Expression and Prognostic Significance of PD-L2 in Diffuse Large B-Cell Lymphoma

Recent studies suggest that programmed death ligand-2 (PD-L2) constitutes an important antitumor immune response. Here, we investigated the relationship between PD-L2 expression and clinicopathological features in diffuse large B-cell lymphoma (DLBCL). Immunohistochemistry showed that positive expression of PD-L2 was observed in 45 of 181 newly diagnosed patients, including 14 cases with expression exclusively on tumor cells (TCs) and 31 cases with the expression on both TCs and immune cells (ICs) in the tumor microenvironment (TME). In 21 recurrent patients, positive expression of PD-L2 was present in six cases, including two cases with expression exclusively on TCs, and four cases with the expression on both TCs and ICs in the TME. Patients with PD-L2 tumor proportion score (TPS) ≥1% exhibited a better ECOG performance status (PS) (ECOG PS score <2, P = 0.041), lower international prognostic index (IPI) score (P < 0.001), and early Ann Arbor stage (Ann Arbor stage I or II, P = 0.010). Similarly, patients with PD-L2 immune proportion score (IPS) ≥1% also exhibited a better ECOG PS (ECOG PS score < 2, P = 0.006) and lower IPI score (P = 0.001). Survival analysis showed that patients with PD-L2 TPS ≥1% exhibited prolonged overall survival (OS) and progression-free survival (PFS). However, survival analysis showed no prognostic significance based on expression of PD-L2 on ICs in the TME. TC PD-L2 expression was significantly associated with OS (P = 0.041) and PFS (P = 0.001). In the multivariate analysis, TC PD-L2 expression was an independent prognostic risk factor for PFS (P = 0.013), but not for OS (P = 0.249). Furthermore, we found that higher TC and IC PD-L2 expression was associated with higher objective response rate (ORR). Moreover, we demonstrated that the expression level of PD-L2 was positively correlated with the expression status of M1 macrophage markers CD86. Our findings highlight PD-L2 as a promising therapeutic target in DLBCL

Optimizing segment storage and retrieval for distributed video-on-demand

In a distributed large-scale video-on-demand (VoD), a content provider often deploys local servers close to their users. A movie is partitioned into k segments which the servers collaboratively store and retrieve (k ≥ 1). A critical but challenging problem is how to minimize overall system deployment cost due to server bandwidth, server storage, and network traffic among servers. In this paper, we address this problem through jointly optimizing movie storage and retrieval in the server network. We first formulate the optimization problem and show that it is NP-hard. sTo address the problem, we propose a novel, effective and implementable heuristic. The heuristic, termed LP-SR, decomposes the problem into two computationally efficient linear programs (LPs) for segment storage and retrieval, respectively. The strength of LP-SR is that it is asymptotically optimal in terms of k, and k does not need to be high to achieve near optimality (around 5 to 10 in our study). For large movie pool, we propose a movie grouping algorithm to further reduce the computational complexity without compromising much on the performance. Through extensive simulation study, LP-SR is shown to perform significantly the best as compared with other state-of-the-art and traditional schemes, reducing the deployment cost by a wide margin (by multiple times in many cases). It attains performance very close to the global minimum cost

LP-SR: Approaching optimal storage and retrieval for video-on-demand

In a distributed large-scale video-on-demand (VoD) streaming network, a content provider often deploys local servers close to their users. A movie is partitioned into k segments which the servers collaboratively replicate and retrieve (k ≥ 1). A critical but challenging problem is how to minimize overall system deployment cost consisting of server bandwidth, server storage, and network traffic among servers. In this paper, we address this problem through jointly optimizing movie storage and retrieval in the server network. We first formulate the optimization problem and show that it is NP-hard. To address the problem, we propose a novel, effective and implementable heuristic termed LP-SR. LP-SR decomposes the optimization problem into two computationally efficient linear programs (LPs) for segment storage and retrieval, respectively. The strength of LP-SR is that it is asymptotically optimal in terms of k, and k is not high to be closely optimal (around 5 to 10 in our study). For large movie pool, we propose a movie grouping algorithm to further reduce the computational complexity without compromising much on the performance. Through extensive simulation, LP-SR is shown to perform significantly the best as compared with other state-of-the-art and traditional schemes, reducing the deployment cost by a wide margin (by multiple times in many cases). It attains performance very close to the global optimum. © 2013 IEEE

Effect of Thermal Aging on Mechanical Properties and Morphology of GF/PBT Composites

The effects of thermal aging at 85~145 °C in air on the tensile and flexural mechanical properties of 20% glass fiber (GF)-reinforced commercial grade polybutylene terephthalate (PBT) composites were studied. The results showed that as the aging temperature increased, the tensile and flexural strength of the GF/PBT composites significantly decreased. However, the elastic modulus of the composites was almost independent of aging. As the aging temperature increased, the separation between GF and the PBT matrix became more pronounced, and the fibers exposed on the surface of the matrix became clearer and smoother, indicating a decrease in interfacial adhesion between the PBT matrix and GF. The reason for this decrease in strength and brittle fracture of composites is the interface damage between the GF and PBT matrix caused by the difference in their thermal expansion coefficients during thermal aging

Analysis of the Influence of Parameters of a Spraying System Designed for UAV Application on the Spraying Quality Based on Box–Behnken Response Surface Method

With the development of precision agriculture (PA), low-altitude and low-volume spraying based on unmanned aerial vehicles (UAVs) is playing an increasingly important role in the control of crop diseases, pests, and weeds. However, the aerial spraying quality and droplet drift are affected by many factors, some of which are controllable (e.g., flight and spraying parameters) and some of which are not (e.g., environmental parameters). In order to study the influence of spraying parameters on the UAV-based spraying performance, we propose a UAV-compatible spraying system and a customized experimental platform in this work. Through single-factor test and Box–Behnken response surface methods, four influencing factors, namely spraying height, flow rate, distance between nozzles, and pulse width modulation (PWM) duty cycle, were studied under indoor conditions. Variance analysis and multiple quadratic regression fitting were performed on the test data by using Design-Expert 8.0.5B software, and quadratic polynomial regression models of effective spraying width, droplet coverage density, coefficient of variation, and droplet coverage rate were established. Based on the Z-score standardization, a mathematical model of the comprehensive score with four factors was established to evaluate the spraying quality and predict optimal spraying parameters. Test results indicate that the effect intensity of four influencing factors from strong to weak is PWM duty cycle, flow rate, distance between nozzles, and spraying height, and their optimal values are 98.65%, 1.74 L/min, 1.0 m, and 1.60 m, respectively. Additionally, verification experimental results demonstrate that the deviation between the predicted comprehensive score and the actual value was less than 6%. This paper can provide a reference for the design and optimization of UAV spraying systems

Analysis of the Influence of Parameters of a Spraying System Designed for UAV Application on the Spraying Quality Based on Box–Behnken Response Surface Method

With the development of precision agriculture (PA), low-altitude and low-volume spraying based on unmanned aerial vehicles (UAVs) is playing an increasingly important role in the control of crop diseases, pests, and weeds. However, the aerial spraying quality and droplet drift are affected by many factors, some of which are controllable (e.g., flight and spraying parameters) and some of which are not (e.g., environmental parameters). In order to study the influence of spraying parameters on the UAV-based spraying performance, we propose a UAV-compatible spraying system and a customized experimental platform in this work. Through single-factor test and Box–Behnken response surface methods, four influencing factors, namely spraying height, flow rate, distance between nozzles, and pulse width modulation (PWM) duty cycle, were studied under indoor conditions. Variance analysis and multiple quadratic regression fitting were performed on the test data by using Design-Expert 8.0.5B software, and quadratic polynomial regression models of effective spraying width, droplet coverage density, coefficient of variation, and droplet coverage rate were established. Based on the Z-score standardization, a mathematical model of the comprehensive score with four factors was established to evaluate the spraying quality and predict optimal spraying parameters. Test results indicate that the effect intensity of four influencing factors from strong to weak is PWM duty cycle, flow rate, distance between nozzles, and spraying height, and their optimal values are 98.65%, 1.74 L/min, 1.0 m, and 1.60 m, respectively. Additionally, verification experimental results demonstrate that the deviation between the predicted comprehensive score and the actual value was less than 6%. This paper can provide a reference for the design and optimization of UAV spraying systems