Efektivitas Pengawasan terhadap Izin Tinggal Tenaga Kerja Asing di Wilayah Kerja Kantor Imigrasi Kelas I Pontianak (Studi Kasus terhadap Tenaga Kerja Asing di PT Well Harvest Winning Sungai Tegar, Kecamatan Kendawangan Kabupaten Ketapang)

This thesis discusses the role of the effectiveness of supervision of the residence permits of foreign workers in the region of class I Pontianak immigration office (a case study of foreign workers in PT Well Harvest Winning Tough River, District Kendawangan Ketapang). From the results of this thesis research we concluded that that Effectiveness Monitoring carried out by the Immigration Office Class I stayed Pontianak Against Foreign Workers Permits have been mostly ineffective due to very presence of violations in years 2014-2015, even though the relevant public has to supervise the workforce foreign accordance with the existing procedure only from foreign labor itself negligent, sometimes foreign nationals ignores the existing procedures at the Immigration office, causing their violations of immigration it can be shown by the violations such as: (a) Foreigners carrying out activities not suitable immigration permit (in accordance with article 122 paragraph a) 7 Case. (B) The foreigners do activities that endanger the security and order and does not respect the regulations (under Article 75) 2 Case. (C) Foreigners Stay Permit holders that have expired and are still in the Indonesian region of less than 90 (ninety) days of the deadline his residence permit. (Under Article 124) 4 Case. actors affecting oversight residence permits to foreign workers who work PT Well Harvest Winning that are in the working area of Immigration Class I Pontianak is Budget operational fund supervision is not appropriate, the lack of quantity and quality of the officer / officers / officials of immigration as a civil servant, a means and adequate infrastructure, as well as the Sponsor and TKA itself in obeying immigration rules and the role of the community as well as central and local governments in immigration law enforcement and supervision work area Class I Immigration Office of Pontianak City wide composed of 12 districts and 2 Cities. Efforts made by the Immigration Class I Pontianak in overseeing foreign labor is to provide direction and guidance to companies that did not submit a report on the whereabouts and activities of expatriate personnel, monitoring directly into the field where / location TKA are and their activities despite various limitations, and from time to time monitor or raids in cooperation with various authorities

Molecular identification of adenoviruses associated with respiratory infection in Egypt from 2003 to 2010.

BACKGROUND: Human adenoviruses of species B, C, and E (HAdV-B, -C, -E) are frequent causative agents of acute respiratory infections worldwide. As part of a surveillance program aimed at identifying the etiology of influenza-like illness (ILI) in Egypt, we characterized 105 adenovirus isolates from clinical samples collected between 2003 and 2010. METHODS: Identification of the isolates as HAdV was accomplished by an immunofluorescence assay (IFA) and confirmed by a set of species and type specific polymerase chain reactions (PCR). RESULTS: Of the 105 isolates, 42% were identified as belonging to HAdV-B, 60% as HAdV-C, and 1% as HAdV-E. We identified a total of six co-infections by PCR, of which five were HAdV-B/HAdV-C co-infections, and one was a co-infection of two HAdV-C types: HAdV-5/HAdV-6. Molecular typing by PCR enabled the identification of eight genotypes of human adenoviruses; HAdV-3 (n = 22), HAdV-7 (n = 14), HAdV-11 (n = 8), HAdV-1 (n = 22), HAdV-2 (20), HAdV-5 (n = 15), HAdV-6 (n = 3) and HAdV-4 (n = 1). The most abundant species in the characterized collection of isolates was HAdV-C, which is concordant with existing data for worldwide epidemiology of HAdV respiratory infections. CONCLUSIONS: We identified three species, HAdV-B, -C and -E, among patients with ILI over the course of 7 years in Egypt, with at least eight diverse types circulating

Mathematical approach of fiber optics for renewable energy sources using general adversarial networks

It is significantly more challenging to extend the visibility factor to a higher depth during the development phase of a communication system for subterranean places. Even if there are numerous optical fiber systems that provide the right energy sources for intended panels, the visibility parameter is not optimized past a certain point. Therefore, the suggested method looks at the properties of a fiber optic communication system that is integrated with a certain energy source while having external panels. A regulating state is established in addition to characteristic analysis by minimizing the reflection index, and the integration of the general adversarial network (GAN) optimizes both central and layer formations in exterior panels. Thus, the suggested technique uses the external noise factor to provide relevant data to the control center via fiber optic shackles. As a result, the normalized error is smaller, boosting the suggested method’s eectiveness in all subsurface areas. The created mathematical model is divided into five dierent situations, and the results are simulated using MATLAB to test the eectiveness of the anticipated strategy. Additionally, comparisons are done for each of the five scenarios, and it is found that the proposed fiber-optic method for energy sources is far more eective than current methodologies.publishedVersio

Autism Spectrum Disorder Prediction in Children Using Machine Learning

Life symptoms associated with autism spectrum disorder (ASD) typically manifest during childhood and persist into adolescence and adulthood. ASD, which can be caused by genetic or environmental factors, can be significantly improved through early detection and treatment. Currently, standardized clinical tests are the primary diagnostic method for ASD. However, these tests are time consuming and expensive. Early detection and intervention are pivotal in enhancing the long-term prospects of children diagnosed with ASD. Machine-learning (ML) techniques are being utilized alongside conventional methods to improve the accuracy and efficiency of ASD diagnosis. Therefore, the paper aims to explore the feasibility of employing support vector machines, random forest classifier, naïve Bayes, logistic regression (LR), K-nearest neighbor, and decision tree classification models on our dataset to construct predictive models for predicting and analyzing ASD problems across different age groups: children, adolescents, and adults. The proposed techniques are assessed using publicly available nonclinical ASD datasets of three distinct datasets. The four ASD datasets, namely toddlers, adolescents, children, and adults, were obtained from publicly available repositories, specifically Kaggle and UCI ML. These repositories provide a valuable data source for research and analysis related to ASD. Our main objective is to identify the susceptibility to ASD in children during the early stages, thereby streamlining the diagnosis process. Based on our findings, LR demonstrated the highest accuracy for the selected dataset

Synthesis and crystal structure of piperidinyl propanenitrile towards the preparation of piperidine based bioactive films for drug delivery applications.

Compounds containing the piperidine group are highly attractive as building blocks for designing new drugs. Functionalized piperidines are of significant interest due to their prevalence in the pharmaceutical field. Herein, 3-oxo-3-(piperidin-1-yl) propanenitrile has been synthesized, and piperidine-based sodium alginate/poly(vinyl alcohol) films have been prepared. The polymeric films display potency and potential for application to fight against microbial infections. The films could also help maintain interaction with tissue to ensure the controlled release of therapeutic molecules. Thus, they are promising in developing drug delivery systems essential in the pharmaceutical industry. The structure of the 3-oxo-3-(piperidin-1-yl)propanenitrile was confirmed via spectroscopic and single crystal x-ray diffraction techniques. A homogenous solution of sodium alginate (SA) was used to prepare the film by the casting method in the presence of poly(vinyl alcohol) (PVA) and 3-oxo-3-(piperidin-1-yl)propanenitrile (PPN). The prepared films were characterized physiochemically via FTIR, XRD, and TGA. The film morphology was studied using SEM. The antimicrobial potency of the prepared films was assessed against various species of microorganisms. The physicochemical analysis indicated that the films were bound by chemical and physical bond formation between the cyano group of 3-oxo-3-(piperidin-1-yl)propanenitrile, methylene group of PVA, and the hydroxyl group of SA. The films showed smooth, homogenous surfaces and good mechanical properties. The results revealed that the films are bioactive, as indicated by promising antimicrobial potency against P. aeruginosa, S. aureus, E. coli, B. subtilis, and C. albicans, with high potency as well as moderate activity against A. niger. Polymeric films have promising potential to be utilized in drug delivery applications. [Abstract copyright: © 2025. The Author(s).

Gamma radiation effects on vitamins, antioxidant, internal and molecular structure of Purslane seeds

Purslane contains the highest amount of omega-3 fatty acids, antioxidants, and has better nutritional quality. Gamma irradiation is harmless and dependable method for refining the shelf life and nutritional quality of the stored seeds. The aim of this research is to study the influence of irradiation by gamma on structure, ascorbic acid and phenolic content of Purslane seeds. The results show that, ascorbic acid, phenolic content, carbohydrate and protein content in Purslane seeds decreased after exposed by gamma rays. Super oxidase dismutase, fat and fiber content in Purslane seeds increased after exposed by gamma radiation. The shape, size, interconnection and arrangement of molecules in/or around benzene ring in Purslane cells changed after exposure to gamma radiation