151 research outputs found

    Učinak četiriju ljekovitih biljaka na proizvodnju, biokemijske pokazatelje u krvi i ilealnu mikrofloru u tovnih pilića.

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    This study was conducted with broilers to evaluate the effects of dietary supplementation of four medicinal plants on the performance, blood lipids and microflora population in the ileum. Three hundred and thirty-six dayold Ross broiler chicks were used in a completely randomized study with 6 treatments and 4 replicates each. The diets were iso-caloric and iso-nitrogenous and contained 15, 3, 2 and 2 g/kg of dried cumin, peppermint, yarrow and poley herbs, respectively. Two dietary treatments were considered the negative (containing no medicinal plant or antibiotic) and positive (containing Flavomycin at 0.4 g/kg) control groups. Flavomycin and peppermint supplementation to the diet increased the FI and BWG of the broiler chickens compared to the control (P<0.01). Dietary Flavomycin significantly increased body weight gain (BWG) in contrast to the other dietary treatments (P<0.05). Peppermint and cumin supplementation to the diet increased the BWG of the broiler chickens, whereas dietary poley and yarrow significantly reduced the BWG and increased feed conversion ratio (FCR) when compared with broilers fed the negative control diet (P<0.05). Dietary Flavomycin and peppermint increased the concentration of triglycerides (TG), low density lipoprotein (LDL) and total cholesterol in serum (P<0.05). Addition of Flavomycin or peppermint to the diet significantly reduced the ileal Bifidobacteria and Clostridia (P<0.05). In conclusion, under the conditions of this study, peppermint improved growth performance and adding it to the diet could be an alternative to the use of antibiotics as growth promoters in poultry production.Istraživanje je poduzeto s ciljem da se procijene učinci dodatka u hranu četiriju biljaka od medicinskog značenja na proizvodnju, sadržaj lipida u krvi i mikrofloru u ileumu. U pokus je bilo uzeto 336 jednodnevnih tovnih pilića linije Ross, nasumce raspoređenih, od kojih je svaki prošao šest tretmana s četiri ponavljanja. Hrana je bila jednake kalorične vrijednosti i dušičnog sastava, a sadržavala je 15 g/kg suhog kumina, 3 g/kg peperminta, 2 g/kg stolisnika i 2 g/kg biljke dubačac. Dva pripravka hrane smatrana su negativnima (nisusadržavala ljekovito bilje ili antibiotike) i pozitivnima (sadržavali su flavomicin 0,4 g/kg). Dodatak flavomicina i peperminta hrani povećao je unos hrane i prirast tjelesne mase tovnih pilića u usporedbi s kontrolom (P<0,01). Dodatak flavomicina značajno je povećao prirast tjelesne mase u odnosu na dodatak drugih biljaka (P<0,05). Dodatkom peperminta i kumina u hranu također se povećala tjelesna masa tovnih pilića, dok su dubačac i stolisnik značajno smanjili tjelesnu masu i povećali omjer konverzije hrane u usporedbi s kontrolnim pilićima (P<0,05). Flavocin i pepermint u hrani povećali su koncentraciju triglicerida, lipoproteina niske gustoće i ukupnog kolesterola u serumu (P<0,05). Dodavanje flavocina ili peperminta u hranu, značajno je smanjilo količinu ilealnih Bifidobacteria i Clostridia (P<0,05). Može se zaključiti da je pepermint pojačao rast tovnih pilića te da njegovo dodavanje hrani može biti zamjena za antibiotike kao promotore rasta u proizvodnji peradi

    Optimizing linear alkyl benzene sulfonate removal using fenton oxidation process in taguchi method

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    Linear alkyl benzene sulfonate (LAS), which is the most common used anionic surfactant in detergents manufacturing, can discharge onto water resources through wastewater and causes change in taste and odor, disruption in water treatment processes, aquatics death, and oxygen transfer limitation. Accordingly, this article investigates to optimize LAS removal using Fenton oxidation process in Taguchi Method for the first time. LAS removal using Fenton oxidation was perused experimentally in a lab-scale reactor

    Drug ranking using machine learning systematically predicts the efficacy of anti-cancer drugs

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    Artificial intelligence and machine learning (ML) promise to transform cancer therapies by accurately predicting the most appropriate therapies to treat individual patients. Here, we present an approach, named Drug Ranking Using ML (DRUML), which uses omics data to produce ordered lists of >400 drugs based on their anti-proliferative efficacy in cancer cells. To reduce noise and increase predictive robustness, instead of individual features, DRUML uses internally normalized distance metrics of drug response as features for ML model generation. DRUML is trained using in-house proteomics and phosphoproteomics data derived from 48 cell lines, and it is verified with data comprised of 53 cellular models from 12 independent laboratories. We show that DRUML predicts drug responses in independent verification datasets with low error (mean squared error < 0.1 and mean Spearman’s rank 0.7). In addition, we demonstrate that DRUML predictions of cytarabine sensitivity in clinical leukemia samples are prognostic of patient survival (Log rank p < 0.005). Our results indicate that DRUML accurately ranks anti-cancer drugs by their efficacy across a wide range of pathologies

    6G Positioning and Sensing Through the Lens of Sustainability, Inclusiveness, and Trustworthiness

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    6G promises a paradigm shift in which positioning and sensing are inherently integrated, enhancing not only the communication performance but also enabling location- and context-aware services. Historically, positioning and sensing have been viewed through the lens of cost and performance trade-offs, implying an escalated demand for resources, such as radio, physical, and computational resources, for improved performance. However, 6G goes beyond this traditional perspective to encompass a set of broader values, namely sustainability, inclusiveness, and trustworthiness. This paper aims to: (i) shed light on these important value indicators and their relationship with the conventional key performance indicators, and (ii) unveil the dual nature of 6G in relation to these key value indicators (i.e., ensuring operation according to the values and enabling services that affect the values)
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