The Effect of Feeding Acidifier and Probiotics with Different Levels in The Diet Growth on Broiler Performance

This research which aims to determine the effect of probiotic and Acidifier supplementations in the fermentation diet on growth of broiler has done in Takengon, Central Aceh District from August until October 2020. This research used 160 chicks strain Cobb 89 produced by PT. Charoen Pokphand. This study used a complete randomized design consisting of 4 treatments and 4 replications. The treatment of probiotic and Acidifier supplementations were: 0% (A), 0.1% (B), 0.2%(C), 0.3%(D). Parameters observed were achievement of final weight, weight gain, feed consumption, feed conversion, and feed efficiency. Data was analyzed by analysis of variance (ANOVA) and continued by Duncan Multiple Range Test if significant effect was detected. The result showed that the differences in supplementation of probiotic and Acidifiers effected significantly (P <0.05) on the final weight, weight gain, feed conversion and feed efficiency. However, there was no significant effect on rate of consumption. The result of present study showed that the combination of probiotic and Acidifier had a best impact on broiler growth and it was also decreased mortality of chicken.

Gravimetric study and statistical data on the symbiotic effect of organic intermixtures on corrosion inhibition of P4 mold steel

The corrosion protection properties of the intermixed of l-leucine and vanillin (LLVL) on P4 mold steel within 1.5 M H2SO4 and HCl media was studied by weight loss analysis. Calculated data revealed the inhibition effect of the intermixed compound performed poorly at low H2SO4 concentrations due to inability of the combined inhibitor molecules to aggregate and effectively hinder the dispersion of the destructive anions to the steel surface. The inhibition efficiency decreased significantly with time to values below effective inhibitor performance. However, from mid to optimum concentration, inhibition efficiency of the compound was generally stable with time with values generally above 85%. In HCl media, the inhibition efficiency of the intermixture was generally above 80% at all concentrations with respect to the inspection time. The inhibitor compound exhibited greater stability in HCl compared to H2SO4 solution. Calculated values of standard deviation in H2SO4 were broadly greater than the outputs received in HCl due to the degree of variation between LLVL inhibition efficiency values. The margin of error at 95% confidence shows 65% of LLVL inhibition efficiency values obtained in H2SO4 solution have values above 70% inhibition efficiency with margin of error at +12.07% while in HCl solution, 100% of the LLVL inhibition efficiency data obtained is above 70% with margin of error of +1%. Analysis of variance showed the statistical relevance of inhibition efficiency in H2SO4 and HCl solution is significantly higher the corresponding relevance for inspection time with values of 70.45% and 71.18%.

Role of artificial intelligence in cloud computing, IoT and SDN: Reliability and scalability issues

Information technology fields are now more dominated by artificial intelligence, as it is playing a key role in terms of providing better services. The inherent strengths of artificial intelligence are driving the companies into a modern, decisive, secure, and insight-driven arena to address the current and future challenges. The key technologies like cloud, internet of things (IoT), and software-defined networking (SDN) are emerging as future applications and rendering benefits to the society. Integrating artificial intelligence with these innovations with scalability brings beneficiaries to the next level of efficiency. Data generated from the heterogeneous devices are received, exchanged, stored, managed, and analyzed to automate and improve the performance of the overall system and be more reliable. Although these new technologies are not free of their limitations, nevertheless, the synthesis of technologies has been challenged and has put forth many challenges in terms of scalability and reliability. Therefore, this paper discusses the role of artificial intelligence (AI) along with issues and opportunities confronting all communities for incorporating the integration of these technologies in terms of reliability and scalability. This paper puts forward the future directions related to scalability and reliability concerns during the integration of the above-mentioned technologies and enable the researchers to address the current research gaps.

Analisis Limpasan Langsung Metode SCS Menggunakan Data Hujan TRMM Studi Kasus Subdas Code Hulu

Ketersediaan data menjadi hal yang krusial dalam analisis hidrologi. Banyak permasalahan menyangkut ketersediaan data yang seringkali ditemui di lapangan, seperti minimnya data, data yang tidak kontinyu, atau sebaran stasiun yang tidak merata. Seiring berkembangnya teknologi, permasalahan tersebut dapat diselesaikan dengan memanfaatkan data pengamatan satelit yang memiliki resolusi spasial dan temporal tinggi, cakupan luas, akses cepat, dan ekonomis. Akan tetapi, data satelit perlu divalidasi dengan data pengamatan nyata di lapangan. Penelitian ini dilakukan untuk validasi data satelit TRMM terhadap data observasi berbasis darat dengan membandingkan debit limpasan dari data hujan terukur di darat atau ARR (Automatic Rainfall Recorder) dengan data hujan TRMM, lalu dikoreksi dengan debit limpasan terukur di stasiun AWLR (Automatic Water Level Recorder) Gemawang. Debit limpasan dari hujan dihitung dengan menggunakan Metode SCS. Hasil penelitian menunjukan jeda waktu rata-rata pengukuran hujan TRMM dan ARR sekitar 8,5 jam. Ditemukan perbedaan bentuk hidrograf limpasanTRMM. Pada data 18 Januari 2018, terdapat kesalahan bentuk gelombang hidrograf (Ew) sebesar 11.843. Dari analisis indeks kesesuaian dan efisiensi, data satelit TRMM mendapat hasil koefisien korelasi rata-rata debit ARR-AWLR dan TRMM-AWLR tergolong rendah yaitu masing-masing sebesar 0,2416 dan 0,1041, sedangkan koefisien efisiensinya 1,67 yang dikategorikan sebagai data yang efisien. Availability of sufficient data as input data is important. Data availability tends to have several data problems, such as the lack of data availability, incomplete data, or the number of stations that are less scattered. As the development of the technology problems, those probelms can be solved by replacing ground-based observation data with satellite observations that have high spatial and temporal resolution, wide area coverage, fast access, and economics. This research was conducted to validate and correct TRMM satellite data on observation data at the AWLR Gemawang station with the SCS Method. The results of this study showed a delay in the average measurements of satellite rainfall and surface approximately 8.5 hours based on the data analysis used in this study. The results of the model error analysis can be concluded that TRMM rainfall data can be used in these needs. However, there is still an error in the TRMM data, which is on the data of January 18, 2018 which results in a hydrograph (Ew) waveform error of 11.843. From the conformity index and efficiency analysis, TRMM satellite data gets the correlation coefficient average ARR-AWLR debit of 0,2416 which is categorized as low efficiency data and TRMM-AWLR of 0,1041 which is categorized as quite low coefficient data, while the efficiency coefficient gets an average value 1,67 which is categorized as highly efficient optimization data.Availability of sufficient data as input data is important. Data availability tends to have several data problems, such as the lack of data availability, incomplete data, or the number of stations that are less scattered. As the development of the technology problems, those probelms can be solved by replacing ground-based observation data with satellite observations that have high spatial and temporal resolution, wide area coverage, fast access, and economics. This research was conducted to validate and correct TRMM satellite data on observation data at the AWLR Gemawang station with the SCS Method. The results of this study showed a delay in the average measurements of satellite rainfall and surface approximately 8.5 hours based on the data analysis used in this study. The results of the model error analysis can be concluded that TRMM rainfall data can be used in these needs. However, there is still an error in the TRMM data, which is on the data of January 18, 2018 which results in a hydrograph (Ew) waveform error of 11.843. From the conformity index and efficiency analysis, TRMM satellite data gets the correlation coefficient average ARR-AWLR debit of 0,2416 which is categorized as low efficiency data and TRMM-AWLR of 0,1041 which is categorized as quite low coefficient data, while the efficiency coefficient gets an average value 1,67 which is categorized as highly efficient optimization data.

Allocation Efficiency of Higher Education Resources in China

This paper uses the super-efficiency data envelopment analysis (DEA) model to measure the higher education resource allocation efficiency (HERAE) of 30 provinces from China 2005-2018, and analyzes the regional difference and dynamic evolution law of the HERAE with Theil index and kernel density estimation, respectively. The results show that: The HERAEs of most provinces are DEA effective, but the HERAEs of a few provinces are DEA ineffective, calling for further improvement to the allocation of higher education resources in these places. There was a certain difference in the HERAE trend between eastern, central, and western regions. In the sample period, eastern region had higher HERAE than central and western regions. With the elapse of time, the internal gap of HERAE decreased to different degrees in the three regions. Eastern region had the largest gap, followed in turn by central and western regions. In addition, China’s HERAEs were polarized in time. With the passage of time, the polarization of regional HERAEs slowly weakened.

Kapasitas Bioadsorpsi Bakteri Simbiosis Spons Laut Terhadap Kontaminan Logam Berat

Heavy metal pollution in the marine environment is quite high. Arsenic and Mercury are two types of dangerous heavy metals because they are toxic and are often found as components of pollution. The research objective was to determine the bio-absorption capacity and efficiency of sponge symbiotic bacteria against arsenic and mercury contaminants. The bio-absorbent material was used by two bacterial isolates, namely Bacillus licheniformis strain ATCC 9789 (Bl.6), the sponge symbiont Auletta Sp and Acinetobacter calcoaceticus strain PHCDB14 (Ac.8), the sponge symbiont Callyspongia aerizusa. The isolates were prepared through culture, then incubated 2 x 24 hours, suspension Bl.6 and Ac.8 were made, then adapted for 24 hours. Interaction with As3 + and Hg2 + contaminants with a concentration of 100 ppm in vials with time variations 0, 4, 8, 12, 16 days. The resulting interactions are extracted, concentrated, and acidified. The bio-absorption capacity and efficiency were determined based on absorption data using Atomic Absorption Spectrometry (AAS). The average efficiency of the bio-absorption of isolate Bl.6 against As3+ = 99.95%, Hg2+ = 88.49%, while isolate Ac.8 against As3+ = 99.95% and Hg2+ = 85.73%. Based on efficiency data, capacity and bio-absorption power relative to Bl.6 = Ac.8 against As3+ and Bl.6 ≥ Ac.8 contaminants to Hg2+. Isolates Bl.6 and Ac.8 adsorbed more strongly against As3+ contaminants than Hg2+.

Diffraction Grating Groove Metrology Using AFM & STM

AFM & STM metrology has been around for a long time, and especially intense since it has been awarded by the Nobel Prize in Physics in 1986. Since then, many AFM & STM groove profile measurements on surface relief diffraction gratings have been presented. However, a wide review of the results of the use of AFM & STM methods for groove metrology of various surface relief gratings has not really been undertaken. The following problems are discussed in this chapter: the cantilever tip deconvolution, geometry, and radius; groove shapes and abrupt groove slopes; roughness; PSD functions; etc. Also, the author demonstrates comparisons with other widely-used metrology techniques and examples of AFM & STM data of bulk, coated, and multilayer-coated ruled, or holographic, or lithographic gratings having realistic groove profiles. These gratings were chosen because high quality efficiency data exists, in particular, for space gratings or/and X-ray gratings characterized by synchrotron radiation sources; and their groove profiles, together with random nanoroughness, were measured by AFM or STM to be included in rigorous efficiency and scattered light intensity calculus. In the present chapter, both the earlier published results and the recent, non-published yet results are described and discussed.