MONASTERIES OF THE TVER HALF OF THE BEZHETSKAYA PYATINA AT THE END OF THE 15TH - 16TH CENTURIES: LOCALIZATION, LAND OWNERSHIP

Статья посвящена монастырям и монастырскому землевладению в Тверской половине Бежецкой пятины в конце XV - XVI в. Основными источниками являются писцовые книги, привлекается актовый материал, описания XIX - начала ХХ в. В общей сложности выявлена информация о десяти монастырях, девять из которых возникло в XVI в. Наиболее ранним, предположительно, является Иоанно-Богословский монастырь в волости Удомля. Размеры монастырей Тверской половины Бежецкой пятины были невелики, землевладения располагались в непосредственной близости от самих монастырей. Более крупными являлись владения новгородских обителей - Воскресенского на Мячине, Кириллова, Юрьева, Троицкого Млёвского. В целом монастырское землевладение в Тверской половине Бежецкой пятины после присоединения Новгорода к Московскому государству уступало размерам владений Хутынского и Аркажского монастырей на этой территории в период новгородской самостоятельности. Небольшие размеры монастырского землевладения и малое количество монастырей на изучаемой территории объясняется ее периферийностью по отношению к Новгороду. Возникшие в XVI в. монастыри находились на сухопутных и водных путях сообщения. Упадок монастырского хозяйства наблюдается с последней четверти XVI в. Формирование систем приписных монастырей в XVII в., вероятно, являлось попыткой выхода из кризиса путем консолидации монастырских ресурсов. The article is devoted to the monasteries and monastery land ownership in the Tver half of the Bezhetskaya pyatina at the end of the 15th - 16th centuries. The main sources are the scribe books, acts, descriptions of the 19th - early 20th centuries. In total, information was revealed about ten monasteries, nine of which arose in the 16th centuries. The earliest, presumably, is the John Theological Monastery in the Udomlya volost. The size of the monasteries of the Tver half of the Bezhetskaya pyatina was very small, the land ownership was usually located in the immediate vicinity of the monasteries themselves. The larger ones were the lands of the Novgorod monasteries - the monastery of the Resurrection on Myachino, Kirillov, Yuryev, as well as the monastery of the St. Trinity Mlevsky.In general, the monastery land ownership in the Tver half of the Bezhetskaya pyatina after the accession of the Novgorod to the Moscow state was very small and inferior to the size of the lands of the Khutynsky and Arkazhsky monasteries in this territory during the period of Novgorod independence. Small scales of monastery land ownership and a small number of monasteries in the area under the research are explained by its periphery in relation to Novgorod. At the same time, the monasteries that arose in the 16th century were on land roads and waterways. The decline of the monastery economy has been observed since the last quarter of the 16th century. The formation of systems of ascribed monasteries in the 17th century was probably an attempt to overcome the crisis by the consolidation of the monastery resources.

mRBioM: An Algorithm for the Identification of Potential mRNA Biomarkers From Complete Transcriptomic Profiles of Gastric Adenocarcinoma

PurposeIn this work, an algorithm named mRBioM was developed for the identification of potential mRNA biomarkers (PmBs) from complete transcriptomic RNA profiles of gastric adenocarcinoma (GA).MethodsmRBioM initially extracts differentially expressed (DE) RNAs (mRNAs, miRNAs, and lncRNAs). Next, mRBioM calculates the total information amount of each DE mRNA based on the coexpression network, including three types of RNAs and the protein-protein interaction network encoded by DE mRNAs. Finally, PmBs were identified according to the variation trend of total information amount of all DE mRNAs. Four PmB-based classifiers without learning and with learning were designed to discriminate the sample types to confirm the reliability of PmBs identified by mRBioM. PmB-based survival analysis was performed. Finally, three other cancer datasets were used to confirm the generalization ability of mRBioM.ResultsmRBioM identified 55 PmBs (41 upregulated and 14 downregulated) related to GA. The list included thirteen PmBs that have been verified as biomarkers or potential therapeutic targets of gastric cancer, and some PmBs were newly identified. Most PmBs were primarily enriched in the pathways closely related to the occurrence and development of gastric cancer. Cancer-related factors without learning achieved sensitivity, specificity, and accuracy of 0.90, 1, and 0.90, respectively, in the classification of the GA and control samples. Average accuracy, sensitivity, and specificity of the three classifiers with machine learning ranged within 0.94–0.98, 0.94–0.97, and 0.97–1, respectively. The prognostic risk score model constructed by 4 PmBs was able to correctly and significantly (∗∗∗p < 0.001) classify 269 GA patients into the high-risk (n = 134) and low-risk (n = 135) groups. GA equivalent classification performance was achieved using the complete transcriptomic RNA profiles of colon adenocarcinoma, lung adenocarcinoma, and hepatocellular carcinoma using PmBs identified by mRBioM.ConclusionsGA-related PmBs have high specificity and sensitivity and strong prognostic risk prediction. MRBioM has also good generalization. These PmBs may have good application prospects for early diagnosis of GA and may help to elucidate the mechanism governing the occurrence and development of GA. Additionally, mRBioM is expected to be applied for the identification of other cancer-related biomarkers.

Bt corn growing information system in Cagayan Province, Philippines: An analysis for enhanced extension delivery service

The adoption of Bacillus thuringiensis (Bt) corn gene has increased production and agricultural information exchange plays a vital role towards sustained production growth. The study examined the information system by assessing the usefulness of information, frequency of consultations and strength of information exchange in Bt corn production in Cagayan Province, Philippines. Using descriptive correlation design, it was revealed that both technical and economic information from all sources were rated useful. Technical information on seed variety, land preparation, weather forecast, soil management and fertilizer application are frequently utilized while on the economic information only current market prices was frequently used. Frequency of Consultation with personal information sources gained the highest mean value of 5.02 signifying a two to three times exchange of information. Public information sources obtained an average mean of 2.80 which means four or five times contact in a year. This reveals the gap between the corn growers and public information sources. For the mass media sources, both radio (4.56) and television (4.72) are frequently used at two to three times a month. Personal information sources showed strong (224.25 IS) exchange of information between and among the Bt corn growers which comprise their communication network. Total information scores from public and mass media information sources revealed weak exchange of information. The total information score is significantly correlated with membership to organization, years of membership, nature of membership, land ownership and position in the farm. Total information score from friends, radio and newspaper showed significant relationship with income. Thus, information exchange with friends, listening to radio and reading newspaper had a significant influence on the increase of corn growers’ income.

ANALISIS PERBANDINGAN KORELASI SPEARMAN DAN MAXIMAL INFORMATION COEFFICIENT DALAM SELEKSI FITUR WEBSITE PHISHING MENGGUNAKAN ALGORITMA MACHINE LEARNING

<p><em>aan yang menipu maupun secara teknis untuk mencuri data identitas pribadi konsumen dan kredensial akun keuangan. Phishing dirancang untuk mengarahkan konsumen ke website phishing yang menipu penerima untuk membocorkan data keuangan seperti nama pengguna dan kata sandi. Dalam dataset phishing, terdapat fitur-fitur yang bisa mengkategorikan apakah sebuah website adalah website phishing atau bukan. Tujuan dari penelitian ini adalah untuk membandingkan hasil seleksi fitur-fitur yang ada dengan menggunakan dua metode yaitu metode gabungan Maximal Information coefficient dan Total Information Coefficient dengan metode korelasi Spearman. Hasil seleksi diuji dengan lima algoritma machine learning yaitu, Logistic Regression, Naïve Bayes, J48, AdaBoost MI</em> dan <em>Random Forest. Hasil dari penelitian ini adalah metode gabungan Maximal Information coefficent dan Total Information Coefficient memiliki nilai akurasi 97.25 % dengan menggunakan Random Forest mengungguli metode korelasi Spearman dengan nilai akurasi 95,33%.</em></p>

Scaling of sensory information in large neural populations shows signatures of information-limiting correlations

How is information distributed across large neuronal populations within a given brain area? Information may be distributed roughly evenly across neuronal populations, so that total information scales linearly with the number of recorded neurons. Alternatively, the neural code might be highly redundant, meaning that total information saturates. Here we investigate how sensory information about the direction of a moving visual stimulus is distributed across hundreds of simultaneously recorded neurons in mouse primary visual cortex. We show that information scales sublinearly due to correlated noise in these populations. We compartmentalized noise correlations into information-limiting and nonlimiting components, then extrapolate to predict how information grows with even larger neural populations. We predict that tens of thousands of neurons encode 95% of the information about visual stimulus direction, much less than the number of neurons in primary visual cortex. These findings suggest that the brain uses a widely distributed, but nonetheless redundant code that supports recovering most sensory information from smaller subpopulations.

Tornadoes in the Russian Regions

New data are presented on tornadoes over land in Russia for the period of 1900–2018 based on various sources. In total, information on 1763 tornadoes was collected, including 993 tornadoes from eyewitness reports on tornado passage and/or associated impacts and 770 tornadoes from satellite data on tornado-induced windthrows. Both single tornadoes and tornado outbreaks, the cases of formation of several tornadoes within one meso- or synoptic-scale system, were reported. On average for 2009– 2018, more than 100 tornadoes are observed in Russia per year, including 15 significant tornadoes (with a wind speed >50 m/s) and one intense tornado (with a wind speed >70 m/s). In some years, these rates can be significantly higher and reach 342, 52, and three tornadoes per year, respectively. Tornadoes are observed on about 41 days per year, up to 68 days per annum in some years. The frequency of occurrence of tornadoes of different categories and the probability of their passage over a point on the ground were estimated. These estimates can be further used to assess a risk of tornado-hazardous situations. The general underestimation of the number of tornadic events in routine meteorological observations and existent statistics is discussed.