variety from negative clones and creating uniform plantings. To improve existing grape varieties, directional selection and propagation of atypical, biologically and economically valuable plant forms are used. Also, restoration of varieties should be one of selection tasks. The identification of different features of a new clone needs an individual approach depending on the properties: mutations and polyploidy, qualitative and quantitative traits. Chimerism of tissues and cells is common in grapes; many varieties of grapevines are periclinal chimeras. Variants of differences between the clone mother vine and the initial variety which are necessary and sufficient for clone selection in the first vegetative generation are presented. From the genetic point of view, main traits for clone selection of grapes should reasonably include traits whose inheritance is essential and has been established. Since a large number of traits have to be taken into account when working with clones, it seems efficient to use multidimensional models of variability. It is noted that development of molecular genetic methods has good prospects since they make it possible to identify ploidy and genetic differences between plants, but the study of clones by such methods has not yet become widespread. The possibilities of using biotechnological methods in clone selection of grapes are discussed. In addition to genetic erosion, the uniformity of vineyards and products enters as a weak point of clone selection. Therefore, the variability within individual varieties should be maintained by selection of various clones, and, along with clone selection, generative breeding must necessarily take place in viticulture. Thus, a clone in viticulture is a vegetative offspring of a plant selected in the plantings of any grape variety and differing from typical vines of the initial variety in terms of characteristics preserved during vegetative propagation. Plants of a clone are identical in genotype and phenotype. Clone selection of grapes is promising, which is facilitated by genetic characteristics of this crop: a high frequency of spontaneous mutants, existence of varieties with a fairly wide genetic variability, vegetative propagation which allows to preserve each deviation for an unlimited time.