Perlindungan Hukum terhadap Hak Karyawan dengan Sistem Outsourcing pada Perusahaan Badan Usaha Milik Negara (Bumn) di Kota Pontianak

This study aims to determine: 1) the reasons BUMN In Pontianak using a system of Outsourcing in the recruitment of employees. 2) outsourcing practices in BUMN in Pontianak, 3) the factors that cause outsourcing system has not given legal protection of employees and 4) the perspective of the legal regulation of the employees who were recruited by the BUMN system outsourcing in Indonesia. The research was conducted at the Department of Social Welfare and Labor Pontianak, and involve Pontianak Trade Union Chairman, Director of PT. Media Prima HR Solutions in Pontianak, Director of PT. Telkom Pontianak, Director of PT. PLN Pontianak, Director of PT. Pertamina Pontianak and workers / laborers who work in state-owned companies Pontianak. Data collection methods used were interviews, questionnaires, and direct observations. The data obtained in qualitative analysis. The results show that the legal protection of workers / laborers, both contradictory, always found the gap between das sollen (must) and das science (reality) and always appeared discrepancy between the law in the books and law in action. Fact of economic life with the hegemony of financial capitalism has operated through the "dis-solution subject" who do not see the workers / laborers as production subject that should be protected, but rather as an object that can be exploited, this is what happens in the practice of outsourcing in Indonesia, so that the legalization of outsourcing by Law No. 13 Year 2003 on Manpower reap kotroversi. For those who disagree argue useful in outsourced business development and create new jobs. For those who refused to believe the practice of outsourcing is a modern style of capitalism that brought misery to the workers / laborers. Based on the fact that the authors formulate the problem: 1) Why BUMN In Pontianak Still Using Outsourcing System In Recruitment? 2) Why not outsource system provide legal protection for employees? 3) How should the legal arrangements for employees who were recruited by the BUMN system outsourcing in Indonesia? The objectives are: 1) To explain the reasons BUMN In Pontianak using Outsourcing the recruitment system. 2) To determine the state of outsourcing practices in Pontianak. 3) To disclose and explain the factors that cause outsourcing system has not been providing legal protection for employees. 4) To reveal the perspective of the legal regulation of the employees who were recruited by the BUMN system outsourcing in Indonesia. To answer the problems and research objectives, juridical approach used empirical / sociological research Descriptive Analytical specifications. Data types include Primary Data and Secondary Data collected through library research and documentation (library and documentation) as well as field research (field research), while the sampling was done by using non-random sampling with purposive sampling method. From the discussion, note that the legality of many violations of outsourcing in terms of Pontianak, employment protection and working conditions for workers / laborers outsourcing is not given by the employer to the fullest, while legal protection for workers / laborers are constrained due to the weakness in the system employment law, good substance, structure and culture. Therefore, it is necessary revision of labor legislation, the Local Government of Pontianak need to increase the numberof labor inspectors personnel, provide facilities and an adequate budget for the operation of the labor inspection in order to carry out its duties and functions to the fullest and empower Unions / Union to be able to carry out the purposes and functions well.Keywords: Outsourcing employee/ labour and Legal Protection. A B S T R A KPenelitian ini bertujuan untuk mengetahui : 1) alasan BUMN Di Kota Pontianak menggunakan sistem Outsourcing dalam perekrutan karyawan. 2) praktik outsourcing pada BUMN di Kota Pontianak, 3) faktor-faktor penyebab sistem outsourcing belum memberikan perlindungan hukum terhadap karyawan dan 4) perspektif pengaturan hukum terhadap karyawan yang direkrut dengan sistem outsourcing pada BUMN di Indonesia. Penelitian ini dilakukan di Dinas Sosial dan Tenaga Kerja Pontianak, dan melibatkan Ketua Serikat Buruh Kota Pontianak, Direktur PT. Media Prima HR Solutions di Kota Pontianak, Direktur PT. Telkom Kota Pontianak, Direktur PT. PLN Pontianak, Direktur PT. Pertamina Pontianak serta pekerja/buruh yang bekerja pada Perusahaan BUMN Kota Pontianak. Metode pengumpulan data yang digunakan adalah wawancara, kuesioner, dan pengamatan langsung. Data yang diperoleh di analisis secara kualitatif. Hasil penelitian menunjukkan bahwa perlindungan hukum pekerja/buruh, keduanya saling bertentangan, selalu dijumpai kesenjangan antara das sollen (keharusan) dan das sain (Kenyataan) dan selalu muncul diskrepansi antara law in the books dan law in action. Nyatanya kehidupan ekonomi dengan hegemoni kapitalisme financial telah beroperasi melalui dis-solution subject yang tidak memandang pekerja/buruh sebagai subjek produksi yang patut dilindungi, melainkan sebagai objek yang bisa di eksploitasi, inilah yang terjadi dalam praktik outsourcing di Indonesia, sehingga legalisasi outsourcing berdasarkan Undang-Undang Nomor 13 Tahun 2003 Tentang Ketenagakerjaan menuai kotroversi. Bagi yang setuju berdalih outsourcing bermanfaat dalam pengembangan usaha dan membuka lapangan kerja baru. Bagi yang menolak beranggapan praktik outsourcing merupakan corak kapitalisme modern yang membawa kesengsaraan bagi pekerja/buruh. Berdasarkan Kenyataan itu penulis merumuskan masalah : 1) Mengapa BUMN Di Kota Pontianak Masih Menggunakan Sistem Outsourcing Dalam Perekrutan Karyawan ? 2) Mengapa sistem outsourcing tidak memberikan perlindungan hukum terhadap karyawan ? 3) Bagaimana seharusnya pengaturan hukum terhadap karyawan yang direkrut dengan sistem outsourcing pada BUMN di Indonesia ? Tujuannya adalah : 1) Untuk menjelaskan mengenai alasan BUMN Di Kota Pontianak menggunakan sistem Outsourcing dalam perekrutan karyawan. 2) Untuk mengetahui praktik outsourcing pada BUMN di Kota Pontianak. 3) Untuk mengungkapkan dan menjelaskan faktor-faktor penyebab sistem outsourcing belum memberikan perlindungan hukum terhadap karyawan. 4) Untuk mengungkapkan perspektif pengaturan hukum terhadap karyawan yang direkrut dengan sistem outsourcing pada BUMN di Indonesia. Untuk menjawab permasalahan dan tujuan penelitian, digunakan metode pendekatan yuridis empiris/sosiologis dengan spesifikasi penelitian Deskriptif Analitis. Jenis datanya meliputi Data Primer dan Data Skunder yang dikumpulkan melalui penelitian kepustakaan dan dokumentasi(library and documentation) serta penelitian lapangan(field research), sedangkan pengambilan sampel dilakukan dengan menggunakan teknik Non Random Sampling dengan metode Purposive Sampling. Dari hasil pembahasan diketahui bahwa secara legalitas banyak terjadi pelanggaran syarat-syarat outsourcing di Kota Pontianak, perlindungan kerja dan syarat-syarat kerja bagi pekerja/buruh outsourcing tidak diberikan oleh pengusaha secara maksimal, sedangkan perlindungan hukum bagi pekerja/buruh terkendala karena adanyakelemahan dalam system hukum ketenagakerjaan, baik substansi, struktur maupun kulturnya. Oleh karena itu, perlu revisi atas beberapa peraturan Perundang-undangan ketenagakerjaan, Pemerintah Daerah Kota Pontianak perlu menambah jumlah personel pegawai pengawas ketenagakerjaan, menyediakan sarana dan fasilitas serta anggaran yang memadai untuk operasional pengawasan ketenagakerjaan agar dapat menjalankan tugas dan fungsinya secara maksimal serta memberdayakan Serikat Pekerja/Serikat Buruh agar mampu menjalankan tujuan dan fungsinya dengan baik.Kata Kunci : Pekerja/Buruh Outsourcing dan Perlindungan Hukum

Partial heat-integrated reactive distillation process for producing n-propyl acetate using a heat exchanger network

In this work, a partial heat-integrated reactive distillation process was studied to yield n-propyl acetate. To optimize the operating parameters of two distinct processes, the sequential iteration optimization method was employed. The heat exchanger network (HEN) is an effective approach for the heat-integrated design of a distillation process. Compared with the conventional reactive distillation process, the total annual cost, CO2 emissions and total energy consumption of the partial heat-integrated reactive distillation process decreased by 20.7%, 31.1%, and 32.2%, respectively. The thermodynamic efficiencies of reactive distillation process and partial heat-integrated reactive distillation process were 4.33% and 9.86%, respectively. The significance of this paper is crucial in guiding the process of partial heat-integrated reactive distillation for the production of n-propyl acetate.</p

Supplementary document for Deep learning using residual deconvolutional network enables real-time high-density single-molecule localization microscopy - 6353834.pdf

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Large-Scale Prediction of Collision Cross-Section Values for Metabolites in Ion Mobility-Mass Spectrometry

The rapid development of metabolomics has significantly advanced health and disease related research. However, metabolite identification remains a major analytical challenge for untargeted metabolomics. While the use of collision cross-section (CCS) values obtained in ion mobility-mass spectrometry (IM-MS) effectively increases identification confidence of metabolites, it is restricted by the limited number of available CCS values for metabolites. Here, we demonstrated the use of a machine-learning algorithm called support vector regression (SVR) to develop a prediction method that utilized 14 common molecular descriptors to predict CCS values for metabolites. In this work, we first experimentally measured CCS values (Ω_N2) of ∼400 metabolites in nitrogen buffer gas and used these values as training data to optimize the prediction method. The high prediction precision of this method was externally validated using an independent set of metabolites with a median relative error (MRE) of ∼3%, better than conventional theoretical calculation. Using the SVR based prediction method, a large-scale predicted CCS database was generated for 35 203 metabolites in the Human Metabolome Database (HMDB). For each metabolite, five different ion adducts in positive and negative modes were predicted, accounting for 176 015 CCS values in total. Finally, improved metabolite identification accuracy was demonstrated using real biological samples. Conclusively, our results proved that the SVR based prediction method can accurately predict nitrogen CCS values (Ω_N2) of metabolites from molecular descriptors and effectively improve identification accuracy and efficiency in untargeted metabolomics. The predicted CCS database, namely, MetCCS, is freely available on the Internet

Large-Scale Prediction of Collision Cross-Section Values for Metabolites in Ion Mobility-Mass Spectrometry

The rapid development of metabolomics has significantly advanced health and disease related research. However, metabolite identification remains a major analytical challenge for untargeted metabolomics. While the use of collision cross-section (CCS) values obtained in ion mobility-mass spectrometry (IM-MS) effectively increases identification confidence of metabolites, it is restricted by the limited number of available CCS values for metabolites. Here, we demonstrated the use of a machine-learning algorithm called support vector regression (SVR) to develop a prediction method that utilized 14 common molecular descriptors to predict CCS values for metabolites. In this work, we first experimentally measured CCS values (Ω_N2) of ∼400 metabolites in nitrogen buffer gas and used these values as training data to optimize the prediction method. The high prediction precision of this method was externally validated using an independent set of metabolites with a median relative error (MRE) of ∼3%, better than conventional theoretical calculation. Using the SVR based prediction method, a large-scale predicted CCS database was generated for 35 203 metabolites in the Human Metabolome Database (HMDB). For each metabolite, five different ion adducts in positive and negative modes were predicted, accounting for 176 015 CCS values in total. Finally, improved metabolite identification accuracy was demonstrated using real biological samples. Conclusively, our results proved that the SVR based prediction method can accurately predict nitrogen CCS values (Ω_N2) of metabolites from molecular descriptors and effectively improve identification accuracy and efficiency in untargeted metabolomics. The predicted CCS database, namely, MetCCS, is freely available on the Internet

An Insight into Dissolved Organic Matter Removal Characteristics of Recycling Filter Backwash Water: A Comparative Study

<div><p>It is necessary to put all aspects,,namely raw water characteristics, corresponding FBWW, and coagulation mechanisms, i.e., charge neutralization and sweep flocculation together to make clear the dissolved organic matter (DOM) removal characteristics and the fate of fractionations in recycle design. The DOM characteristics of molecular weight (MW) distribution, hydrophobicity, and fluorescence in source water W1 (synthesized water) and W2 (“Longtan” lake water), FBWW and treated water samples therefore are identified, and three recycling ratios of 2%, 5%, and 8% as compared to control (0%) are conducted. It is found that DOM within FBWW becomes more hydrophilic and lower MW as compared to corresponding source water. Recycling trials indicate that higher DOM concentrations and more low-MW fractions are not of any benefit to enhance UV₂₅₄ and DOC removal. Hydrophobic acid can be further eliminated in case recycling particles mainly produced by sweep flocculation, while weakly hydrophobic acid and hydrophilic fraction can be enhanced and removed under recycling particles mainly formed by charge neutralization. Higher molecular weight fraction (>30 kDa) exhibits potentially enhanced removal at preferred recycling ratio of 5%. Fluorescent characteristics analysis demonstrate that recycling FBWW can effectively improve humic-like substances removal, but the protein-like matters are resistant to be eliminated with unvaried structure.</p></div

LipidCCS: Prediction of Collision Cross-Section Values for Lipids with High Precision To Support Ion Mobility–Mass Spectrometry-Based Lipidomics

The use of collision cross-section (CCS) values derived from ion mobility–mass spectrometry (IM–MS) has been proven to facilitate lipid identifications. Its utility is restricted by the limited availability of CCS values. Recently, the machine-learning algorithm-based prediction (e.g., MetCCS) is reported to generate CCS values in a large-scale. However, the prediction precision is not sufficient to differentiate lipids due to their high structural similarities and subtle differences on CCS values. To address this challenge, we developed a new approach, namely, LipidCCS, to precisely predict lipid CCS values. In LipidCCS, a set of molecular descriptors were optimized using bioinformatic approaches to comprehensively describe the subtle structure differences for lipids. The use of optimized molecular descriptors together with a large set of standard CCS values for lipids (458 in total) to build the prediction model significantly improved the precision. The prediction precision of LipidCCS was externally validated with median relative errors (MRE) of ∼1% using independent data sets across different instruments (Agilent DTIM-MS and Waters TWIM-MS) and laboratories. We also demonstrated that the improved precision in the predicted LipidCCS database (15 646 lipids and 63 434 CCS values in total) could effectively reduce false-positive identifications of lipids. Common users can freely access our LipidCCS web server for the following: (1) the prediction of lipid CCS values directly from SMILES structure; (2) database search; and (3) lipid match and identification. We believe LipidCCS will be a valuable tool to support IM–MS-based lipidomics. The web server is freely available on the Internet (http://www.metabolomics-shanghai.org/LipidCCS/)

LipidCCS: Prediction of Collision Cross-Section Values for Lipids with High Precision To Support Ion Mobility–Mass Spectrometry-Based Lipidomics

The use of collision cross-section (CCS) values derived from ion mobility–mass spectrometry (IM–MS) has been proven to facilitate lipid identifications. Its utility is restricted by the limited availability of CCS values. Recently, the machine-learning algorithm-based prediction (e.g., MetCCS) is reported to generate CCS values in a large-scale. However, the prediction precision is not sufficient to differentiate lipids due to their high structural similarities and subtle differences on CCS values. To address this challenge, we developed a new approach, namely, LipidCCS, to precisely predict lipid CCS values. In LipidCCS, a set of molecular descriptors were optimized using bioinformatic approaches to comprehensively describe the subtle structure differences for lipids. The use of optimized molecular descriptors together with a large set of standard CCS values for lipids (458 in total) to build the prediction model significantly improved the precision. The prediction precision of LipidCCS was externally validated with median relative errors (MRE) of ∼1% using independent data sets across different instruments (Agilent DTIM-MS and Waters TWIM-MS) and laboratories. We also demonstrated that the improved precision in the predicted LipidCCS database (15 646 lipids and 63 434 CCS values in total) could effectively reduce false-positive identifications of lipids. Common users can freely access our LipidCCS web server for the following: (1) the prediction of lipid CCS values directly from SMILES structure; (2) database search; and (3) lipid match and identification. We believe LipidCCS will be a valuable tool to support IM–MS-based lipidomics. The web server is freely available on the Internet (http://www.metabolomics-shanghai.org/LipidCCS/)

L'Écho : grand quotidien d'information du Centre Ouest

05 décembre 19141914/12/05 (A43).Appartient à l’ensemble documentaire : PoitouCh

Synergistic Effect to High-Performance Perovskite Solar Cells with Reduced Hysteresis and Improved Stability by the Introduction of Na-Treated TiO₂ and Spraying-Deposited CuI as Transport Layers

For a typical perovskite solar cell (PKSC), both the electron transport layers (ETLs) and hole transport materials (HTMs) play a very important role in improving the device performance and long-term stability. In this paper, we firstly improve the electron transport properties by modification of TiO₂ ETLs with Na species, and an enhanced power conversion efficiency (PCE) of 16.91% has been obtained with less hysteresis. Subsequently, an inorganic CuI film prepared by a facile spray deposition method has been employed to replace the conventional spiro-OMeTAD as the HTM in PKSCs. Because of the improved transport properties at the ETL/perovskite and perovskite/HTM interfaces, a maximum photovoltaic efficiency of 17.6% with reduced hysteresis has been achieved in the PKSC with both the Na-modified TiO₂ ETL and 60 nm-thick CuI layer HTM. To our knowledge, the PCE achieved in this paper is one of the highest values ever reported for the PKSC devices with inorganic HTMs. More significantly, the PKSCs exhibit an outstanding device stability, their PCE remains constant after storage in the dark for 50 days, and they can retain approximately 92% of their initial efficiency after storage even for 90 days