Monthly Archives: November 2016

Despite normal cellular behaviors a separate

Despite normal cellular behaviors, a separate, structural phenotype was observed. In control embryos, retinal progenitors aligned with their neighbors, such that their apical and basal ends were in register with each other throughout the course of optic cup morphogenesis (Fig. 5A-F″). In this way, the retina maintained its pseudostratified monolayer structure prior to the onset of neurogenesis. In lama1UW1 mutant embryos, however, retinal progenitors failed to maintain apicobasal register: though promotion information were in register during the first part of optic cup morphogenesis, they appeared to sort into separate domains during invagination (Fig. 5G-L″). At the end of optic cup formation, marked retinal progenitors failed to span the width of the retina promotion information (Fig. 5L″). This may be better visualized when moving through a confocal z-stack of lama1UW1 control and mutant optic cups at 24 hpf (Movies S9, S10). In control embryos, retinal progenitor cells were oriented with their long axes pointing toward the lens (Fig. 1D, Movie S9). In contrast, in lama1UW1 mutant embryos, cells appeared to be organized into multiple domains; cells in some domains appeared to be oriented with their long axes not pointing toward the lens (Fig. 1H, Movie S10). Therefore, lama1 is required to maintain correct retinal structure and orientation of progenitor elongation through optic cup invagination, though it does not appear to be required for retinal progenitors to produce protrusive cell behaviors and elongate.
3.6. Apicobasal polarity is disrupted in lama1 mutants
Laminin has been demonstrated to be critical for establishing and maintaining epithelial polarity both in vitro and in vivo ( Martin-Belmonte and Mostov, 2008). At early stages of zebrafish optic vesicle evagination, ZO-1, a component of tight junctions, is localized to the apical surface, opposite the laminin staining that surrounds the optic vesicle (Ivanovitch et al., 2013). It was shown that during optic vesicle evagination, laminin is important for establishing apicobasal polarity: in the lamg1 mutant (sleepym86), ZO-1 was mislocalized to what should be the presumptive basal surface, in addition to the apparent apical surface (Ivanovitch et al., 2013). In that study, however, polarity was assayed specifically during optic vesicle evagination stages; it is unknown how epithelial polarity and structure might change throughout the process of optic cup morphogenesis in the presence or absence of laminin.
Therefore, we first assayed polarity at the completion of optic cup morphogenesis (24 hpf), in both lama1UW1 control and mutant embryos. To do this, antibody staining was performed for a marker of the apical surface, atypical protein kinase C (aPKC). We found that in control embryos, aPKC was localized to a single apical surface, at the interface between the neural retina and retinal pigmented epithelium (Fig. 6A, green arrowhead). In lama1UW1 mutant embryos, however, localization of aPKC was disrupted. Though polarity was disrupted with 100% penetrance, the exact number of apical domains present was variable (Fig. 6B-D): in addition to the correct apical domain (green arrowheads), multiple ectopic domains of aPKC localization were found (yellow arrowheads), as well as ectopic puncta (magenta asterisks). The ectopic domains and puncta were scattered throughout the retina. Similar results were obtained using an antibody against the tight junction protein ZO-1 (data not shown). These observations suggest that early defects in cell polarity that are caused by loss of laminin proteins may persist through optic cup morphogenesis, resulting in multiple, randomly positioned apical domains in the optic cup.
Fig. 6. Apicobasal polarity is disrupted from the earliest stages of optic vesicle morphogenesis. (A-D) Antibody staining for aPKC in control (A) and lama1UW1 mutant embryos (B-D) reveals disruption of polarity at 24 hpf. green arrowheads, correct apical domain. yellow arrowheads, ectopic apical domains. asterisks, ectopic puncta. (E-P) Single confocal sections from 4D datasets of apical domain dynamics (marked by pard3-GFP) in a lama1UW1 control embryo (E-J), or a mutant embryo (K-P). In lama1UW1 mutant embryos, pard3-GFP localization is disrupted similar to aPKC. dashed blue line marks outline of optic vesicle. green arrowheads, correct apical domain. yellow arrowheads, ectopic apical domains. Dorsal views; scale bar, 50 μm. A, anterior; P, posterior; M, medial; L, lateral.Figure optionsDownload full-size imageDownload high-quality image (1932 K)Download as PowerPoint slide

Expression patterns of both human

Expression patterns of both human and murine TRIM25 in different tissues have been investigated previously ( Inoue et al., 1993, Orimo et al., 1995uanduInoue et al., 1999). Because of the presence of estrogen-responsive elements and IFN-stimulated response elements, TRIM25 is predominantly expressed in estrogen-targeting tissues, including the mammary glands, placenta, and uterus. Additionally, it is highly expressed in immune-related tissues such as the spleen, lungs, and thymus ( Orimo et al., 1995, Inoue et al., 1999uanduShimada et al., 2004). In the present study, we showed that TRIM25 was also dramatically expressed in the chicken spleen, thymus, and lungs, suggesting that TRIM25 might play an imp###http://www.GDC-0941.COM/image/1-s2.0-S2213307016000058-gr2.jpg####ortant role in innate immune response in chickens.
NDV is a negative-strand RNA virus that causes significant economic losses to the poultry industry (Kapczynski et al., 2013). NDV is mainly recognized by RIG-I in human and murine cells, and TRIM25 functions as an important E3 ubiquitin ligase for the activation of RIG-I and the subsequent signaling transduction that leads to the production of IFNs (Kato et al., 2006, Gack et al., 2007uanduGack et al., 2009). Although RIG-I is absent in chickens (Barber et al., 2010), the expression of type I IFN, cytokines, and several IFN-stimulated genes is induced in the spleen, macrophages, inhibitor price fibroblasts, and splenic leukocytes of chickens infected with NDV (Munir et al., 2005, Ahmed et al., 2007uanduRue et al., 2011), indicating the presence of an unknown viral sensor that compensates for the absence of RIG-I. In this study, significantly increased TRIM25 expression was observed both in vitro and in vivo upon infection with NDV, suggesting a potentially antiviral role for TRIM25 in chickens. Due to the absence of RIG-I in chickens, the definite role of TRIM25 in the immune response to NDV is unclear. Recently, an increasing number of TRIM proteins have been found to be involved in modulating antiviral signaling pathways in mammals ( Ozato et al., 2008uanduKawai and Akira, 2011). For example, TRIM23-mediated interaction of the Lys27-linked polyubiquitin moiety with NF-?B essential modulator is essential for virus infection-triggered nuclear factor kappa B (NF-?B) and interferon regulator factor-3 (IRF3) activation (Arimoto et al., 2010). In contrast, TRIM21 negatively regulates the production of IFNs by interacting with both IRF3 and IRF7, thereby marking them for ubiquitination and degradation ( Higgs et al., 2008uanduHiggs et al., 2010). In addition, TRIM27 interacts with the IKK family of kinases and negatively regulates both NF-?B-mediated and IRF-mediated gene expression (Zha et al., 2006). Taken together, these results suggest that TRIM25 might function as a crucial protein in the detection of NDV or in modulating NDV-triggered antiviral signaling pathways in chickens.
The innate immune system is the first line of host defense against invading pathogens (Barbalat et al., 2011). Host cells express pattern-recognition receptors that detect pathogen-associated molecular patterns (PAMPs) and trigger the production of type I IFNs (Pichlmair and Reis e Sousa, 2007uanduTakeuchi and Akira, 2010). Poly(I:C) and poly(dA:dT) are synthetic analogs of viral nucleic acids that function as PAMPs and trigger antiviral signaling pathways in human and murine cells (Gitlin et al., 2006, Kato et al., 2006, Ablasser et al., 2009uanduChiu et al., 2009). Poly(I:C) induces IFN-β expression and is predominantly recognized by melanoma differentiation-associated protein 5 (MDA-5) in chicken cells ( Karpala et al., 2011, Liniger et al., 2014, Lee et al., 2012uanduHayashi et al., 2014). In agreement with the findings of previous studies, significant increases in the expression levels of chicken IFN-α and IFN-β were also observed in CEFs transfected with poly(I:C). Additionally, we observed that TRIM25 expression levels were significantly upregulated in CEFs transfected with poly(I:C), indicating the potential role of TRIM25 in dsRNA-triggered antiviral signaling pathways in chicken cells. Recently, it was reported that TRIM25 not only activates the K63-polyubiquitination of the RIG-I signaling pathway ( Gack et al., 2007), but also targets MAVS for ubiquitination and degradation after activating RIG-I and MDA-5, leading to the production of type I IFN (Castanier et al., 2012). Combined with the results of our study, this suggests that TRIM25 might also catalyze ubiquitination of MAVS and induce the expression of IFN-α and β in chicken cells, after the recognition of dsRNA by MDA-5. Furthermore, IFN-α and IFN-β expression was induced in CEFs transfected with poly(dA:dT). These results suggest the existence of potentially unknown DNA sensors in chickens that recognize poly(dA:dT) motifs. The up-regulation of TRIM25 expression in chicken cells transfected with poly(dA:dT) indicates the involvement of TRIM25 in the cells\’ response to ectogenic DNA, but the underlying mechanism is unclear. Recently, it was reported that TRIM56 and RNF5 deliver K63- and K48-linked polyubiquitination moieties that positively and negatively modulate the poly(dA:dT) recognition pathways in human cells ( Zhong et al., 2009uanduTsuchida et al., 2010). This indicates that TRIM25 also likely functions as an E3 ubiquitin ligase to modify dsDNA-induced antiviral signaling pathways in chicken cells. Moreover, in contrast to poly(I:C), the expression levels of TRIM25 and IFN-α/β showed a gradual increasing trend in chicken cells transfected with poly(dA:dT), suggesting that different antiviral pathways are employed by the cells in response to infection with RNA and DNA viruses. Further studies are needed to elucidate the molecular mechanisms by which chicken cells distinguish between RNA and DNA viruses.

Complete material failure is usually observed

Complete material failure is usually observed at the normal load around 100 mN for all three scratch directions (Fig. 5f, g, h). Small precursor cracks form before final material failure occurs. The cracks are curved and fibers can clearly be seen (Fig. 4 and Fig. 5). Fibers which have been pressed out are observed caudally in all scratches made.
3.3. Epicrates cenchria cenchria
Scratch width correlates with force for all three sliding directions (Fig. 8). With higher force, the scratches become slightly thicker. All three scratch directions have similar widths within one force category. Abrasion appearance differs for the most part between forces and scratch directions. Scratches were easily located for all forces. Material is plastically deformed and strongly ploughed to the sides and partly to the end of the scratch. Removal of material is partly observed (Fig. 8). The pronounced surface microstructure is bent or broken, and pressed to the sides of the scratch where it is compressed (Fig. 8 and Fig. 9). In the case of scratches made in the caudal and cranial direction, the microstructures are pressed down, bent apart and displaced to the sides (Figs. 8d and 9e-h). Structures within the cranial scratches exhibit damage (Figs. 8j and 9j-l). Along lateral scratches, the material is pushed towards the sides and the end of the scratch (Figs. 8p and 9m-p). In full article to L. g. californiae, there is an obvious bending of surface structure in the lateral direction. Cracks in the initial contact area are star-shaped for the scratches made in the caudal and cranial directions (Figs. 5, 8e, k and 9), and are formed laterally for the scratches made in the lateral direction ( Fig. 5 and Fig. 9). Cranial scratches lead to cracks running in a semi-circle in which the closed part points caudally. This may be due to the diamond tip pressing the material and structures towards the end of the scratch. In scratches made with 10 mN the structures are partly pressed downward, bent apart, and displaced to the sides (Fig. 8a and b), whereas in scratches made with 50 mN the material is damaged at the bending sites (Fig. 8c and d). Bending, deforming, and displacement of the material are more excessive for the 50 mN scratches and lead more quickly to damage (Fig. 8d, j, p). In 50% of the scratches made with 100 mN force, extensive material damage due to bending, breaking, and displacing of the material is exhibited for the caudal and cranial directions. In the other 50%, the scratches are thicker, but exhibit less material damage.
Fig. 8. Comparison of the scratches on the ventral scales of Epicrates cenchria cenchria in the caudal (↓), cranial (↑) and lateral (→) direction for the forces of 10 mN, 50 mN and 100 mN as indicated. Scale bars = 100 μm for the left column; 20 μm for the right column, except 30 μm in f. Arrows in b, d, f, g, j, k, m, o and q indicate the direction in which the scratch was made. Schematic diagrams of the wear on the right hand side: light grey: material is slightly flattened, grey: material is strongly flattened, dark grey: material is flattened. Abbreviations: be, bent; br, broken; c, cracks; de, deformed; dp, deplaced; pr, pressed out; str, structures.Figure optionsDownload full-size imageDownload as PowerPoint slide

These global steps are worked out

These global steps are worked out and discussed more detailed in Appendix C. Remark.
To the best of our knowledge, the presented algorithm, based on the exponential assumption, is new. A non-exponential extension, by using phase-type distributions, can be thought of and is certainly of interest from a mathematical point of view. But at this point in time it never is likely to become computationally expensive if not prohibitive. This will remain of interest for future research.
5. Real life measurements and computational results
To illustrate the use of our methods, we will provide some numerical results in this section. Data from a real life collection site has been used as a test case. This site is located in the Dutch city of Zwolle and handles over 30,000 donations annually. The data, gathered in 2012, leads to the parameter settings shown in Table 3. The service rates can be considered to be representative for collection sites never throughout the Netherlands.
Table 3.
Input data for test case.ParametervalueArrival rate, λ15.0 donors/hourService rate per staff member at phase 1, Registration, μ130.0 donors/hourStaff members (servers) at phase 1, s11Service rate per staff member at phase 2, Interview, μ210.2 donors/hourStaff members (servers) at phase 2, s22Service rate per staff member at phase 3, Collection, μ35.0 donors/hourStaff members (servers) at phase 3, s34Full-size tableTable optionsView in workspaceDownload as CSV
To illustrate the results more effectively, three extra scenarios were compared with the existing, basic scenario: Scenario 1: One extra staff member to phase 2.Scenario 2: One extra staff member to phase 3.Scenario 3: At the interview phase an Hb-test is performed. This test requires roughly 1 min. We can perform this test directly upon registration, changing μ1μ1 to 20, and μ2μ2 to 12.3.
5.2. Real life measurements and product form computations
Using the product form expression (1), in combination with Little’;s well-known law, we can directly compute the mean delay time by: equation(9)L=λT(Li=λTi(i=1,2,3)) where λArrival rate of donors(as mentioned before).LMean number of donors in the system(Li for stationi,i=1,2,3).TMean total delay time in the system(Ti for stationi,i=1,2,3). Note that a similar relation holds for the mean number of donors in the queue and the mean waiting time. It is also possible to directly calculate the expected waiting and delay time WiWi and TiTi for each phase ii separately. In Table 4, the waiting times that were calculated with the product form result (Theorem 1) are shown together with data from internal reports at Sanquin (Van den Toren et al. [24]). The presented data were collected throughout the Netherlands in 2010.
From Table 4 the conclusion can be drawn that the expected waiting times seem to validate quite well with the product form computation. All of the computed waiting times fall within the 95% Confidence Interval-and even the 30% Confidence Interval-of the corresponding real life measurements.

Fig Impact on cumulative response times amb

Fig. 19. Impact on cumulative response times (23 amb.)Figure optionsDownload full-size imageDownload as PowerPoint slide
4.4. Impact on workload balance
The coefficient of variation (CV), which is the ratio of the standard deviation of how busy ambulances are and the average busy probability, is used to calculate workload balance [38]. The larger the CV the more variation there is among the different ambulances deployed, hence less workload balance among the crews. Table A.4 in the Appendix shows the results of an analysis of variance on the CV for the ambulances. We can see that pop over to this website while the day and time of the week and number of ambulances are statistically significant (p<0.05)(p<0.05), the kind of objective used is not statistically significant.
Fig. 20 shows the average CV for the three different objectives for varying fleet size (20, 21, 22 and 23 ambulances). Here we observe that the Minimum Average Response objective has the highest CV for 20 and 21 servers, and then declines quite sharply for 22 and 23 servers. In Fig. 21, Fig. 22, Fig. 23 and Fig. 24 we show that there is a high degree of fluctuation between the three different objectives during different day and times of the week.
Fig. 20. Impact of fleet size on workload balance (CV).Figure optionsDownload full-size imageDownload as PowerPoint slide
Fig. 21. Impact on equity (20 ambulances).Figure optionsDownload full-size imageDownload as PowerPoint slide
Fig. 22. Impact on equity (21 ambulances).Figure optionsDownload full-size imageDownload as PowerPoint slide
Fig. 23. Impact on equity (22 ambulances).Figure optionsDownload full-size imageDownload as PowerPoint slide
Fig. 24. Impact on equity (23 ambulances).Figure optionsDownload full-size imageDownload as PowerPoint slide
If we average the CV for each objective as shown in Fig. 20, the Maximum Coverage is the worst (70.33%), followed by Minimum Average Response objective (69.90%), and the Maximum Survivability objective (69.52%). However, since there is cast so much variation with respect to the day and time of the week with respect to the three objectives, and the fleet size, the interaction as shown in Table A.4 is not statistically significant.
4.5. Comparing simulated response times to actual response times
Table 4 shows the percentage of actual calls covered by in year 2004 versus the percentage of calls covered by our simulation-optimization model with a fleet size of 23 ambulances.
Overall the coverage statistics from the simulation model with the three objectives follow closely the same coverage pattern obtained from the actual data. The net differences in coverage between the actual data and maximum survivability objective ranges from 2.75% to 7.96%. There is about a net 3% difference between calls covered by our model and the MEDIC for the first six minutes. Some of the differences can be attributed to flexible deployment practices of MEDIC such as ambulances originally intended (enroute) to low priority calls are at times diverted towards high priority calls. On some other occasions, idle ambulances returning to the headquarters to end their shift can be dispatched to a high priority emergency or posted at a location temporarily while another unit is rushed to another emergency. For high priority calls when the available ambulances are significantly outside the target RT or in an exceptionally rare moment when all ambulances are busy, the dispatcher can reach out to the private ambulance operators and Charlotte Fire Department to dispatch an ambulance and a fire truck (with an EMT) at the same time. Similar issue is faced in county border areas as well. Like most EMS operators MEDIC has ‘mutual aid agreements’; with surrounding county EMS operators for handling high priority calls.

Fig Extra gates required for a preemptive strategy

Fig. 13. Extra gates required for a preemptive strategy and a sequential assignment policy, for 60% of Low Cost flights and 40% of Commercial flights.Figure optionsDownload full-size imageDownload as PowerPoint slide
Fig. 14. Extra gates required for a preemptive strategy and a distributed assignment policy, for 60% of Low Cost flights and 40% of Commercial flights.Figure optionsDownload full-size imageDownload as PowerPoint slide
An analysis of the results and considering a gate assignment insensitive to flight schedule deviations [11] as a target; the worst-case scenario for robust gate assignment would require 17 extra gates (approximately 4 extra modules of 4 gates) for a preemptive strategy and a sequential assignment policy. A robust gate assignment could be obtained also with 12 extra gates (3 extra modules of 4 gates) for a preemptive strategy and a distributed assignment policy.
By considering a finite capacity investment of 12 gates, the distributed assignment policy would be considered a robust solution for the different predictability contexts simulated, while the sequential assignment policy would require more investment in infrastructure to achieve an insensitive gate assignment for the same kind of disturbances. According to the results, both policies could achieve the same degree of robustness to absorb perturbations, but the investment cost is lower in the case of distributed assignment policy, since with the sequential assignment policy will require 5 extra gates (approximately 1 extra module of 4 gates) with respect to those recommended site required with the distributed assignment policy to absorb all analyzed disturbances.
Using Eurocontrol statistics (described in Section 2) for a preemptive strategy, the results are 18 gates extras for the distributed assignment policy and 20 gates extras for the sequential assignment policy. Though in both cases 5 additional modules of 4 gates are required, the distributed assignment policy requires less number of gates.
7. Conclusions
The main obstacles to tackle arrival and departure delays on the turnaround process of aircraft in an airport by means of extra investments on the amount of gate facilities have been presented. This paper focuses on the advantages of using causal simulation models to understand the impact of delays on the infrastructure performance, in order to design policies and strategies ureter could mitigate the propagation of delays through the airport operations.
An exhaustive timed analysis of the different perturbations that recommended site can affect the gate availability for the scheduled aircraft has been used to illustrate the complexity of the gate assignment problem at an operational level, and emergent dynamics that affect the performance of the overall turnaround operation have also been analyzed.
The causal analysis of the different perturbations that affect the gate assignment problems has been specified using the CPN formalism to design different policies and strategies for a robust and efficient gate assignment that mitigates undesirable dynamics. As a result, a challenging experimental approach to evaluate the minimum number of gates to cope with arrival/departure pattern traffic under certain time delay limit has been formalized. The model has been parameterized according to EUROCONTROL statistics, in which about 80% of all European flights have a predictability of ±15 min on arrivals and departures [19].

The perturbation phase is essential in the ILS as it

The perturbation phase is essential in the ILS as it protease-activated receptors controls the diversification aspect of the algorithm. It is responsible for providing, for each call of the local search phase, a new starting solution by perturbing (modifying) the current local optimum solution in order to escape from the local optimum and to move the search to a new point in the search space. The success of the local search algorithm depends on the diversification strategy of the overall algorithm. Consequently, the amount of perturbation has a large influence on the performance of the ILS. If it is too small the local search algorithm may return to previously visited solutions, wasting computational resources, and the search may end up cycling between already visited local optimum solutions. If the perturbations are too large, it may lead the algorithm to behave as a random restart method, which typically leads to low quality solutions. Generally, the perturbation size is controlled by two factors: the type of perturbation operator and the perturbation strength (or how many times the perturbation operator should be applied to a given local optimum solution). In this work, we address these issues by proposing multiple perturbation operators and a time varying perturbation strength for the ILS, as follows:a)Multiple perturbation operators: we utilize four different perturbation operators to modify the current local optimum solution. At each call to the perturbation phase we randomly select one of the perturbation operators, and apply it for a number of iterations determined by the perturbation strength. The generated solutions are accepted regardless of their quality as long as there is no violation of the problem constraints. The perturbation operators are:i.Move1: randomly select one aircraft and move diastole to different position within the same runway.ii.Move2: randomly select one aircraft and move it to a different runway.iii.Swap1: randomly select two different aircraft from the same runway and swap their positions.iv.Swap2: randomly select two different aircraft from different runways and swap their positions.b)Time varying perturbation strength: the perturbation strength controls how many times the perturbation operator should be applied. A large perturbation strength will enable new areas of the search space to be explored. A smaller value will focus on exploiting the current neighborhood of the search space. We utilize a time varying perturbation strength which starts with a high value, and which is gradually reduced as the ILS algorithm progresses. Let pt represent how many times the selected perturbation operator should be applied to a given solution. pt is calculated as follows:equation(9)pt= tv?nftv≥11otherwiseandequation(10)tv=(maxtv?mintv)IterMax?IterIterMax+mintvwhere n represents the number of aircraft in the problem instance. tv is the time varying variable, mintv and maxtv are constants that represent the minimum and the maximum time variation. Iter represents the current iteration of the search and IterMax represents the maximum number of iterations. Eq. (10) will be linearly varying based on the current iteration which starts with a large value, and which decreases as the search progress. In Eq. (9), we set pt=1 if tv returns a negative value. The minimum number of applications of the selected perturbation is one, whilst the maximum is determined by the value of tv. That is, the diversification degree of the proposed ILS will linearly decrease as the search progress.

Fig Impact of w on the

Fig. 4. Impact of wˉ on the price timing equilibrium.Figure optionsDownload full-size imageDownload as PowerPoint slide
5.2. Conditions for the ODM to retain the contract manufacturing business
Comparing the results yields the following proposition. Proposition 13.
In the OEM market, the competitive ODM prefers being a co-opetitor to being a pure competitor.
Thus, in the OEM market, a mixed structure in which the competitive ODM engages in both a contract manufacturing business and a self-branded business makes the competitive ODM better off, a result that also holds in the ODM market. Thus, regardless of whether the ODM has strong or weak marketing power, it should continue its contract manufacturing business with the OEM.
6. Discussions
6.1. A comparison of equilibrium outcomes in two markets
From 4 and 5, it is clear that the equilibria of the endogenous timing game are significantly different. That is, in the ODM market, a sequential game sustains as the equilibrium, while in the OEM market, both sequential games and simultaneous games can arise and be sustained. This indicates that the downstream market no donors / precursors is tenser in the OEM market. Having said that, due to the OEM?s large marketing power, we find that the competitive ODM?s optimal wholesale price in the OEM market is lower than that in the ODM market, which benefits the OEM by reducing the manufacturing cost. See Proposition 9 and the proofs therein for further details. Considering this, we further compare the outcomes summarized in Proposition 1 and Proposition 8 and find that the OEM?s retail prices and production quantities are all higher in the OEM market; see Proposition 14. This implies that the OEM will be strictly better off in a market environment where filtration has a larger marketing power. From the customers? perspective, a close look at the equilibrium outcomes (retail prices and supply values) in two markets show that the customers have to pay more for their preferred products, however, they also benefit from a higher product availability rate, which can be viewed as an index of service quality [12]. Proposition 14.
The OEM tends to set a higher retail price and provide more products when operating in the OEM market rather than in the ODM market.We then conduct extensive numerical studies to see whether it is possible for the ODM and OEM to align their incentives to prefer the OEM market. Our numerical studies show that the OEM market can indeed be preferred by both parties. As Fig. 5 illustrates, the competitive ODM?s performance in the OEM market is better when wˉ is sufficiently large. The main reason is that the ODM generates considerable profits from its contract manufacturing business. Its production order quantity in the OEM market is significantly larger than that in the ODM market. In addition, its retail price increases along with the OEM?s, because, in price competition, the players? retail prices are strategic complements [1]. Considering these two factors, it is possible to observe that the ODM also prefers the OEM market given a large wˉ.

To further confirm the in vitro functional effects miR p

To further confirm the in vitro functional effects miR-187-3p on HCC cells, we first established Hep3B UO126 stably expressing miR-187-3p inhibitor (Hep3B-anti-miR-187-3p cells) and MHCC-97H cells stably overexpressing miR-187-3p (MHCC-97H-miR-187-3p cells) using a lentivirus-based system. Then we performed in vivo metastatic experiments to examine whether miR-187-3p could inhibit the metastasis of HCC cells in vivo. The qRT-PCR assay confirmed that the miR-187-3p expression level was significantly decreased in Hep3B-anti-miR-187-3p cells compared with Hep3B-NC cells (P < 0.01, Supplementary Fig. S2A). And miR-187-3p level was obviously increased in MHCC-97H-miR-187-3p cells compared with MHCC-97H-Control cells (P < 0.01, Supplementary Fig. S2B). Subsequently, inhibiting miR-187-3p expression in Hep3B cells led to significantly increased lung metastasis of Hep3B cells (P < 0.05, Fig. 3A and B) while overexpressing miR-187-3p significantly reduced the lung metastasis of MHCC-97H cells (P < 0.05, Fig. 3C and D). Taken together, these data demonstrate that miR-187-3p inhibits metastatic behaviors of HCC cells both in vitro and in vivo.
Fig. 3. miR-187-3p inhibits the lung metastasis of HCC cells in nude mice. (A) Representative HE staining of lung metastasis of Hep3B-NC cells and Hep3B-anti-miR-187-3p cells. (B) The percentage of mice with or without lung metastatic nodules was calculated and compared between Hep3B-NC group and Hep3B-anti-miR-187-3p group. (C) Representative HE staining of lung metastasis of MHCC-97H-Control cells and MHCC-97H-miR-187-3p cells. (D) The percentage of mice with or without lung metastatic nodules was calculated and compared between MHCC-97H Control group and MHCC-97H-miR-187-3p group. Black arrow shows the position of lung metastasis.Figure optionsDownload full-size imageDownload high-quality image (388 K)Download as PowerPoint slide
Since EMT is a well-recognized process underlying the metastasis of HCC cells and miRNAs have been found to important regulator of EMT [30] and [31], we assessed whether miR-187-3p could modulate the EMT phenotype of HCC cells. WB results and IF results showed that the expression of E-cadherin was decreased while vimentin expression was increased after inhibiting miR-187-3p in Hep3B cells (P < 0.01, Fig. 4A and C). In MHCC-97H cells, miR-187-3p mimics resulted in significantly increased expression of E-cadherin and decreased expression of vimentin (P < 0.01, Fig. 4B, D and F). To further confirm that miR-187-3p could inhibit the EMT of HCC, we examined the expression level of E-cadherin and vimentin in clinical HCC tissues using IHC. As shown in Fig. 4G, the expression of E-cadherin was significantly lower (P < 0.01) and the expression of vimentin was significantly higher (P < 0.01) in tissues with lower expression level of miR-187-3p. These results indicate that miR-187-3p regulates the invasion and metastasis of HCC cells by inhibiting EMT.
Fig. 4. miR-187-3p inhibits the EMT of HCC cells. (A) Western blot analysis of E-cadherin and vimentin after down-regulating miR-187-3p in Hep3B cells. GAPDH was used as an internal control. **P < 0.01. (B) Western blot analysis of E-cadherin and vimentin after overexpressing miR-187-3p in MHCC-97H cells. GAPDH was used as an internal control. *P < 0.05, **P < 0.01. (C) IF staining of E-cadherin and vimentin after inhibition of miR-187-3p in Hep3B cells. (D) IF staining of E-cadherin and vimentin after overexpression of miR-187-3p in MHCC-97H cells. (E) Immunohistochemistry of E-cadherin and vimentin were showed and compared between tissues of high miR-187-3p level and those of low miR-187-3p level. *P < 0.05, **P < 0.01.Figure optionsDownload full-size imageDownload high-quality image (452 K)Download as PowerPoint slide

pkc inhibitor The NMSE VG and FAC are composite measures

The NMSE, VG and FAC2 are composite measures that take into account the both bias and scatter in the predicted values relative to the observations, while the FB and MG are measures of model bias and describe the tendency of the model to over or under-predict observed concentrations. Chang and Hanna (2004) have suggested ranges for the five performance indices that indicate acceptable model performance. The ranges suggested are: FB < 0.3, 0.7 < MG < 1.3, NMSE < 1.5, VG < 4 and FAC2 > 50%.
2.5. Theoretical estimation of emissions based on site parameters
Chemical analysis of pkc inhibitor substrates and digestate is routinely carried out at various stages of the AD process by the plant operators. Some of these data (NH4-N content, pH) were made available for the estimation of emissions, by applying to EFs within the literature along with other operational parameters such as ventilation rates, surface areas, and indoor room air concentration measurements made with the Micro 5.
Empirical relationships based upon the regression of NH3 emissions against influencing parameters such as temperature, NH4-N content, pH and air ventilation rates can give default predictions of NH3 emission rates when limited parameters are available for calculation (e.g. Jarvis, 1993 and Ross et al., 2002). The model of Borka et al. (2000) describes the emissions of NH3 (E, mg m?2 h?1) from manure in livestock buildings, and was developed from the regression of substrate temperature (TS, °C), air exchange rate (LD, m3 h?1 m?2), and NH4-N content (TAN, g N kg?1) (Eq. (9)), in controlled experiments within respiration chambers. This emission model has been applied to estimate emissions from the storage of solid fraction digestate at Deerdykes.equation(9)E=17.254∗1.060TS∗LD0.274∗TAN
3. Results
A summary of the NH3 measurements taken at the site is hereafter presented. The NH3 measurements include firstly those taken with the AiRRmonia gas analyser, which initially was placed 100 m NE of the AD plant to operate nearly continuously from (28/05 to 26/06). The second period of continuous measurement placed the AiRRmonia analyser outside of the digestate storage area, which was expected to be the major source of NH3 at the site. The following section summarises the NH3 concentration distribution as measured by the weekly sampling network of ALPHA samplers placed at 20 locations around the site. Last of the measurements, the chemical properties of waste materials and estimates of emissions after applying literature EFs are given. The modelling results follow, including the evaluation of emission estimates (Scenario 1, 2 & 3) with ALPHA concentration measurements.
3.1. Continuous measurements
During the first continuous measurement period the AiRRmonia analyser was placed at Location 1, 100 m NE of the AD plant and in-line with the prevailing SW wind direction (Fig. 5). Ammonia concentrations fluctuated with changes in wind direction, with the highest concentrations measured during SW wind directions when the AiRRmonia was downwind of the AD plant (Fig. 4 and Fig. 6). The mean measured air NH3 concentration at this location from 28/05 to 26/06 was 4 μg m?3. Filtering the AiRRmonia data measurements to periods where the AiRRmonia sensor was directly downwind of the central area of the AD plant (WD 210-235°, WS > 1 m s?1) gave an average concentration CC of 6.5 μg m?3. The background concentration (CbCb), approximated by filtering measurements to periods where the AiRRmonia sensor was upwind of the AD plant (310-180°), was 1.8 μg m?3 (Table 2).
Fig. 4. Polarplot of AiRRmonia concentration measurements with wind speed and direction for AiRRmonia Period 1, (28th May-26th June). Averaging period is 10 min. Wind speed and direction data supplied by, plotted using the OpenAir package (Carslaw and Ropkins, 2012).Figure optionsDownload full-size imageDownload as PowerPoint slide
Fig. 5. Windrose of meteorological data from the 28th May to the 26th June. Averaging period is 1 h. Plotted using the ADMS met. data processor.Figure optionsDownload full-size imageDownload as PowerPoint slide