3D Baskı ile Hızlı Prototip ve Son Ürün Üretimi

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Bounds on non-linear errors for variance computation with stochastic rounding *

The main objective of this work is to investigate non-linear errors and pairwise summation using stochastic rounding (SR) in variance computation algorithms. We estimate the forward error of computations under SR through two methods: the first is based on a bound of the variance and Bienaym{\'e}-Chebyshev inequality, while the second is based on martingales and Azuma-Hoeffding inequality. The study shows that for pairwise summation, using SR results in a probabilistic bound of the forward error proportional to log(n)u rather than the deterministic bound in O(log(n)u) when using the default rounding mode. We examine two algorithms that compute the variance, called ''textbook'' and ''two-pass'', which both exhibit non-linear errors. Using the two methods mentioned above, we show that these algorithms' forward errors have probabilistic bounds under SR in O(\sqrt nu) instead of nu for the deterministic bounds. We show that this advantage holds using pairwise summation for both textbook and two-pass, with probabilistic bounds of the forward error proportional to log(n)u

COVID-19 Pandemi Sırasındaki Acil Cerrahi Bakım ve Ameliyathane Uygulamalarında Perioperatif Uygulama ve Rehberlik; Deneyimlerimiz

Aim: The novel coronavirus SARS-CoV-2 (COVID-19) can infect healthcare workers. We developed an institutional algorithm to protect operating room team members during the COVID-19 pandemic and rationally conserve personal protective equipment (PPE). We aimed to review the latest data on the COVID-19 pandemic and essential information for practice in emergency surgery and the operating room.Materials and Methods: An interventional platform (operating room, interventional suite, and endoscopy) with our committee formed with our doctors consisting of different branches, we developed our guidelines based on potential patterns of spread, risk of exposure, and conservation of PPE. We aimed to share our experiences with 128 patients who were taken into operation in a 2-month period.Anesthetic management and infection control guidelines for emergency procedures for patients with suspected 2019-nCoV were drafted and applied in Medical Faculty of Namık Kemal University.Results: A decision tree algorithm describing our institutional guidelines for precautions for operating room team members was created. This algorithm is based on the urgency of operation, anticipated viral burden at the surgical site, the opportunity for a procedure to aerosolize virus, and the likelihood a patient could be infected based on symptoms and testing.Conclusion: Despite COVID-19 being a new threat, we have shown that by developing an easy-to-follow decision algorithm for the interventional platform teams, we can ensure optimal healthcare worker safety.Amaç: Yeni koronavirüs SARS-CoV-2 (COVID-19) sağlık çalışanlarını enfekte edebilir. COVID-19 salgını sırasında ameliyathane ekip üyelerini korumak ve rasyonel olarak kişisel koruyucu ekipman (KKE) için kurumsal bir algoritma geliştirdik. Acil cerrahi ve ameliyathanede COVID-19 salgını ile ilgili en güncel bilgileri gözden geçirmeyi amaçladık. Materyal ve Metot: Farklı branşlardan oluşan doktorlarımızla oluşturduğumuz komitemiz ile girişimsel bir platform (ameliyathane, girişimsel ve endoskopi), potansiyel yayılma örüntüleri, maruz kalma riski ve KKE'nin korunmasına dayanan kılavuzlarımızı geliştirdik. Deneyimlerimizi 2 aylık bir sürede ameliyat edilen 128 hasta ile paylaşmayı amaçladık. 2019-nCoV şüphesi olan hastalar için acil durum prosedürleri için anestezi yönetimi ve enfeksiyon kontrol kılavuzları Namık Kemal Üniversitesi Tıp Fakültesi'nde hazırlanmış ve uygulanmıştır. Bulgular: Ameliyathane ekibi üyelerine yönelik önlemler için kurumsal yönergelerimizi açıklayan bir karar algoritması oluşturuldu. Bu algoritma ameliyatın aciliyetine, cerrahi bölgede beklenen viral yüke, virüsü aerosol haline getirme prosedürü fırsatına ve hastanın semptomlara ve testlere dayanarak enfekte olma olasılığına dayanır. Sonuç: COVID-19'un yeni bir tehdit olmasına rağmen, girişimsel platform ekipleri için izlemesi kolay bir karar algoritması geliştirerek, optimum sağlık çalışanı güvenliğini sağlayabildiğimizi gösterdik

Treatment of olive mill based wastewater by means of magnetic nanoparticles: Decolourization, dephenolization and COD removal

AbstractOlive mill wastewater (OMW) is an environmental concern that has been highlighted as a serious environmental problem in the Mediterranean basin countries because of its high organic load and phytotoxic and antibacterial phenolic compounds, which resist biological degradation. Consequently, this type of wastewater represents a huge challenge for the conventional wastewater treatment techniques as it can impact the lifetime of bacteria needed for the treatment. Iron-oxide nanoparticles are attractive for wastewater treatment for two important reasons. First, nanoparticles can remove pollutants from wastewater rapidly. Second, this magnetic type of nanoparticles could be separated easily using a magnet after finishing treatment process. In this study, we aimed at investigating the effectiveness of the magnetic iron oxide nanoparticles in the removal of large organic contaminants from OMW. Batch and continuous mode processes were applied on OMW treatment to determine the effect of contact time, solution pH, coexisting contaminants and the adsorption isotherm.The results showed that the adsorption was fast and the adsorption reached equilibrium within less than 30min. The adsorption equilibrium data fit very well to the Brunauer–Emmett–Teller (BET) Model, indicating multi-layers adsorption. The adsorption of major pollutants was associated to an efficient removal of coexisting contaminants such as heavy metals and free ions. The adsorption of OMW pollutants was dependent on pH of the solution. Finally, continuous-mode process was tested successfully using a packed bed column that combined sand filtration with magnetic nanoparticles to decolourize OMW effluent. This study will provide valuable insight on the effect of nanoparticles toward the treatment and recyclability of olive mill wastewater, which is crucial for the local olive mill industry. After seeing the successful achievement of integrating nanoparticles with fixed bed filtration, a preliminary process description and cost estimation of stand-alone plant (with a capacity of 4m3/h) for OMW treatment were considered in this study. Process capital and annual operating costs were estimated to be $12,306 and$476/year, respectively

Relating Spatial Patterns of Stream Metabolism to Distributions of Juveniles Salmonids at the River Network Scale

Understanding the factors that drive spatial patterns in stream ecosystem processes and the distribution of aquatic biota is important to effective management of these systems and the conservation of biota at the network scale. In this study, we conducted field surveys throughout an extensive river network in NE Oregon that supports diminishing populations of wild salmonids. We collected data on physical habitat, nutrient concentrations, biofilm standing stocks, stream metabolism (gross primary production [GPP] and ecosystem respiration [ER]), and ESA‐listed juvenile salmonid density from approximately 50 sites across two sub‐basins. Our goals were to (1) to evaluate network patterns in these metrics, and (2) determine network‐scale linkages among these metrics, thus providing inference of processes driving observed patterns. Ambient nitrate‐N and phosphate‐P concentrations were low across both sub‐basins (\u3c40 μg/L). Nitrate‐N decreased with watershed area in both sub‐basins, but phosphate‐P only decreased in one sub‐basin. These spatial patterns suggest co‐limitation in one sub‐basin but N limitation in the other; experimental results using nutrient diffusing substrates across both sub‐basins supported these predictions. Solar exposure, temperature, GPP, ER, and GPP:ER increased with watershed area, but biofilm Chl a and ash‐free dry mass (AFDM) did not. Spatial statistical network (SSN) models explained between 70% and 75% of the total variation in biofilm Chl a, AFDM, and GPP, but only 21% of the variation in ER. Temperature and nutrient concentrations were the most supported predictors of Chl aand AFDM standing stocks, but these variables explained little of the total variation compared to spatial autocorrelation. In contrast, solar exposure and temperature were the most supported variables explaining GPP, and these variables explained far more variation than autocorrelation. Solar exposure, temperature, and nutrient concentrations explained almost none of the variation in ER. Juvenile salmonids—a key management focus in these sub‐basins—were most abundant in cool stream sections where rates of GPP were low, suggesting temperature constraints on these species restrict their distribution to oligotrophic areas where energy production at the base of the food web may be limited

A Predictive Model for Steady State Ozone Concentration at an Urban-Coastal Site

Ground level ozone (O-3) plays an important role in controlling the oxidation budget in the boundary layer and thus affects the environment and causes severe health disorders. Ozone gas, being one of the well-known greenhouse gases, although present in small quantities, contributes to global warming. In this study, we present a predictive model for the steady-state ozone concentrations during daytime (13:00-17:00) and nighttime (01:00-05:00) at an urban coastal site. The model is based on a modified approach of the null cycle of O-3 and NOx and was evaluated against a one-year data-base of O-3 and nitrogen oxides (NO and NO2) measured at an urban coastal site in Jeddah, on the west coast of Saudi Arabia. The model for daytime concentrations was found to be linearly dependent on the concentration ratio of NO2 to NO whereas that for the nighttime period was suggested to be inversely proportional to NO2 concentrations. Knowing that reactions involved in tropospheric O-3 formation are very complex, this proposed model provides reasonable predictions for the daytime and nighttime concentrations. Since the current description of the model is solely based on the null cycle of O-3 and NOx, other precursors could be considered in future development of this model. This study will serve as basis for future studies that might introduce informing strategies to control ground level O-3 concentrations, as well as its precursors' emissions.Peer reviewe

A Predictive Model for Steady State Ozone Concentration at an Urban-Coastal Site

Ground level ozone (O3) plays an important role in controlling the oxidation budget in the boundary layer and thus affects the environment and causes severe health disorders. Ozone gas, being one of the well-known greenhouse gases, although present in small quantities, contributes to global warming. In this study, we present a predictive model for the steady-state ozone concentrations during daytime (13:00–17:00) and nighttime (01:00–05:00) at an urban coastal site. The model is based on a modified approach of the null cycle of O3 and NOx and was evaluated against a one-year data-base of O3 and nitrogen oxides (NO and NO2) measured at an urban coastal site in Jeddah, on the west coast of Saudi Arabia. The model for daytime concentrations was found to be linearly dependent on the concentration ratio of NO2 to NO whereas that for the nighttime period was suggested to be inversely proportional to NO2 concentrations. Knowing that reactions involved in tropospheric O3 formation are very complex, this proposed model provides reasonable predictions for the daytime and nighttime concentrations. Since the current description of the model is solely based on the null cycle of O3 and NOx, other precursors could be considered in future development of this model. This study will serve as basis for future studies that might introduce informing strategies to control ground level O3 concentrations, as well as its precursors’ emissions

A Predictive Model for Steady State Ozone Concentration at an Urban-Coastal Site

Ground level ozone (O3) plays an important role in controlling the oxidation budget in the boundary layer and thus affects the environment and causes severe health disorders. Ozone gas, being one of the well-known greenhouse gases, although present in small quantities, contributes to global warming. In this study, we present a predictive model for the steady-state ozone concentrations during daytime (13:00–17:00) and nighttime (01:00–05:00) at an urban coastal site. The model is based on a modified approach of the null cycle of O3 and NOx and was evaluated against a one-year data-base of O3 and nitrogen oxides (NO and NO2) measured at an urban coastal site in Jeddah, on the west coast of Saudi Arabia. The model for daytime concentrations was found to be linearly dependent on the concentration ratio of NO2 to NO whereas that for the nighttime period was suggested to be inversely proportional to NO2 concentrations. Knowing that reactions involved in tropospheric O3 formation are very complex, this proposed model provides reasonable predictions for the daytime and nighttime concentrations. Since the current description of the model is solely based on the null cycle of O3 and NOx, other precursors could be considered in future development of this model. This study will serve as basis for future studies that might introduce informing strategies to control ground level O3 concentrations, as well as its precursors’ emissions