142 research outputs found

    Determination of dynamic impact factor for continuous girder bridge due to vehicle braking force by finite element method and experimental

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    In this study, the finite element method (FEM) is used to investigate the dynamic response of continuous girder bridge due to moving three-axle vehicle . Vertical reaction forces of axles that change with time make bending vibration of girder significantly Β increase. The braking in the first span is able to create response in other spans. In addition, the dynamic impact factors are investigated by both FEM and experiment for Hoa Xuan bridge. The results of this study provide an improved understanding of the bridge dynamic behavior and can be used as additional references for bridge codes by practicing engineers

    ACTUAL SITUATION OF HUMAN RESOURCES WITH BACHELOR’S DEGREE OF SPORTS MAJORING IN BASKETBALL AT BAC NINH SPORT UNIVERSITY OF VIETNAM

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    The study investigated the assessing the actual situation of human resources with bachelor’s degree in Basketball major, Bac Ninh Sport University of Viet Nam in the period of 2015-2019 through the following criteria: characteristics of the major graduates and job searching results of the bachelors after graduation. The result showed that the percentage of enrolled and graduated students majoring in Basketball accounts for a high percentage of the total students in the university. However, the number of students majoring in Basketball does the right job after leaving university is still low. The level of meeting the social requirements of Bachelors of Sports majoring in Basketball is mainly at the average level.Β  Article visualizations

    Identify and predict incorrect prices by Machine Learning Model

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    Electronic commerce (e-commerce) brings huge advantages to businesses for selling products through multiple online shops. However, companies have difficulties in supervising the prices of products set by different retail shops on e-commerce platforms. Addressing these difficulties, we suggest a method to identify and predict products that sell at incorrect prices using a machine learning model combined price analysis. The study uses four machine learning models: K-nearest Neighbor (KNN), Random Forest (RF), Support Vector Machine (SVM), and Multinomial Naive Bayes (MNB) and two text-based information extraction methods: BoW and TF-IDF to find to the best method. The research results show that the RF model and text-based information extraction method by the BoW provide more average accuracy than other specific models, when experimenting on the filter dataset the average accuracy after 10 runs are RF: 98.06%, SVM: 83.92%, MNB: 92.21%, KNN: 94.06%. Experimental results on the product dataset have an accuracy of RF: 83.02%, SVM: 55%, MNB: 79.33%, KNN: 79.36%

    Climatological regime and weather condition occurred on the cruise expedition (May 1999) on Vietnam continental shelf

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    The report is considered in two parts as climatological regime in which the most of meteorological parameters are summarized in its climatological conditions based on long time series of data and the exact weather phenomenon occurred on the area during the time of the expedition. In doing such study we have used two kinds of data, one is climatological data collected during the recent 30 years on the stations located along the Vietnam coast and islands, another is data collected during the time of present cruise expedition. The final consideration will reveal the variation of the weather condition in comparison with the climatological characteristics of each meteorological parameter. The cruise crossing expedition comprises 58 points expanding throughout on Vietnam continental shelf. The study area can be divided into 6 areas depending on the geographical and hydro- meteorological features of each region. We try to describe the climatological regime in each region in particular and the weather condition of the whole area during the time of cruise exploitation

    Factors contributing to animal health risks: Implication for smallholder pig production in Vietnam

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    In Vietnam, there are about four million households producing pigs of which more than half are producing at small scale, i.e., about one to two pigs per production cycle. One of the most critical constraints to pig production, especially for small scale, is the presence of animal disease. Many types of diseases have been reported by smallholder pig producers in Hung Yen such as diarrhea, pneumonia, fever, blue ear, head edema and pasteurellosis. The percentage of sick pigs is highest among piglets (27 percent), as compared with growing pigs and fatteners (five percent each). Diseases could lead to death of pigs, resulting in economic losses to the pig producers. Estimates of the cost of mortality in pig production in Hung Yen were about 3.3 million VND per household, accounting for about 13.6 percent of total income from pig production. Results of this study suggest that there are some practices that contribute to mitigating disease risk and those practices can be easily applied at small scale of pig production. These practices are related to applying a suitable production scale, isolating different age classes of pigs, designing pig houses and using specialized livestock farming tools and sanitation. The value of losses avoided from the above practices is estimated at 320.3 USD per household per year

    Cognitive full-duplex relay networks under the peak interference power constraint of multiple primary users

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    Abstract This paper investigates the outage performance of cognitive spectrum-sharing multi-relay networks in which the relays operate in a full-duplex (FD) mode and employ the decode-and-forward (DF) protocol. Two relay selection schemes, i.e., partial relay selection (PRS) and optimal relay selection (ORS), are considered to enhance the system performance. New exact expressions for the outage probability (OP) in both schemes are derived based on which an asymptotic analysis is carried out. The results show that the ORS strategy outperforms PRS in terms of OP, and increasing the number of FD relays can significantly improve the system performance. Moreover, novel analytical results provide additional insights for system design. In particular, from the viewpoint of FD concept, the primary network parameters (i.e., peak interference at the primary receivers, number of primary receivers, and their locations) should be carefully considered since they significantly affect the secondary network performance

    НСравСнство Π΄ΠΎΡ…ΠΎΠ΄ΠΎΠ² Π² Ρ€Π°Π·Π»ΠΈΡ‡Π½Ρ‹Ρ… сСкторах экономики Π’ΡŒΠ΅Ρ‚Π½Π°ΠΌΠ°: Π°Π½Π°Π»ΠΈΠ· структурных связСй

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    НСсмотря Π½Π° Π²Ρ‹Π΄Π°ΡŽΡ‰ΠΈΠ΅ΡΡ достиТСния Π² области сокращСния бСдности, нСравСнство Π΄ΠΎΡ…ΠΎΠ΄ΠΎΠ² Π²ΠΎ Π’ΡŒΠ΅Ρ‚Π½Π°ΠΌΠ΅ ΠΏΠΎ-ΠΏΡ€Π΅ΠΆΠ½Π΅ΠΌΡƒ ΠΈΠΌΠ΅Π΅Ρ‚ Ρ‚Π΅Π½Π΄Π΅Π½Ρ†ΠΈΡŽ ΠΊ ΡƒΠ²Π΅Π»ΠΈΡ‡Π΅Π½ΠΈΡŽ, оказывая Π½Π΅Π³Π°Ρ‚ΠΈΠ²Π½ΠΎΠ΅ влияниС Π½Π° устойчивоС Ρ€Π°Π·Π²ΠΈΡ‚ΠΈΠ΅ страны. ЦСль исслСдования β€” выявлСниС ΠΈ ΠΈΠ·ΠΌΠ΅Ρ€Π΅Π½ΠΈΠ΅ влияния сСкторов экономики Π½Π° Π΄ΠΎΡ…ΠΎΠ΄Ρ‹ Ρ€Π°Π·Π»ΠΈΡ‡Π½Ρ‹Ρ… Π³Ρ€ΡƒΠΏΠΏ насСлСния; ΠΏΠΎΠ»ΡƒΡ‡Π΅Π½Π½Ρ‹Π΅ Π΄Π°Π½Π½Ρ‹Π΅ ΠΌΠΎΠ³ΡƒΡ‚ Π±Ρ‹Ρ‚ΡŒ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΠΎΠ²Π°Π½Ρ‹ для сниТСния уровня бСдности Π²ΠΎ Π’ΡŒΠ΅Ρ‚Π½Π°ΠΌΠ΅. Бвязь ΠΌΠ΅ΠΆΠ΄Ρƒ сСкторами экономики ΠΈ распрСдСлСниСм Π΄ΠΎΡ…ΠΎΠ΄ΠΎΠ² насСлСния Π’ΡŒΠ΅Ρ‚Π½Π°ΠΌΠ° Π±Ρ‹Π»Π° выявлСна ΠΏΡ€ΠΈ ΠΏΠΎΠΌΠΎΡ‰ΠΈ ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΠΈ Π°Π½Π°Π»ΠΈΠ·Π° структурных связСй, основанной Π½Π° ΠΌΠ°Ρ‚Ρ€ΠΈΡ†Π΅ ΡΠΎΡ†ΠΈΠ°Π»ΡŒΠ½Ρ‹Ρ… счСтов Π·Π° 2016 Π³., которая Π΄ΠΎ сих ΠΏΠΎΡ€ Π½Π΅ ΠΏΠΎΠ»ΡƒΡ‡ΠΈΠ»Π° ΡˆΠΈΡ€ΠΎΠΊΠΎΠ³ΠΎ примСнСния срСди Π²ΡŒΠ΅Ρ‚Π½Π°ΠΌΡΠΊΠΈΡ… ΡƒΡ‡Π΅Π½Ρ‹Ρ…. По ΡΡ€Π°Π²Π½Π΅Π½ΠΈΡŽ с ΠΏΡ€Π΅Π΄Ρ‹Π΄ΡƒΡ‰ΠΈΠΌΠΈ Ρ€Π°Π±ΠΎΡ‚Π°ΠΌΠΈ, Π΄Π°Π½Π½ΠΎΠ΅ исслСдованиС ΠΏΡ€ΠΎΠ²Π΅Π΄Π΅Π½ΠΎ Π½Π° ΡƒΡ€ΠΎΠ²Π½Π΅ страны, Π° Π½Π΅ Ρ€Π΅Π³ΠΈΠΎΠ½Π°. Π’Π°ΠΊΠΆΠ΅ Π±Ρ‹Π»ΠΈ ΠΏΠΎΠ΄Ρ€ΠΎΠ±Π½ΠΎ описаны Ρ„Π°ΠΊΡ‚ΠΎΡ€Ρ‹, Π²Π»ΠΈΡΡŽΡ‰ΠΈΠ΅ Π½Π° распрСдСлСниС Π΄ΠΎΡ…ΠΎΠ΄ΠΎΠ², Ρ‚Π°ΠΊΠΈΠ΅ ΠΊΠ°ΠΊ сСкторы экономики, Ρ‚Ρ€ΡƒΠ΄ΠΎΠ²Ρ‹Π΅ рСсурсы ΠΈ Π³Ρ€ΡƒΠΏΠΏΡ‹ насСлСния. Анализ выявил, Ρ‡Ρ‚ΠΎ распрСдСлСниС большСй части Π΄ΠΎΡ…ΠΎΠ΄ΠΎΠ² 25 сСкторов экономики происходит ΠΏΠΎ 513 ΠΏΠΎΡ‚ΠΎΠΊΠ°ΠΌ. ΠŸΡ€ΠΈ Ρ€Π°ΡΡˆΠΈΡ€Π΅Π½ΠΈΠΈ сСкторов экономики вслСдствиС политичСских ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ ΠΏΠΎΠ²Ρ‹ΡˆΠ΅Π½ΠΈΠ΅ Π΄ΠΎΡ…ΠΎΠ΄ΠΎΠ² насСлСния Π² основном зависит ΠΎΡ‚ Ρ‚Π°ΠΊΠΈΡ… ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»Π΅ΠΉ, ΠΊΠ°ΠΊ квалификация Ρ€Π°Π±ΠΎΡ‚Π½ΠΈΠΊΠΎΠ², ΠΊΠ°ΠΏΠΈΡ‚Π°Π» ΠΈ ΠΌΠ°ΡΡˆΡ‚Π°Π± мСТотраслСвых связСй. ΠŸΡ€ΠΈΠΌΠ΅Ρ‡Π°Ρ‚Π΅Π»ΡŒΠ½ΠΎ, Ρ‡Ρ‚ΠΎ Π½Π° Π΄ΠΎΡ…ΠΎΠ΄Ρ‹ городских домохозяйств сущСствСнноС влияниС ΠΎΠΊΠ°Π·Ρ‹Π²Π°Π΅Ρ‚ ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»ΡŒ «высококвалифицированный Ρ‚Ρ€ΡƒΠ΄Β», Π² Ρ‚ΠΎ врСмя ΠΊΠ°ΠΊ ΠΊΠ°ΠΏΠΈΡ‚Π°Π» являСтся Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ Π²Π°ΠΆΠ½Ρ‹ΠΌ Ρ„Π°ΠΊΡ‚ΠΎΡ€ΠΎΠΌ, Π²Π»ΠΈΡΡŽΡ‰ΠΈΠΌ Π½Π° Π΄ΠΎΡ…ΠΎΠ΄Ρ‹ ΡΠ΅Π»ΡŒΡΠΊΠΈΡ… домохозяйств. Богласно ΠΏΡ€ΠΎΠ²Π΅Π΄Π΅Π½Π½ΠΎΠΌΡƒ Π°Π½Π°Π»ΠΈΠ·Ρƒ, 32 ΠΏΠΎΡ‚ΠΎΠΊΠ° Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ Π·Π½Π°Ρ‡ΠΈΠΌΠΎ Π²Π»ΠΈΡΡŽΡ‚ Π½Π° Π΄ΠΎΡ…ΠΎΠ΄Ρ‹ насСлСния. Π’Π°ΠΆΠ½ΡƒΡŽ Ρ€ΠΎΠ»ΡŒ Π² Π±ΠΎΡ€ΡŒΠ±Π΅ с Π±Π΅Π΄Π½ΠΎΡΡ‚ΡŒΡŽ ΠΈΠ³Ρ€Π°ΡŽΡ‚ ΡΠ»Π΅Π΄ΡƒΡŽΡ‰ΠΈΠ΅ сСкторы экономики: лСсноС хозяйство, дрСвСсина ΠΈ издСлия ΠΈΠ· дрСвСсины, рыболовство, Π΄ΠΎΠ±Ρ‹Ρ‡Π° угля, сырой Π½Π΅Ρ„Ρ‚ΠΈ ΠΈ ΠΏΡ€ΠΈΡ€ΠΎΠ΄Π½ΠΎΠ³ΠΎ Π³Π°Π·Π°, производство ΠΎΠ±ΡƒΠ²ΠΈ, поставки элСктроэнСргии, Π³Π°Π·Π°, Π²ΠΎΠ΄Ρ‹ ΠΈ ΠΊΠΎΠΌΠΌΡƒΠ½Π°Π»ΡŒΠ½Ρ‹Ρ… услуг, Π° Ρ‚Π°ΠΊΠΆΠ΅ розничная ΠΈ оптовая торговля. ΠŸΠΎΠ»ΡƒΡ‡Π΅Π½Π½Ρ‹Π΅ Π΄Π°Π½Π½Ρ‹Π΅ послуТили основой для Ρ€Π΅ΠΊΠΎΠΌΠ΅Π½Π΄Π°Ρ†ΠΈΠΉ Π² области сокращСния нСравСнства Π΄ΠΎΡ…ΠΎΠ΄ΠΎΠ²

    НСравСнство Π΄ΠΎΡ…ΠΎΠ΄ΠΎΠ² Π² Ρ€Π°Π·Π»ΠΈΡ‡Π½Ρ‹Ρ… сСкторах экономики Π’ΡŒΠ΅Ρ‚Π½Π°ΠΌΠ°: Π°Π½Π°Π»ΠΈΠ· структурных связСй

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    НСсмотря Π½Π° Π²Ρ‹Π΄Π°ΡŽΡ‰ΠΈΠ΅ΡΡ достиТСния Π² области сокращСния бСдности, нСравСнство Π΄ΠΎΡ…ΠΎΠ΄ΠΎΠ² Π²ΠΎ Π’ΡŒΠ΅Ρ‚Π½Π°ΠΌΠ΅ ΠΏΠΎ-ΠΏΡ€Π΅ΠΆΠ½Π΅ΠΌΡƒ ΠΈΠΌΠ΅Π΅Ρ‚ Ρ‚Π΅Π½Π΄Π΅Π½Ρ†ΠΈΡŽ ΠΊ ΡƒΠ²Π΅Π»ΠΈΡ‡Π΅Π½ΠΈΡŽ, оказывая Π½Π΅Π³Π°Ρ‚ΠΈΠ²Π½ΠΎΠ΅ влияниС Π½Π° устойчивоС Ρ€Π°Π·Π²ΠΈΡ‚ΠΈΠ΅ страны. ЦСль исслСдования β€” выявлСниС ΠΈ ΠΈΠ·ΠΌΠ΅Ρ€Π΅Π½ΠΈΠ΅ влияния сСкторов экономики Π½Π° Π΄ΠΎΡ…ΠΎΠ΄Ρ‹ Ρ€Π°Π·Π»ΠΈΡ‡Π½Ρ‹Ρ… Π³Ρ€ΡƒΠΏΠΏ насСлСния; ΠΏΠΎΠ»ΡƒΡ‡Π΅Π½Π½Ρ‹Π΅ Π΄Π°Π½Π½Ρ‹Π΅ ΠΌΠΎΠ³ΡƒΡ‚ Π±Ρ‹Ρ‚ΡŒ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΠΎΠ²Π°Π½Ρ‹ для сниТСния уровня бСдности Π²ΠΎ Π’ΡŒΠ΅Ρ‚Π½Π°ΠΌΠ΅. Бвязь ΠΌΠ΅ΠΆΠ΄Ρƒ сСкторами экономики ΠΈ распрСдСлСниСм Π΄ΠΎΡ…ΠΎΠ΄ΠΎΠ² насСлСния Π’ΡŒΠ΅Ρ‚Π½Π°ΠΌΠ° Π±Ρ‹Π»Π° выявлСна ΠΏΡ€ΠΈ ΠΏΠΎΠΌΠΎΡ‰ΠΈ ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΠΈ Π°Π½Π°Π»ΠΈΠ·Π° структурных связСй, основанной Π½Π° ΠΌΠ°Ρ‚Ρ€ΠΈΡ†Π΅ ΡΠΎΡ†ΠΈΠ°Π»ΡŒΠ½Ρ‹Ρ… счСтов Π·Π° 2016 Π³., которая Π΄ΠΎ сих ΠΏΠΎΡ€ Π½Π΅ ΠΏΠΎΠ»ΡƒΡ‡ΠΈΠ»Π° ΡˆΠΈΡ€ΠΎΠΊΠΎΠ³ΠΎ примСнСния срСди Π²ΡŒΠ΅Ρ‚Π½Π°ΠΌΡΠΊΠΈΡ… ΡƒΡ‡Π΅Π½Ρ‹Ρ…. По ΡΡ€Π°Π²Π½Π΅Π½ΠΈΡŽ с ΠΏΡ€Π΅Π΄Ρ‹Π΄ΡƒΡ‰ΠΈΠΌΠΈ Ρ€Π°Π±ΠΎΡ‚Π°ΠΌΠΈ, Π΄Π°Π½Π½ΠΎΠ΅ исслСдованиС ΠΏΡ€ΠΎΠ²Π΅Π΄Π΅Π½ΠΎ Π½Π° ΡƒΡ€ΠΎΠ²Π½Π΅ страны, Π° Π½Π΅ Ρ€Π΅Π³ΠΈΠΎΠ½Π°. Π’Π°ΠΊΠΆΠ΅ Π±Ρ‹Π»ΠΈ ΠΏΠΎΠ΄Ρ€ΠΎΠ±Π½ΠΎ описаны Ρ„Π°ΠΊΡ‚ΠΎΡ€Ρ‹, Π²Π»ΠΈΡΡŽΡ‰ΠΈΠ΅ Π½Π° распрСдСлСниС Π΄ΠΎΡ…ΠΎΠ΄ΠΎΠ², Ρ‚Π°ΠΊΠΈΠ΅ ΠΊΠ°ΠΊ сСкторы экономики, Ρ‚Ρ€ΡƒΠ΄ΠΎΠ²Ρ‹Π΅ рСсурсы ΠΈ Π³Ρ€ΡƒΠΏΠΏΡ‹ насСлСния. Анализ выявил, Ρ‡Ρ‚ΠΎ распрСдСлСниС большСй части Π΄ΠΎΡ…ΠΎΠ΄ΠΎΠ² 25 сСкторов экономики происходит ΠΏΠΎ 513 ΠΏΠΎΡ‚ΠΎΠΊΠ°ΠΌ. ΠŸΡ€ΠΈ Ρ€Π°ΡΡˆΠΈΡ€Π΅Π½ΠΈΠΈ сСкторов экономики вслСдствиС политичСских ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ ΠΏΠΎΠ²Ρ‹ΡˆΠ΅Π½ΠΈΠ΅ Π΄ΠΎΡ…ΠΎΠ΄ΠΎΠ² насСлСния Π² основном зависит ΠΎΡ‚ Ρ‚Π°ΠΊΠΈΡ… ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»Π΅ΠΉ, ΠΊΠ°ΠΊ квалификация Ρ€Π°Π±ΠΎΡ‚Π½ΠΈΠΊΠΎΠ², ΠΊΠ°ΠΏΠΈΡ‚Π°Π» ΠΈ ΠΌΠ°ΡΡˆΡ‚Π°Π± мСТотраслСвых связСй. ΠŸΡ€ΠΈΠΌΠ΅Ρ‡Π°Ρ‚Π΅Π»ΡŒΠ½ΠΎ, Ρ‡Ρ‚ΠΎ Π½Π° Π΄ΠΎΡ…ΠΎΠ΄Ρ‹ городских домохозяйств сущСствСнноС влияниС ΠΎΠΊΠ°Π·Ρ‹Π²Π°Π΅Ρ‚ ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»ΡŒ «высококвалифицированный Ρ‚Ρ€ΡƒΠ΄Β», Π² Ρ‚ΠΎ врСмя ΠΊΠ°ΠΊ ΠΊΠ°ΠΏΠΈΡ‚Π°Π» являСтся Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ Π²Π°ΠΆΠ½Ρ‹ΠΌ Ρ„Π°ΠΊΡ‚ΠΎΡ€ΠΎΠΌ, Π²Π»ΠΈΡΡŽΡ‰ΠΈΠΌ Π½Π° Π΄ΠΎΡ…ΠΎΠ΄Ρ‹ ΡΠ΅Π»ΡŒΡΠΊΠΈΡ… домохозяйств. Богласно ΠΏΡ€ΠΎΠ²Π΅Π΄Π΅Π½Π½ΠΎΠΌΡƒ Π°Π½Π°Π»ΠΈΠ·Ρƒ, 32 ΠΏΠΎΡ‚ΠΎΠΊΠ° Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ Π·Π½Π°Ρ‡ΠΈΠΌΠΎ Π²Π»ΠΈΡΡŽΡ‚ Π½Π° Π΄ΠΎΡ…ΠΎΠ΄Ρ‹ насСлСния. Π’Π°ΠΆΠ½ΡƒΡŽ Ρ€ΠΎΠ»ΡŒ Π² Π±ΠΎΡ€ΡŒΠ±Π΅ с Π±Π΅Π΄Π½ΠΎΡΡ‚ΡŒΡŽ ΠΈΠ³Ρ€Π°ΡŽΡ‚ ΡΠ»Π΅Π΄ΡƒΡŽΡ‰ΠΈΠ΅ сСкторы экономики: лСсноС хозяйство, дрСвСсина ΠΈ издСлия ΠΈΠ· дрСвСсины, рыболовство, Π΄ΠΎΠ±Ρ‹Ρ‡Π° угля, сырой Π½Π΅Ρ„Ρ‚ΠΈ ΠΈ ΠΏΡ€ΠΈΡ€ΠΎΠ΄Π½ΠΎΠ³ΠΎ Π³Π°Π·Π°, производство ΠΎΠ±ΡƒΠ²ΠΈ, поставки элСктроэнСргии, Π³Π°Π·Π°, Π²ΠΎΠ΄Ρ‹ ΠΈ ΠΊΠΎΠΌΠΌΡƒΠ½Π°Π»ΡŒΠ½Ρ‹Ρ… услуг, Π° Ρ‚Π°ΠΊΠΆΠ΅ розничная ΠΈ оптовая торговля. ΠŸΠΎΠ»ΡƒΡ‡Π΅Π½Π½Ρ‹Π΅ Π΄Π°Π½Π½Ρ‹Π΅ послуТили основой для Ρ€Π΅ΠΊΠΎΠΌΠ΅Π½Π΄Π°Ρ†ΠΈΠΉ Π² области сокращСния нСравСнства Π΄ΠΎΡ…ΠΎΠ΄ΠΎΠ²
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