Analysis of urban air pollution based on network observation

A joint analysis of cases of high monthly mean concentrations of benzo(a)pyrene measured at stationary stations of Roshydromet in the atmospheric air of the cities of Novosibirsk and Iskitim of the Novosibirsk region is carried out. The influence of meteorological conditions on pollution levels is investigated. Particular attention is paid to the analysis of observational data carried out in the winter months of 2018, for which high monthly mean concentrations of benzo(a)pyrene were recorded in both cities, reaching 15–20 maximum permissible concentrations. Correlation relationships were obtained between measurements at stations in the cities of Novosibirsk and Iskitim, which indicates the determining influence of meteorological conditions on pollution levels.

Single-Macromolecular Level Imaging of a Hydrogel Structure

Hydrogels are promising materials for several applications, including cell scaffolds and artificial load-bearing substitutes (cartilages, ligaments, tendons, etc.). Direct observation of the nanoscale polymer network of hydrogels is essential in understanding its properties. However, imaging of individual network strands at the molecular level is not achieved yet due to the lack of suitable methods. Herein, for the first time, we developed a novel mineral-staining method and network fixation method for transmission electron microscopy observation to visualize the hydrogel network in its unperturbed conformation with nanometer resolution. Surface network observation indicates that the length of surface dangling chains, which play a major role in friction and wetting, can be estimated from the gel mesh size. Moreover, bulk observations reveals a hierarchical formation mechanism of gel heterogeneity. These observations have the great potential to advance gel science by providing comprehensive perspective that link bulk gel properties with nanoscale.

Feature Extraction for Dimensionality Reduction in Cellular Networks Performance Analysis

Next-generation mobile communications networks will have to cope with an extraordinary amount and variety of network performance indicators, causing an increase in the storage needs of the network databases and the degradation of the management functions due to the high-dimensionality of every network observation. In this paper, different techniques for feature extraction are described and proposed as a means for reducing this high dimensionality, to be integrated as an intermediate stage between the monitoring of the network performance indicators and their usage in mobile networks’ management functions. Results using a dataset gathered from a live cellular network show the benefits of this approach, in terms both of storage savings and subsequent management function improvements.

Examining the variability in network populations and its role in generative models

A principled approach to understand networks is to formulate generative models and infer their parameters from given network data. Due to the scarcity of data in the form of multiple networks that have evolved from the same process, generative models are typically formulated to learn parameters from a single network observation, hence ignoring the natural variability of the “true” process. In this paper, we highlight the importance of variability in evaluating generative models and present two ways of quantifying the variability for a finite set of networks. The first evaluation scheme compares the statistical properties of networks in a dissimilarity space, while the other relies on data-driven entropy measures to compute variability in network populations. Using these measures, we evaluate the ability of four generative models to synthesize networks that capture the variability of the “true” process. Our empirical analysis suggests that generative models fitted for a single network observation fail to capture the variability in the network population. Our work highlights the need for rethinking the way we evaluate the goodness-of-fit of new and existing network models and devising models that are capable of matching the variability of network populations when available.

Alumni Pesantren Gontor dan Jaringan Islam Global

Abstract.,The paper aims to discuss the shading player called “network” of the globalized Islam behind formal Islamic educational institutions. Globalized Islam as Olivier Roy defines is an idea or movement that detach Islam from its geography or cultural territories. Examining alumnae of pesantren Gontor and their position over the contemporary discourse of Islam in Indonesia, the author found that networking with globalized Islam groups has strong influence on their world views. The mutual relationship between Gontor and globalized Islam networks has some impacts on its alumnae. Its exposure to more global Muslim world has prepared its alumnae embrace the globalized Islam identity. More decisive factors are their networks during higher education period out of pesantren. The author uses life experiences as a student and alumni of Gontor as his main research data as well as social network observation. This paper moreover strengthened the existing previous researches that the globalization of Wahabism starting in the 1980s has been very effective in Indonesia. By penetrating the Islamic education institution networks, it has opened doors for more influence on the general mass of Indonesian Muslims key words: globalized Islam, pesantren, Gontor Abstrak., Artikel ini mendiskusikan fenomena “Global Islam” salah satu sumber ideologi radikal di Indonesia. Global Islam (Islamisme) sebagaimana didefinisikan oleh Oliver Roy sebagai sebuah ide, praktek atau gerakan yang berusaha memisahkan Islam dari teritori dan kultur di mana ia berada. Mengambil kasus alumni Pondok Modern Gontor dan posisi mereka terhadap wacana Islam kekinian di Indonesia, penulis menemukan bahwa bahkan alumni pesantren yang dikenal luas moderat dalam pandangan-pandangan keagamaannya, tidak dijamin bebas dari pengaruh jaringan “global Islam”. Hubungan antara Gontor dan jejaring global Islam mempunyai dampak terhadap para alumninya. Praktek pengajaran Gontor yang berorientasi internasional menumbuhkan “chemistry” yang kuat di kalangan alumni Gontor dengan jaringan global Islam. Jaringan kerja mereka yang dibangun, utamanya, selama periode pendidkan tinggi, atau tingkat universitas setelah lulus dari pesantren adalah salah satu faktor penentu utama orientasi wacana dan sikap keislaman mereka, selain latar belakang keluarga dll. Melalui metode life history para alumni dan observasi social network mereka, paper ini telah memperkuat studi-studi sebelumnya bahwa globalisasi ideologi Wahabi (global Islam) di Indonesia cukup efektif bekerja. Melalaui programnya di institusi-institusi pendidikan yang berpengaruh, dan hadirnya jaringan mereka telah mempersiapkan “infrastruktur” berkembangnya ideologi Wahabi di masyarakat luas di Indonesia. Kata Kunci: Islam Global, Pesantren, Gontor

The influence of silviculture investment in fixed assets on forest water conservation in China

Forests play an important role in water conservation. It is important to study the relationship between forest water conservation (FWC) and forestry investment. Based on official statistics and ecological network observation data in China from 1999 to 2013, this paper for the first time uses correlation analysis and regression analysis methods to analyze the relationship between FWC and forest silviculture investment in fixed assets (FSIFA). Results show that FWC and FSIFA have a strong correlation and a strong influence, correlation coefficient is around 0.96. The amount of annual forest water conservation is increased with an increase in investment in fixed assets. The study also found that FSIFA affecting annual FWC lags more than 1 year, showing that FSIFA cannot play a role in water conservation immediately. The research also discussed other affecting factors on FWC, such as forest coverage rate, economic development level and forest quality improvement, etc. Their effects were also found to lag 1–5 years. Finally, the paper predicts the amount of annual FWC from 2014 to 2020 and gives some suggestions to strengthen investment in forest fixed assets and improve management of forest resources so as to promote the development of benefits of FWC.

Pengembangan Perangkat Pembelajaran Bahasa Indonesia Bermodel JOSUA untuk Meningkatkan Keterampilan Menulis dan Berbicara Siswa Kelas IV Sekolah Dasar

Inaccuracy in the use of the model will cause saturation for students and students to be passive in learning. For that need to design more innovative learning, one of the selected learning model is JOSUA learning model that can increase activity in student learning activities and student learning outcomes. This research uses 4-D development model (Four D) which develops a learning device using JOSUA model. Data analysis in this research is done by using quantitative descriptive analysis. The results of this study indicate that, the activities of students during the learning activities show active. Student responses to the JOSUA model (network, observation, simulation, and final repetition) show a good response. And there is an increase in the ability to write and speak students during the implementation of learning learning JOSUA Indonesian language (network, observation, simulation, and final repetition) can be said to increase.

Lidar network observation of dust layer evolution over the Gobi Desert in MAY 2013

A lidar network captured the evolution of a dust layer in the Gobi Desert on 22–23 May 2013. The lidar network consists of a ceilometer and two AD-Net lidars in Mongolia. The dust layer was generated by a strong wind due to a cold front and elevated over the surface of the cold front by an updraft of the warm air in the cold-front system. It was evolving from the atmospheric boundary layer to the free troposphere while moving 600 km through the desert with the cold front.