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Ammonia (NH 3 ) is a key precursor of secondary inorganic aerosols. During precipitation, NH 3 in the atmosphere can be captured by rain and converted to NH 4 + , whereas during evaporation, NH 4 + can become NH 3 and be released again. The northeastern region of China experiences diverse precipitation types, making the study of the NH 3 release flux and its influencing factors during evaporation highly significant. In this study, precipitation samples of haze (HZ), dust (DS), convective (CC), and monsoon (MN) events were collected three times in Changchun from March to September 2024 (a total of twelve rain events), and indoor simulation evaporation experiments were conducted. The results revealed significant differences in the NH 4 + conversion rate ( R ), NH 3 release flux ( F ) and release rate ( V ) across the precipitation types ( P  < 0.05). The NH 3 flux released from precipitation evaporation was 20.33 µg/m 2 in spring and 64.53 µg/m 2 in summer, accounting for approximately 4.14% and 7.70%, respectively, of the corresponding atmospheric NH 3 concentrations. Meteorological factors influenced NH 3 release similarly across precipitation types. R peaked and then decreased with increasing temperature and was significantly negatively correlated with wind speed and precipitation amount ( P  < 0.05). In addition, this study calculates the temperature coefficient ( K 1 ), wind speed coefficient ( K 2 ), and precipitation amount coefficient ( K 3 ) by considering these factors. These findings provide valuable insights for estimating NH 3 release fluxes from precipitation evaporation in different regions.

The objective of this work was to evaluate the effect of semi-purified glycerin added to the feed of pregnant and lactating sows on performance including dorsal diameter, body condition, daily weight gain, feed intake, and feed conversion rate. Growth and feeding parameters were evaluated in born piglets: litter average, survival, daily weight gain, feed conversion rate, and daily milk consumption. Pregnant sows (n = 60; initial weight 180 ± 22 kg) were randomly assigned to the Control or Glycerin group (2%). Semi-purified glycerin was supplied from the beginning of gestation until farrowing. The inclusion of semi-purified glycerin did not affect any of the parameters evaluated in sows during gestation. The inclusion of semi-purified glycerin had a significant effect (p = 0.04) on the body condition of sows at weaning and appeared to have a negative effect on piglet survival. However, semi-purified glycerin caused no negative effects on milk production during lactation and did not affect piglet performance parameters. The addition of semi-purified glycerin as a caloric source could be an economically viable alternative to be implemented in feeding pregnant and lactating sows. However, additional tests are suggested.

The widespread adoption of high speed Internet access and it’s usage for everyday tasks are causing profound changes in users’ expectations in terms of Web site performance and reliability. At the same time, server management is living a period of changes with the emergence of the cloud computing paradigm that enables scaling server infrastructures within minutes. To help set performance objectives for maximizing user satisfaction and sales, while minimizing the number of servers and their cost, we present a methodology to determine how user sales are affected as response time increases. We begin with the characterization of more than 6 months of Web performance measurements, followed by the study of how the fraction of buyers in the workload is higher at peak traffic times, to then build a model of sales through a learning process using a 5-year sales dataset. Finally, we present our evaluation of high response time on users for popular applications found in the Web.

Interlocus gene conversion occurs such that a certain length of DNA fragment is non-reciprocally transferred (copied and pasted) between paralogous regions. To understand the rate and tract length of gene conversion, there are two major approaches. One is based on mutation-accumulation experiments, and the other uses natural DNA sequence variation. In this review, we overview the two major approaches and discuss their advantages and disadvantages. In addition, to demonstrate the importance of statistical analysis of empirical and evolutionary data for estimating tract length, we apply a maximum likelihood method to several data sets.

The present study was aimed to investigate the polymorphism of the myostatin gene and its relation with some growth traits,included feed conversion rate and efficiency, protein intake and protein efficiency ratio in 68 specimens of common carp Cyprinus carpio. Sequencing of single nucleotide polymorphism (SNP) showed three genotypes at site T2230C in the myostatin gene. The distribution rates were 5.88, 38.24 and 55.88% for TT, TC and CC respectively, and the variation among them was high significant, the allelic frequency was 0.25 for allele T, while it was 0.75 for C. Effect of the genotype of the myostatin gene was significantly in the feed conversion rate and efficiency, the protein intake and the protein efficiency ratio of the common carp with the variation of the genotypes of myostatin gene, whereas the feed conversion rate was 6.18 , 6.00 and 4.50 at TC , TT and CC respectively. Based on the mentioned results , the positive relation between myostatin gene polymorphism with some growth traits observed in this study may be a useful biomarker in the selection and crossing the genotypes that have achieved the best performance in common carp .

The phenomenon of sponsored search advertising—where advertisers pay a fee to Internet search engines to be displayed alongside organic (nonsponsored) Web search results—is gaining ground as the largest source of revenues for search engines. Using a unique six-month panel data set of several hundred keywords collected from a large nationwide retailer that advertises on Google, we empirically model the relationship between different sponsored search metrics such as click-through rates, conversion rates, cost per click, and ranking of advertisements. Our paper proposes a novel framework to better understand the factors that drive differences in these metrics. We use a hierarchical Bayesian modeling framework and estimate the model using Markov Chain Monte Carlo methods. Using a simultaneous equations model, we quantify the relationship between various keyword characteristics, position of the advertisement, and the landing page quality score on consumer search and purchase behavior as well as on advertiser's cost per click and the search engine's ranking decision. Specifically, we find that the monetary value of a click is not uniform across all positions because conversion rates are highest at the top and decrease with rank as one goes down the search engine results page. Though search engines take into account the current period's bid as well as prior click-through rates before deciding the final rank of an advertisement in the current period, the current bid has a larger effect than prior click-through rates. We also find that an increase in landing page quality scores is associated with an increase in conversion rates and a decrease in advertiser's cost per click. Furthermore, our analysis shows that keywords that have more prominent positions on the search engine results page, and thus experience higher click-through or conversion rates, are not necessarily the most profitable ones—profits are often higher at the middle positions than at the top or the bottom ones. Besides providing managerial insights into search engine advertising, these results shed light on some key assumptions made in the theoretical modeling literature in sponsored search.

Recruitment for clinical trials continues to be a challenge, as patient recruitment is the single biggest cause of trial delays. Around 80% of trials fail to meet the initial enrollment target and timeline, and these delays can result in lost revenue of as much as US $8 million per day for drug developing companies. This study aimed to conduct a systematic review and meta-analysis examining the effectiveness of online recruitment of participants for clinical trials compared with traditional in-clinic/offline recruitment methods. Data on recruitment rates (the average number of patients enrolled in the study per month and per day of active recruitment) and conversion rates (the percentage of participants screened who proceed to enroll into the clinical trial), as well as study characteristics and patient demographics were collected from the included studies. Differences in online and offline recruitment rates and conversion rates were examined using random effects models. Further, a nonparametric paired Wilcoxon test was used for additional analysis on the cost-effectiveness of online patient recruitment. All data analyses were conducted in R language, and P<.05 was considered significant. In total, 3861 articles were screened for inclusion. Of these, 61 studies were included in the review, and 23 of these were further included in the meta-analysis. We found online recruitment to be significantly more effective with respect to the recruitment rate for active days of recruitment, where 100% (7/7) of the studies included had a better online recruitment rate compared with offline recruitment (incidence rate ratio [IRR] 4.17, P=.04). When examining the entire recruitment period in months we found that 52% (12/23) of the studies had a better online recruitment rate compared with the offline recruitment rate (IRR 1.11, P=.71). For cost-effectiveness, we found that online recruitment had a significantly lower cost per enrollee compared with offline recruitment (US $72 vs US $199, P=.04). Finally, we found that 69% (9/13) of studies had significantly better offline conversion rates compared with online conversion rates (risk ratio 0.8, P=.02). Targeting potential participants using online remedies is an effective approach for patient recruitment for clinical research. Online recruitment was both superior in regard to time efficiency and cost-effectiveness compared with offline recruitment. In contrast, offline recruitment outperformed online recruitment with respect to conversion rate.

Objective: The aim of the present study was to report our single-center initial experience in laparoscopic radical prostatectomy (LRP) with special emphasis on the complications and collateral problems and their management. Material and methods: A total of 48 patients (mean age 64 years) underwent LRP in our institution between August 2014 and July 2018. Two surgeons completed a fellowship training program for LRP before. Mentored operations started after the first 10 cases. The patients were divided in two groups of 30 (group I) and 18 (group II) patients. Demographic, preoperative, peroperative, and postoperative data were collected prospectively. Anesthesiology and nurses’ team performances, as well as problems and their management, were reviewed. Results: The demographic data for both groups (group I vs. group II) were similar. Estimated blood loss (695.5±139.23 vs. 398±339.39 mL) and intraoperative complication rates (36.66% vs. 5.55%) were significantly (p<0.05) higher in group I. Conversion to open surgery occurred in 7 (20%) patients in group I and in 1 (5.55%) patient in group II. Continence rates at 12 (83%) months were similar in both groups. Positive surgical margins were 8.33% for pT2 and 27.1% for pT3 stages. Conclusion: A validated fellowship program before starting LRP and performing the first cases under mentorship are helpful. The complication and conversion rates decrease after 30 cases in addition to the improved experience also with improved cooperation with the anesthesiologist and scrub nurse. Cite this article as: Akdere H, Aktoz T, Arıkan MG, Atakan İH, Veneziano D, Gözen AS. Embarking with laparoscopic radical prostatectomy and dealing with the complications and collateral problems: A single-center experience. Turk J Urol 2020; 46(1): 37-43.

Customers increasingly rely on other consumers' reviews to make purchase decisions online. New insights into the customer review phenomenon can be derived from studying the semantic content and style properties of verbatim customer reviews to examine their influence on online retail sites' conversion rates. The authors employ text mining to extract changes in affective content and linguistic style properties of customer book reviews on Amazon. com. A dynamic panel data model reveals that the influence of positive affective content on conversion rates is asymmetrical, such that greater increases in positive affective content in customer reviews have a smaller effect on subsequent increases in conversion rate. No such tapering-off effect occurs for changes in negative affective content in reviews. Furthermore, positive changes in affective cues and increasing congruence with the product interest group's typical linguistic style directly and conjointly increase conversion rates. These findings suggest that managers should identify and promote the most influential reviews in a given product category, provide instructions to stimulate reviewers to write powerful reviews, and adapt the style of their own editorial reviews to the relevant product category.

The phenomenon of paid search advertising has now become the most predominant form of online advertising in the marketing world. However, we have little understanding of the impact of search engine advertising on consumers' responses in the presence of organic listings of the same firms. In this paper, we model and estimate the interrelationship between organic search listings and paid search advertisements. We use a unique panel data set based on aggregate consumer response to several hundred keywords over a three-month period collected from a major nationwide retailer store chain that advertises on Google. In particular, we focus on understanding whether the presence of organic listings on a search engine is associated with a positive, a negative, or no effect on the click-through rates of paid search advertisements, and vice versa for a given firm. We first build an integrated model to estimate the relationship between different metrics such as search volume, click-through rates, conversion rates, cost per click, and keyword ranks. A hierarchical Bayesian modeling framework is used and the model is estimated using Markov chain Monte Carlo methods. Our empirical findings suggest that click-throughs on organic listings have a positive interdependence with click-throughs on paid listings, and vice versa. We also find that this positive interdependence is asymmetric such that the impact of organic clicks on increases in utility from paid clicks is 3.5 times stronger than the impact of paid clicks on increases in utility from organic clicks. Using counterfactual experiments, we show that on an average this positive interdependence leads to an increase in expected profits for the firm ranging from 4.2% to 6.15% when compared to profits in the absence of this interdependence. To further validate our empirical results, we also conduct and present the results from a controlled field experiment. This experiment shows that total click-through rates, conversions rates, and revenues in the presence of both paid and organic search listings are significantly higher than those in the absence of paid search advertisements. The results predicted by the econometric model are also corroborated in this field experiment, which suggests a causal interpretation to the positive interdependence between paid and organic search listings. Given the increased spending on search engine-based advertising, our analysis provides critical insights to managers in both traditional and Internet firms.