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In flexible manufacturing lines with delayed differentiation, the production process may fluctuate sharply when a control action is performed. As a result, the steady-state analysis algorithm is inaccurate for these production lines, and transient behavior studies have become crucial. However, dynamic analysis remains unexplored compared with the well-established theoretical system of steady-state analysis. Therefore, in this study, we propose a fast algorithm for predicting the production process performance in the delayed differentiation-based flexible production line under operation control. We first formulate practical problems existing in the auto, food, and furniture industries into a mathematical formation. Then, we offer closed-form formulae for predicting the production process performance using the built stochastic model in the production line with three machines. We also propose an algorithm to predict the performance of a production line having more than three machines. The proposed methods were verified to be highly accurate through comparison experiments. In terms of theoretical contributions, this study offers a research foundation for other transient-based studies. From a practical perspective, the proposed algorithms can be employed to predict the production process performance of processing lines under production control in advance. [ABSTRACT FROM AUTHOR]

Purpose: The Centiloid project helps calibrate the quantitative amyloid-β (Aβ) load into a unified Centiloid (CL) scale that allows data comparison across multi-site. How the smaller regional amyloid converted into CL has not been attempted. We first aimed to express regional Aβ deposition in CL using [18F]Flutemetamol and evaluate regional Aβ deposition in CL with that in standardized uptake value ratio (SUVr). Second, we aimed to determine the presence or absence of focal Aβ deposition by measuring regional CL in equivocal cases showing negative global CL. Methods: Following the Centiloid project pipeline, Level-1 replication, Level-2 calibration, and quality control were completed to generate corresponding Centiloid conversion equations to convert SUVr into Centiloid at regional levels. In equivocal cases, the regional CL was compared with visual inspection to evaluate regional Aβ positivity. Results: 14 out of 16 regional conversions from [18F]Flutemetamol SUVr to Centiloid successfully passed the quality control, showing good reliability and relative variance, especially precuneus/posterior cingulate and prefrontal regions with good stability for Centiloid scaling. The absence of focal Aβ deposition could be detected by measuring regional CL, showing a high agreement rate with visual inspection. The regional Aβ positivity in the bilateral anterior cingulate cortex was most prevalent in equivocal cases. Conclusion: The expression of regional brain Aβ deposition in CL with [18F]Flutemetamol has been attempted in this study. Equivocal cases had focal Aβ deposition that can be detected by measuring regional CL. [ABSTRACT FROM AUTHOR]

Key Points: Question: Does the connective tissue growth factor inhibitor pamrevlumab decrease the rate of decline in lung function for patients with idiopathic pulmonary fibrosis compared with placebo? Findings: In this phase 3 randomized clinical trial including 356 adults with idiopathic pulmonary fibrosis, the decline in forced vital capacity at 48 weeks did not differ significantly between patients treated with pamrevlumab (–260 mL) vs placebo (–330 mL). Meaning: Use of pamrevlumab among patients with idiopathic pulmonary fibrosis did not result in a difference in decline in forced vital capacity from baseline to 48 weeks compared with placebo. Importance: Current treatments for idiopathic pulmonary fibrosis slow the rate of lung function decline, but may be associated with adverse events that affect medication adherence. In phase 2 trials, pamrevlumab (a fully human monoclonal antibody that binds to and inhibits connective tissue growth factor activity) attenuated the progression of idiopathic pulmonary fibrosis without substantial adverse events. Objective: To assess the efficacy and safety of pamrevlumab for patients with idiopathic pulmonary fibrosis. Design, Setting, and Participants: Phase 3 randomized clinical trial including 356 patients aged 40 to 85 years with idiopathic pulmonary fibrosis who were not receiving antifibrotic treatment with nintedanib or pirfenidone at enrollment. Patients were recruited from 117 sites in 9 countries between July 18, 2019, and July 29, 2022; the last follow-up encounter occurred on August 28, 2023. Interventions: Pamrevlumab (30 mg/kg administered intravenously every 3 weeks; n = 181) or placebo (n = 175) for 48 weeks. Main Outcomes and Measures: The primary outcome was absolute change in forced vital capacity (FVC) from baseline to week 48. There were 5 secondary outcomes (including time to disease progression, which was defined as a decline of ≥10% in predicted FVC or death). The exploratory outcomes included patient-reported symptoms. Adverse events were reported. Results: Among 356 patients (mean age, 70.5 years; 258 [72.5%] were men; 221 [62.1%] were White), 277 (77.8%) completed the trial. There was no significant between-group difference for absolute change in FVC from baseline to week 48 (least-squares mean, −260 mL [95% CI, −350 to −170 mL] in the pamrevlumab group vs −330 mL [95% CI, −430 to −230 mL] in the placebo group; mean between-group difference, 70 mL [95% CI, −60 to 190 mL], P =.29). There were no significant between-group differences in any of the secondary outcomes or in the patient-reported outcomes. In the pamrevlumab group, there were 160 patients (88.4%) with treatment-related adverse events and 51 patients (28.2%) with serious adverse events vs 151 (86.3%) and 60 (34.3%), respectively, in the placebo group. During the study, 23 patients died in each group (12.7% in the pamrevlumab group vs 13.1% in the placebo group). Conclusions and Relevance: Among patients with idiopathic pulmonary fibrosis treated with pamrevlumab or placebo, there was no statistically significant between-group difference for the primary outcome of absolute change in FVC from baseline to week 48. Trial Registration: ClinicalTrials.gov Identifier: NCT03955146 This randomized clinical trial compares the efficacy and safety of pamrevlumab vs placebo for patients with idiopathic pulmonary fibrosis. [ABSTRACT FROM AUTHOR]

Many invertebrates and vertebrates secrete mucus from their body surface, which plays a crucial role in protecting themselves from attacks by microorganism or predators. This study reports on the potential functions of mucus secreted from the body surface of larvae of the moth Phauda flammans (Walker) (Lepidoptera: Phaudidae). We tested whether the mucus could inhibit the growth of the fungus Beauveria bassiana PfBb (Bals.‐Criv.) Vuill. (Hypocreales) and attract and/or deter predators such as the crazy ant, Paratrechina longicornis (Latreille) (Hymenoptera: Formicidae), and the predatory bug Eocanthecona furcellata (Wolff) (Hemiptera: Pentatomidae). Our results showed that de‐ and rehydrated mucus concentrations of 0.5–1.0 mg mL−1 had an inhibitory effect on the conidial germination and colony growth of B. bassiana PfBb; however, P. flammans mucus did not significantly affect fungal sporulation. Raw mucus and mucus concentrations of 1.0–4.0 mg mL−1 attracted P. longicornis workers in a Y‐tube olfactometer, whereas the physical viscosity of raw mucus hindered their foraging for food in a laboratory test. The E. furcellata adults did not display a preference for the odour of P. flammans mucus. Therefore, P. flammans mucus may inhibit pathogenic microorganisms and attract or repel predators, but the mucus does not act as a complete deterrent. [ABSTRACT FROM AUTHOR]

The prediction of power equipment activity plays a vital role in optimizing power resource dispatch, ensuring supply and demand balance, and guiding network planning and management. However, due to the complex nonlinear, multi-scale, and multivariate characteristics of power grid communication networks service activity (PCNSA) data, it is often challenging to capture its intrinsic patterns and dynamic changes through a simple model. To address this issue, this paper proposes a power grid communication network service activity prediction method based on convolutional neural network, bidirectional gated recurrent unit, and attention mechanism, referred to as CBGA. CNN is used to extract features from time-series data, BiGRU is used to capture long-term feature changes in the data, and the attention mechanism is used to enhance the extraction of important information. To validate the performance of the proposed method, experiments and comparisons were conducted on three real power grid communication network datasets, demonstrating that our method shows better performance and robustness. [ABSTRACT FROM AUTHOR]

To understand non-compliance behaviors in investment goods in pandemic preparedness and resilience, we resort to a form of bounded rationality that people suffer from a lack of self-control due to "present bias", and differ in their sophistication levels (the degree to which they are aware of such compliance barriers). We focus on (i) the manufacturer's pricing strategy under an advance selling framework, and (ii) the subsidy policy to mitigate under-adoption, to generate operational insights. We show that subsidizing the manufacturer is more cost-effective than subsidizing consumers, because the latter subsidy will not fully trickle down to consumers when the manufacturering manipulates prices in response. In particular, when the subsidy program is budget-constrained, the manufacturer subsidy should be provided only in the spot period. In contrast, when the budget constraint is relaxed, subsidies in both periods should be provided. Surprisingly, such a subsidy program has non-monotone impacts on consumers' adoption quantities. Intuitively, this is because the spot-period subsidy induces consumers' non-compliance behaviors in the advance period. In response, the manufacturer/seller will shift to a pricing strategy that may further reduce the advance-selling quantity. This result provides a natural explanation to reconcile the mixed effects of adoption subsidies. [ABSTRACT FROM AUTHOR]

The advancement of low-temperature co-fired ceramic (LTCC) technology has led to increased demands for microwave dielectric ceramics. Among various material systems, the ATiB2O8 (A = Mg2+, Zn2+, Cu2+, Co2+, Ni2+; B = Ta5+, Nb5+) family has garnered significant attention due to its high quality factor (Q × f). However, the elevated sintering temperature of this system hinders its application in LTCC technology. In this study, CoTiTa2O8 ceramics were synthesized using the molten salt method to lower the sintering temperature. The correlation between phase composition, microstructure, and microwave dielectric properties (MDP) of CoTiTa2O8 samples was investigated through XRD, Rietveld refinement, and SEM analyses. The findings reveal that CoTiTa2O8 ceramics fabricated under optimized conditions exhibit a tri-rutile structure with space group P42/mnm (136). The impact of oxygen octahedron distortion dielectric, packing fraction, and MDP is deliberated. CoTiTa2O8 samples sintered at 950 ℃ demonstrate exceptional dielectric characteristics with εr = 38.6, Q × f = 20,600 GHz, τf = + 108.42 ppm/℃, suggesting their significant potential for application in LTCC technology. [ABSTRACT FROM AUTHOR]

Reflectance spectroscopy is rapid, inexpensive, and non-destructive and can provide important information about the mineralogy of rocks and sediments. We measured the reflectance spectroscopy of Miocene red clay deposits on the northeastern margin of the Tibetan Plateau, with the aim of developing a rapid methodology for detecting paleoclimatic changes. We obtained visible/near-infrared (VNIR) and short-wave infrared (SWIR) spectroscopy data from the red clay in the Jianzha Basin, and analyzed their relationship with independent paleoclimatic records, including mineral contents and environmental magnetic parameters. The results show that the VNIR parameters, including D500, D900, R500, and R900 (where D and R represent the depth and reflectance of the absorption peaks around 500 and 900 nm, respectively) are temperature-sensitive and correlated with the magnetic susceptibility, frequency-dependent magnetic susceptibility, and the marine δ18O record. The results of frequency-domain analysis of the VNIR parameters show that they reflect climate change on orbital timescales. SWIR parameters, such as AS1400, D1400/D1900 and D1900 (where AS represents the asymmetry of the absorption peaks around 1400 nm), are correlated with the illite and montmorillonite content, and they are sensitive to the weathering intensity. The spectral parameters of the eolian red clay in the Jianzha Basin reflect regional climatic changes caused by the uplift of the Tibetan Plateau at ∼8.5 Ma and global climatic cooling at ∼7.2 Ma, and thus they are applicable as both regional and global paleoenvironmental indicators. [ABSTRACT FROM AUTHOR]

This work provides performance guarantees for solving data-driven contextual newsvendor problems when the contextual data contains intertemporal dependence and non-stationarities. While machine learning tools have observed increasing use in data-driven inventory management problems, most of the existing work assumes that the contextual data are independent and identically distributed (often referred to as i.i.d.). However, such assumptions are often violated in real operational environments where the contextual data are sequentially generated with intertemporal correlations and possible non-stationarities. By accommodating these naturally arising operational environments, our work adopts comparatively more realistic assumptions and develops out-of-sample performance bounds for learning data-driven contextual newsvendor problems. [ABSTRACT FROM AUTHOR]

Problem definition: Content promotion policies are crucial for online content platforms to improve content consumption and user engagement. However, traditional promotion policies generally neglect the diffusion effect within a crowd of users. In this paper, we study the candidate generation and promotion optimization (CGPO) problem for an online content platform, emphasizing the incorporation of the diffusion effect. Methodology/results: We propose a diffusion model that incorporates platform promotion decisions to characterize the adoption process of online content. Based on this diffusion model, we formulate the CGPO problem as a mixed-integer program with nonconvex and nonlinear constraints, which is proved to be NP-hard. Additionally, we investigate methods for estimating the diffusion model parameters using available online platform data and introduce novel double ordinary least squares (D-OLS) estimators. We prove the submodularity of the objective function for the CGPO problem, which enables us to find an efficient (1−1/e) -approximation greedy solution. Furthermore, we demonstrate that the D-OLS estimators are consistent and have smaller asymptotic variances than traditional ordinary least squares estimators. By utilizing real data from a large-scale video-sharing platform, we show that our diffusion model effectively characterizes the adoption process of online content. Compared with the policy implemented on the platform, our proposed promotion policy increases total adoptions by 49.90%. Managerial implications: Our research highlights the essential role of diffusion in online content and provides actionable insights for online content platforms to optimize their content promotion policies by leveraging our diffusion model. Funding: R. Zhang is grateful for the financial support from the Hong Kong Research Grants Council General Research Fund [Grants 14502722 and 14504123] and the National Natural Science Foundation of China [Grant 72293560/72293565]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0172. [ABSTRACT FROM AUTHOR]

Cardiac macrophage contributes to the development of cardiac fibrosis, but factors that regulate cardiac macrophages transition and activation during this process remains elusive. Here we show, by single-cell transcriptomics, lineage tracing and parabiosis, that cardiac macrophages from circulating monocytes preferentially commit to macrophage-to-myofibroblast transition (MMT) under angiotensin II (Ang II)-induced hypertension, with accompanying increased expression of the RNA N6-methyladenosine demethylases, ALKBH5. Meanwhile, macrophage-specific knockout of ALKBH5 inhibits Ang II-induced MMT, and subsequently ameliorates cardiac fibrosis and dysfunction. Mechanistically, RNA immunoprecipitation sequencing identifies interlukin-11 (IL-11) mRNA as a target for ALKBH5-mediated m6A demethylation, leading to increased IL-11 mRNA stability and protein levels. By contrast, overexpression of IL11 in circulating macrophages reverses the phenotype in ALKBH5-deficient mice and macrophage. Lastly, targeted delivery of ALKBH5 or IL-11 receptor α (IL11RA1) siRNA to monocytes/macrophages attenuates MMT and cardiac fibrosis under hypertensive stress. Our results thus suggest that the ALKBH5/IL-11/IL11RA1/MMT axis alters cardiac macrophage and contributes to hypertensive cardiac fibrosis and dysfunction in mice, and thereby identify potential targets for cardiac fibrosis therapy in patients. Cardiac macrophage contributes to the onset of cardiac fibrosis, but the underneath mechanisms remain unclear. Here the authors show that mouse cardiac macrophages from circulating monocytes may trans-differentiate into myofibroblast under hypertensive conditions for fibrosis development, with an AKLBH5/IL11 molecular axis modulating this macrophage-to-myofibroblast transition. [ABSTRACT FROM AUTHOR]

A precise, scalable, and computationally efficient mathematical framework is proposed for region-wide autonomous electric vehicle (AEV) fleet management, sizing and infrastructure planning for urban ride-hailing services. A comprehensive techno-economic analysis in New York City is conducted not only to calculate the societal costs but also to quantify the environmental and health benefits resulting from reduced emissions. The results reveal that strategic fleet management can reduce fleet size and unnecessary cruising mileage by up to 40% and 70%, respectively. This alleviates traffic congestion, saves travel time, and further reduces fleet sizes. Besides, neither large-battery-size AEVs nor high-power charging infrastructure is necessary to achieve efficient service. This effectively alleviates financial and operational burdens on fleet operators and power systems. Moreover, the reduced travel time and emissions resulting from efficient fleet autonomy create an economic value that exceeds the total capital investment and operational costs of fleet services. [ABSTRACT FROM AUTHOR]

Aphis spiraecola Patch is one of the most economically important tree fruit pests worldwide. The pyrethroid insecticide lambda-cyhalothrin is commonly used to control A. spiraecola. In this 2-year study, we quantified the resistance level of A. spiraecola to lambda-cyhalothrin in different regions of the Shaanxi province, China. The results showed that A. spiraecola had reached extremely high resistance levels with a 174-fold resistance ratio (RR) found in the Xunyi region. In addition, we compared the enzymatic activity and expression level of P450 genes among eight A. spiraecola populations. The P450 activity of A. spiraecola was significantly increased in five regions (Xunyi, Liquan, Fengxiang, Luochuan, and Xinping) compared to susceptible strain (SS). The expression levels of CYP6CY7 , CYP6CY14 , CYP6CY22, P4504C1-like , P4506a13 , CYP4CZ1 , CYP380C47, and CYP4CJ2 genes were significantly increased under lambda-cyhalothrin treatment and in the resistant field populations. A L1014F mutation in the sodium channel gene was found and the mutation rate was positively correlated with the LC50 of lambda-cyhalothrin. In conclusion, the levels of lambda-cyhalothrin resistance of A. spiraecola field populations were associated with P450s and L1014F mutations. Our combined findings provide evidence on the resistance mechanism of A. spiraecola to lambda-cyhalothrin and give a theoretical basis for rational and effective control of this pest species. [ABSTRACT FROM AUTHOR]

Grounded in advanced analytical techniques and close relationships with its partners, JD.com, the largest retailer in China based on revenue, is committed to an intelligent, integrated, and resilient supply chain that creates value for all stakeholders within the retail ecosystem. Despite challenges in the complex and sophisticated retail supply chain, JD.com has strengthened its supply chain agility, and attained shared value by focusing on supply chain efficiency, supply chain resilience, and customer-demand intelligence. Specifically, JD.com implemented an end-to-end inventory management system based on a dynamic programming model and a neural network model, leading to a reduction in costs and enhancements in operational efficiency. To be able to provide guaranteed service levels for consumers during supply chain disruptions, the company used intelligent techniques, including an emergency classification mechanism and a simulation model, to strengthen its collaboration with critical partners, attain resilience, and benefit society as a whole. For the upstream manufacturers, JD.com implemented the consumer-to-manufacturer system by incorporating state-of-the-art artificial intelligence algorithms and enabled manufacturers to accurately predict customer demand and produce more popular products according to customer preferences, hence creating value for the entire ecosystem. Billions of dollars in increased revenue and tens of millions of dollars in cost savings have been achieved to date since the implementation of the aforementioned techniques, and customer welfare and partner manufacturers' benefits have been significantly enhanced. [ABSTRACT FROM AUTHOR]

Problem definition: We consider intertemporal pricing in the presence of reference effects and consumer heterogeneity. Our research question encompasses how to estimate heterogeneous consumer reference effects from data and how to efficiently compute the optimal pricing policy. Academic/practical relevance: Understanding reference effects is essential for designing pricing policies in modern retailing. Our work contributes to this area by incorporating consumer heterogeneity under arbitrary distributions. Methodology: We propose a mixed logit demand model that allows arbitrary joint distributions of valuations, responsiveness to prices, and responsiveness to reference prices among consumers. We use a nonparametric estimation method to learn consumer heterogeneity from transaction data. Further, we formulate the pricing optimization as an infinite horizon dynamic programming problem and solve it by applying a modified policy iteration algorithm. Results: Moreover, we investigate the structure of optimal pricing policies and prove the suboptimality of constant pricing policies even when all consumers are loss-averse according to the classical definition. Our numerical studies show that our estimation and optimization framework improves the expected revenue of retailers via accounting for heterogeneity. We validate our model using real data from JD.com, a large E-commerce retailer, and find empirical evidence of consumer heterogeneity. Managerial implications: In practice, ignoring consumer heterogeneity may lead to a significant loss of revenue. Furthermore, heterogeneous reference effect offers a strong motive for promotions and price fluctuations. History: This paper has been accepted as part of the 2020 MSOM Data Driven Research Challenge. Funding: This work was partially supported by the National Natural Science Foundation of China [Grant 71991462]. Supplemental Material: The e-companion is available at https://doi.org/10.1287/msom.2022.1134. [ABSTRACT FROM AUTHOR]

To improve the atomic oxygen (AO) erosion resistance of Kapton for application as an aerospace material in low earth orbit (LEO), a graphene-modified polysiloxane-60 vol.% SiO2 (G-PSS) composite coating was prepared and tested for AO exposure at a total flux of 1.86 × 1020 atoms/cm2. The prepared coating with a thickness of 5 μm was smooth, with good adhesion and no macroscopic defects. Its AO erosion yield was 9.77 × 10−27–1.25 × 10−26 cm3/atom, which was about three orders and one order of magnitude lower than that of Kapton and polysiloxane-60vol.%SiO2 (PSS) hybrid coating, respectively. The beneficial effect of graphene was attributed to the effective inhibition of gas permeation by the single-layer graphene due to its unique structure and the more stable epoxy groups produced during the reaction of graphene with AO. [ABSTRACT FROM AUTHOR]

The security of the dynamic heterogeneous redundancy (DHR) architecture relies on the heterogeneity of its executors, which also defines the vulnerability of the mimic system. In order to select executors with reliable and significant dissimilarity as service executors, we propose a DHR executor selection algorithm based on historical credibility and dissimilarity clustering (HCDC), which adds two metrics of executor historical credibility and dissimilarity. First, to maximize the difference between heterogeneous executor pools, clustering is performed based on the dissimilarity of the executor. Second, the executor with the highest historical credibility is selected from the heterogeneous executor pool as the candidate pool. The historical credibility is dynamically updated by the negative feedback control based on the results of the multi-mode adjudicator. Finally, the dynamic scheduling algorithm selects the executors from the candidate pool to form the set of service executors. The simulation results demonstrate that, in comparison to existing methods, the algorithm reduces the attack success rate and average failure rate while increasing system reliability. [ABSTRACT FROM AUTHOR]

Aim: The geographical distribution of bacteria is an important, but poorly understood, topic in microbial ecology. A major question is how broadly distributed generalist taxa, and limitedly distributed specialist taxa, vary across a latitudinal gradient in freshwater ecosystems. We predict that: (a) generalists and specialists exhibit latitudinal diversity gradient with different patterns; (b) their community assemblies are mainly driven by stochastic processes; and (c) generalists coexist through niche differences, while specialists coexist through fitness differences. Location: Sixty lakes and reservoirs in China, ranging from 18° N to 50° N. Time Period: July–August in 2012 and 2018. Taxa Studied: Bacterioplankton. Methods: We clustered zero‐radius operational taxonomic unit (zOTU) (subspecies‐like level) into operational taxonomic unit (OTU) (species‐like level) and calculated the intra‐specific variation and spatial asynchrony of OTU. We examined the relative effects of environment versus space (latitude) on bacterial community and quantified the community assembly processes of generalists and specialists, respectively. The binary‐state speciation and extinction (BiSSE) model has been used to estimate the evolutionary characteristics. The abundances of the top zOTUs within each OTU were identified to reveal their niche preferences (distribution patterns at different sites). Results: We found that bacterial generalists had a higher intra‐specific variation, greater asynchrony and wider niche width than the specialists. With increasing latitude, bacterial diversity decreased with abundance variations in generalists and occurrence variations in specialists, respectively. Diversification in stochastic processes was the main driving factor in both groups, though deterministic processes showed greater effects on specialists than generalists in local communities. Bacterial generalists coexisted through niche differences, whereas specialists coexisted through average fitness differences. Main Conclusions: We demonstrated distinct latitudinal distribution patterns of bacterial generalists and specialists. These results highlight differences in biogeography of microbial generalist and specialist taxa mediated by intra‐specific variation and emphasize their distinctly vital roles mediated by differing mechanisms in freshwater ecosystems. [ABSTRACT FROM AUTHOR]

The carpooling service, which is the sharing of journeys heading in similar directions, is expected to be more efficient. In this article, we study the impact of providing a carpooling service on customer waiting time and driver utilization in an on-demand service platform. We build an M / G / N queueing model to approximate the dynamics of the on-demand service platform that provides two services: a standard service and a carpooling service. We find that two factors influence the efficiency of the carpooling service: the source of customers who use the carpooling service, and the length of a normalized detour. If the carpooling service attracts customers who have not used this on-demand service before, i.e., the market size increases, then both the customer waiting time and driver utilization increase when more customers use the carpooling service. If the carpooling service primarily attracts customers who already use the standard on-demand service before, i.e., customers switch from the standard service to the carpooling service, then the impact of the carpooling service depends on the normalized detour. It is possible that customer waiting time and driver utilization first increase and then decrease as customers switch from the standard service to the carpooling service. [ABSTRACT FROM AUTHOR]

Trade credit is widely used by companies to obtain external funds. The extant literature has demonstrated that trade credit benefits the buyer and the supplier in multiple ways, but might still induce various issues. In this paper, we focus on the impact of trade credit on growing small businesses and their suppliers. By looking into a one-supplier-one-retailer supply chain under a multiple-period setting, we study the expansion and inventory policies of the retailer with his consideration of risk control, which is critical for any small business. We also take into account the supplier's risk control decision on whether trade credit will be extended. We further numerically mimic various growth scenarios of the retailer. Interestingly, we find that, in contrast to the traditional wisdom, trade credit offered by the supplier not only increases the profits of both parties, but also reduces the retailer's default risk, as long as the supplier can apply appropriate risk controls. In addition, we show that offering trade credit does not necessarily attract retailers to act aggressively in general. Under the supplier's risk controls, the retailer's growth rate can be quite insensitive with the term of trade credit. [ABSTRACT FROM AUTHOR]

Content-sharing social network platforms rely heavily on user-generated content to attract users and advertisers, but they have limited authority over content provision. We develop an intervention that leverages social interactions between users to stimulate content production. We study social nudges, whereby users connected with a content provider on a platform encourage that provider to supply more content. We conducted a randomized field experiment (N = 993 , 676) on a video-sharing social network platform where treatment providers could receive messages from other users encouraging them to produce more, but control providers could not. We find that social nudges not only immediately boosted video supply by 13.21% without changing video quality but also, increased the number of nudges providers sent to others by 15.57%. Such production-boosting and diffusion effects, although declining over time, lasted beyond the day of receiving nudges and were amplified when nudge senders and recipients had stronger ties. We replicate these results in a second experiment. To estimate the overall production boost over the entire network and guide platforms to utilize social nudges, we combine the experimental data with a social network model that captures the diffusion and over-time effects of social nudges. We showcase the importance of considering the network effects when estimating the impact of social nudges and optimizing platform operations regarding social nudges. Our research highlights the value of leveraging co-user influence for platforms and provides guidance for future research to incorporate the diffusion of an intervention into the estimation of its impacts within a social network. This paper was accepted by Victor Martínez-de-Albéniz, operations management. Funding: H. Dai thanks the University of California, Los Angeles (UCLA) [Hellman Fellowship and Faculty Development Award] for funding support. R. Zhang is grateful for financial support from the Hong Kong Research Grants Council [Grant 16505418]. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2022.4622. [ABSTRACT FROM AUTHOR]

Problem definition: Shared micromobility vehicles provide an eco-friendly form of short-distance travel within an urban area. Because customers pick up and drop off vehicles in any service region at any time, such convenience often leads to a severe imbalance between vehicle supply and demand in different service regions. To overcome this, a micromobility operator can crowdsource individual riders with reward incentives in addition to engaging a third-party logistics provider (3PL) to relocate the vehicles. Methodology/results: We construct a time-space network with multiple service regions and formulate a two-stage stochastic mixed-integer program considering uncertain customer demands. In the first stage, the operator decides the initial vehicle allocation for the regions, whereas in the second stage, the operator determines subsequent vehicle relocation across the regions over an operational horizon. We develop an efficient solution approach that incorporates scenario-based and time-based decomposition techniques. Our approach outperforms a commercial solver in solution quality and computational time for solving large-scale problem instances based on real data. Managerial implications: The budgets for acquiring vehicles and for rider crowdsourcing significantly impact the vehicle initial allocation and subsequent relocation. Introducing rider crowdsourcing in addition to the 3PL can significantly increase profit, reduce demand loss, and improve the vehicle utilization rate of the system without affecting any existing commitment with the 3PL. The 3PL is more efficient for mass relocation than rider crowdsourcing, whereas the latter is more efficient in handling sporadic relocation needs. To serve a region, the 3PL often relocates vehicles in batches from faraway, low-demand regions around peak hours of a day, whereas rider crowdsourcing relocates a few vehicles each time from neighboring regions throughout the day. Furthermore, rider crowdsourcing relocates more vehicles under a unimodal customer arrival pattern than a bimodal pattern, whereas the reverse holds for the 3PL. Funding: This work was supported by the Research Grants Council of Hong Kong [Grants 15501319 and 15505318] and the National Natural Science Foundation of China [Grant 71931009]. Z. Jin was supported by the Hong Kong PhD Fellowship Scheme. Y. F. Lim was supported by the Lee Kong Chian School of Business, Singapore Management University [Maritime and Port Authority Research Fellowship]. Supplemental Material: The online appendices are available at https://doi.org/10.1287/msom.2023.1199. [ABSTRACT FROM AUTHOR]

Adjusting the grain growth orientation may be a feasible way to improve the oxidation resistance. In this work, textured Ti3(SiAl)C2 ceramic was successfully fabricated via the spark plasma sintering technique. The crystal orientation and microstructure were investigated by XRD combined with EBSD. The oxidation behavior of textured Ti3(SiAl)C2 was investigated at 1000–1300 °C for 10 h. The results showed that the oxidation was significantly anisotropic and the surface parallel to the compression direction exhibited better oxidation resistance below 1200 °C. The improved oxidation resistance was primarily attributed to the formation of passivated Al2O3 scale by rapid out-diffusion of Al elements on the orientated (hko) planes in textured Ti3(SiAl)C2. The formation of oxide scales was strongly dependent on the crystallographic orientation of Ti3(SiAl)C2. [ABSTRACT FROM AUTHOR]

The application of a sodium laser guide star is the key difference between a modern adaptive optics system and traditional adaptive optics system. Especially in system such as multiconjugate adaptive optics, a sodium laser guide star asterism that is formed by several laser guide stars in a certain pattern is required to probe more atmospheric turbulence in different directions. To achieve this, a sodium laser guide star asterism launching platform is required. In this paper, we introduce the sodium laser guide star asterism launching platform built and tested on the 1.8 m telescope of Gaomeigu Observatory. The platform has two functions: one function is to compare the performance of sodium laser guide stars generated by different lasers at the same place, and the other function is to generate a sodium laser guide star asterism with an adjustable shape. The field test results at the beginning of 2021 verified the important role of the platform, which is also the first time that a sodium laser guide star asterism was realized in China. [ABSTRACT FROM AUTHOR]

Rising temperatures can enhance foraging activity and accelerate the encounter rate of different predators, which may increase their interference competition strengths. However, limited information is available on such effects of temperature, and on the consequences for their predation rates. We used a functional response approach to experimentally quantify the interspecific interference competition strength of two species of ladybirds, Harmonia axyridis and Propylea japonica (Coleoptera: Coccinellidae), toward their prey Myzus persicae (Hemiptera: Aphididae) at 23 and 33 °C, respectively. The results indicated that high temperature could cause P. japonica to be more active and interfere with H. axyridis more often, and strengthened the interference competition between these two predators. The functional response of H. axyridis was changed from type II in single H. axyridis treatment to type III in paired predator assays at 23 and 33 °C. Moreover, single H. axyridis consumed more aphids than H. axyridis in heterospecific predator trials at aphid densities below 50 and 35 at 23 and 33 °C treatments, respectively. For P. japonica, type II functional responses were detected in all assays. Additionally, when competing with H. axyridis, the predation rate of P. japonica at 23 °C was almost unchanged compared to that of single P. japonica, but fewer aphids were eaten compared with single P. japonica across all aphid densities at 33 °C. Thus, with interference competition, two predator species respond differently to temperature changes in terms of foraging efficiency, which may further affect the population adaptability and control efficiency of these two focal species. [ABSTRACT FROM AUTHOR]

We investigate a data-driven multiperiod inventory replenishment problem with uncertain demand and vendor lead time (VLT) with accessibility to a large quantity of historical data. Different from the traditional two-step predict-then-optimize (PTO) solution framework, we propose a one-step end-to-end (E2E) framework that uses deep learning models to output the suggested replenishment amount directly from input features without any intermediate step. The E2E model is trained to capture the behavior of the optimal dynamic programming solution under historical observations without any prior assumptions on the distributions of the demand and the VLT. By conducting a series of thorough numerical experiments using real data from one of the leading e-commerce companies, we demonstrate the advantages of the proposed E2E model over conventional PTO frameworks. We also conduct a field experiment with JD.com, and the results show that our new algorithm reduces holding cost, stockout cost, total inventory cost, and turnover rate substantially compared with JD's current practice. For the supply chain management industry, our E2E model shortens the decision process and provides an automatic inventory management solution with the possibility to generalize and scale. The concept of E2E, which uses the input information directly for the ultimate goal, can also be useful in practice for other supply chain management circumstances. This paper was accepted by Hamid Nazerzadeh, big data analytics. Funding: This research was supported by the National Key Research and Development Program of China [Grant 2018YFB1700600] and National Natural Science Foundation of China [Grants 71991462 and 91746210]. Supplemental Material: The online data are available at https://doi.org/10.1287/mnsc.2022.4564. [ABSTRACT FROM AUTHOR]

New products are highly valued by manufacturers and retailers due to their vital role in revenue generation. Product life cycle (PLC) curves often vary by their shapes and are complicated by promotional activities that induce spiky and irregular behaviors. We collaborate with JD.com to develop a flexible PLC curve forecasting framework based on Bayesian functional regression that accounts for useful covariate information, including product attributes and promotion. The functional model treats PLC curves as target variables and includes both scalar and functional predictors, capturing time‐varying promotional activities. Harnessing the power of basis function transformation, the developed model can effectively characterize the local features and temporal evolution of sales curves. Our Bayesian framework can generate initial curve forecasts before the product launch and update the forecasts dynamically as new sales data are collected. We validate the superior performance of our method through extensive numerical experiments using three real‐world data sets. Our forecasting framework reduces the forecasting error by 5.35%–30.76% over JD.com's current model and outperforms alternative models significantly. Furthermore, the estimated promotion effect function provides useful insights into how promotional activities interact with sales curves. [ABSTRACT FROM AUTHOR]

Due to the particularity of biomedical industry, it has become necessary for biomedical enterprises to seek innovative research and development (R&D) cooperation to maintain advanced technologies and products in multiple fields. Under such circumstance, the biomedical industry has gradually formed a certain cluster to promote the development of the industry. So far, the biomedical industry cluster has formed in China, mainly within the Yangtze River Delta, Pearl River Delta, and Beijing-Tianjin-Hebei three urban agglomerations. Within the industrial clusters, the frequency of innovation cooperation among enterprises, universities, research institutions, and other relevant organizations in the biomedical area is high, and the capacity for innovation cooperation is strong as well. This paper used the representative cross-section data of cooperative patents from the medical science and technology patent database of China National Knowledge Infrastructure (CNKI), researching the R&D cooperation within the three major urban agglomerations in China from 2008 to 2016 (Yangtze River Delta Urban Agglomeration, Pearl River Delta Urban Agglomeration, Beijing-Tianjin-Hebei Urban Agglomeration) on total 36 cities' spatial pattern characteristics of biomedical cooperation and the influencing factors. The spatial interaction model was used to study the spatial, economic, political, and R&D influencing factors of cross-city cooperation. The degree of aggregation showed that cross-city R&D cooperation mainly occurred in well-developed and central cities of urban agglomerations. Econometric results revealed that spatial, economic, political, and R&D bias factors did have a significant impact on the frequency of biomedical R&D cooperation across cities. [ABSTRACT FROM AUTHOR]

The mission of the Institute of Industrial and Systems Engineers (IISE) is to serve those who solve complex and critical problems of the world. Notably, the research–practice gap in Operations Management (OM) marginalizes the value and relevance of the IISE. To maintain and enhance the impact of the IISE, we identify major bottlenecks that limit the industrial installation of OM research outcomes. Ranked by the relative importance, the three bottlenecks are verifying the performance improvement, building trust with practitioners, and balancing model accuracy and simplicity, respectively, in the stages of value verification, implementation and development. We propose potential research opportunities and illustrate the challenges and opportunities using real case studies from three Fortune Global 500 companies. In particular, we emphasize the role of data-driven decision methods in dealing with the three bottlenecks. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar (SAR) is a powerful tool for sea surface monitoring. The 2017–2020 mission of the Chinese Gaofen-3 (GF-3) over the Arctic Ocean provided a unique opportunity to investigate the feasibility of wave retrieval in the Arctic Ocean. In this study, several GF-3 SAR images acquired in quad-polarization (QPS) mode were applied for wave retrieval using two theoretical-based algorithms, i.e. the parameterized first-guess spectrum method (PFSM) (with improved tilt modulation) and quad-polarization (Q-P). These images were collocated with wave fields simulated using the third-generation numeric wave model WAVEWATCH-III (WW3) and measurements from the Haiyang-2B (HY-2B) altimeter. A comparison of the HY-2B winds with the wind speeds generated by the geophysical model function (GMF) CMOD5.N showed a 3.36 m/s root mean square error (RMSE) with a correlation (COR) of 0.66. The retrieved significant wave height (SWH) validated against the WW3-simulated results had a 0.50 m RMSE using PFSM and 0.91 m RMSE with the Q-P algorithm. These results show that PFSM is suitable for wave retrieval from GF-3 SAR images. We also used PFSM to investigate the characteristics of the wave spectrum in the presence of sea ice. Although the analysis concludes that GF-3 SAR has the capability for wave monitoring in Arctic Ocean due to the high spatial resolution of SAR-derived wave spectra, an optimal wave retrieval algorithm needs to be developed for improving the retrieval accuracy. [ABSTRACT FROM AUTHOR]

Background. The aim of this study was to apply bioinformatic analysis to develop a robust miRNA signature and construct a nomogram model in uveal melanoma (UM) to improve prognosis prediction. Methods. miRNA and mRNA sequencing data for 80 UM patients were obtained from The Cancer Genome Atlas (TCGA) database. The patients were further randomly assigned to a training set (n = 40, used to identify key miRNAs) and a testing set (n = 40, used to internally verify the signature). Then, miRNAs data of GSE84976 and GSE68828 were downloaded from Gene Expression Omnibus (GEO) database for outside verification. Combining univariate analysis and LASSO methods for identifying a robust miRNA biomarker in training set and the signature was validated in testing set and outside dataset. A prognostic nomogram was constructed and combined with decision curve as well as reduction curve analyses to assess the application of clinical usefulness. Finally, we constructed a miRNA-mRNA regulator network in UM and conducted pathway enrichment analysis according to the mRNAs in the network. Results. In total, a 3-miRNA was identified and validated that can robustly predict UM patients' survival. According to univariate and multivariate cox analyses, age at diagnosis, tumor node metastasis (TNM) classification, stage, and the 3-miRNA signature significantly correlated with the survival outcomes. These characteristics were used to establish nomogram. The nomogram worked well for predicting 1 and 3 years of overall survival time. The decision curve of nomogram revealed a good clinical usefulness of our nomogram. What's more, a miRNA-mRNA network was constructed. Pathway enrichment showed that this network was largely involved in mRNA processing, the mRNA surveillance pathway, the spliceosome, and so on. Conclusions. We developed a 3-miRNA biomarker and constructed a prognostic nomogram, which may afford a quantitative tool for predicting the survival of UM. Our finding also provided some new potential targets for the treatment of UM. [ABSTRACT FROM AUTHOR]

New technologies and innovative business models are leading to connected, shared, autonomous, and electric solutions for the tomorrow of urban transport and logistics (UTL). The efficiency and sustainability of these solutions are greatly empowered by the capability of understanding and utilizing the tremendous amount of data generated by passengers, drivers, and vehicles. In this study, we first review the innovative applications in UTL and several related research areas in the operations management (OM)/operations research (OR) literature. We then highlight the sources, types, and uses of data in different applications. We further elaborate on business analytics techniques and software developed to facilitate the planning and management of UTL systems. Finally, we conclude the paper by reflecting on the emerging trends and potential research directions in data‐driven decision making for smart UTL. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "ALKBH5-mediated m6A modification of IL-11 drives macrophage-to-myofibroblast transition and pathological cardiac fibrosis in mice" published in Nature Communications. The correction addresses an error in the author affiliation, where the author Wei Lu was incorrectly associated with affiliation '2' instead of affiliation '3'. The correction has been made in both the HTML and PDF versions of the article. The authors of the article are Tao Zhuang, Mei-Hua Chen, Ruo-Xi Wu, Jing Wang, Xi-De Hu, Ting Meng, Ai-Hua Wu, Yan Li, Yong-Feng Yang, Yu Lei, Dong-Hua Hu, Yan-Xiu Li, Li Zhang, Ai-Jun Sun, Wei Lu, Guan-Nan Zhang, Jun-Li Zuo, and Cheng-Chao Ruan. [Extracted from the article]

Copyright of International Journal of Tourism Research is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Problem definition: Observing the retail industry inevitably evolving into omnichannel, we study an offline-channel planning problem that helps an omnichannel retailer make store location and location-dependent assortment decisions in its offline channel to maximize profit across both online and offline channels, given that customers' purchase decisions depend on not only their preferences across products but also, their valuation discrepancies across channels, as well as the hassle costs incurred. Academic/practical relevance: The proposed model and the solution approach extend the literature on retail-channel management, omnichannel assortment planning, and the broader field of smart retailing/cities. Methodology: We derive parameterized models to capture customers' channel choice and product choice behaviors and customize a corresponding parameter estimation approach employing the expectation-maximization method. To solve the proposed optimization model, we develop a tractable mixed integer second-order conic programming reformulation and explore the structural properties of the reformulation to derive strengthening cuts in closed form. Results: We numerically validate the efficacy of the proposed solution approach and demonstrate the parameter estimation approach. We further draw managerial insights from the numerical studies using real data sets. Managerial implications: We verify that omnichannel retailers should provide location-dependent offline assortments. In addition, our benchmark studies reveal the necessity and significance of jointly determining offline store locations and assortments, as well as of incorporating the online channel while making offline-channel planning decisions. [ABSTRACT FROM AUTHOR]

Problem definition: We study an urban bike lane planning problem based on the fine-grained bike trajectory data, which are made available by smart city infrastructure, such as bike-sharing systems. The key decision is where to build bike lanes in the existing road network. Academic/practical relevance: As bike-sharing systems become widespread in the metropolitan areas over the world, bike lanes are being planned and constructed by many municipal governments to promote cycling and protect cyclists. Traditional bike lane planning approaches often rely on surveys and heuristics. We develop a general and novel optimization framework to guide the bike lane planning from bike trajectories. Methodology: We formalize the bike lane planning problem in view of the cyclists' utility functions and derive an integer optimization model to maximize the utility. To capture cyclists' route choices, we develop a bilevel program based on the Multinomial Logit model. Results: We derive structural properties about the base model and prove that the Lagrangian dual of the bike lane planning model is polynomial-time solvable. Furthermore, we reformulate the route-choice-based planning model as a mixed-integer linear program using a linear approximation scheme. We develop tractable formulations and efficient algorithms to solve the large-scale optimization problem. Managerial implications: Via a real-world case study with a city government, we demonstrate the efficiency of the proposed algorithms and quantify the trade-off between the coverage of bike trips and continuity of bike lanes. We show how the network topology evolves according to the utility functions and highlight the importance of understanding cyclists' route choices. The proposed framework drives the data-driven urban-planning scheme in smart city operations management. [ABSTRACT FROM AUTHOR]

A high performance liquid chromatographic (HPLC) method was developed for simultaneous determination of seven antioxidants in plastic eye drops bottles and their migration in pharmaceuticals. The samples were ultrasonically extracted and separated by Shim-pack GIST C18 chromatographic column with methanol-water as mobile phase for gradient elution. The flow rate is 1.0 mL/min, the column temperature is 35 °C, the detection wavelength is 276 nm, and the injection volume is 10 μL. The results show that the seven antioxidants have a good linear relationship in the corresponding mass concentration range (R²=0.999 9). The detection limit is 0.15~0.31 μg/mL, and the lower limit of quantification is 0.53°C1.04 μg/mL. The recoveries of extraction test and migration test are 87.02%*105.28% and 84.79%~104.77%, respectively. The relative standard deviation (RSD) of each recovery is not more than 4.80%. Six antioxidants are detected in plastic medicinal eye drops bottles with the content of 3.86~203.54 μg/g. Antioxidant is not detected in migration test eye drops. The method is simple, accurate and reliable, and can be used to investigate the antioxidants in plastic medicinal eye drops bottles and their migration in medicinal. [ABSTRACT FROM AUTHOR]

When supply disruptions occur, firms want to employ an effective pricing strategy to reduce losses. However, firms typically do not know precisely how customers will react to price changes in the short term, during a disruption. In this article, we investigate the customer's order variability and the firm's profit under several representative heuristic pricing strategies, including no change at all (fixed pricing strategy), changing the price only (naive pricing strategy), and adjusting the belief and price simultaneously (one‐period correction [1PC] and regression pricing strategies). We show that the fixed pricing strategy creates the most stable customer order process, but it brings lower profit than the naive pricing strategy in most cases. The 1PC pricing strategy produces a more volatile customer order process and smaller profit than the naive one does. Although the regression pricing strategy is a more advanced approach, it leads to lower profit and greater customer order variability than the naive pricing strategy (but the opposite when compared to the 1PC strategy). We conclude that (i) completely eliminating the customer order variability by employing a fixed pricing strategy is not advisable and adjusting the price to match supply with demand is necessary to improve the profit; (ii) frequently adjusting the belief about customer behaviors under imperfect information may increase the customer's order variability and reduce the firm's profit. The conclusions are robust to the inventory assumption (i.e., without or with inventory carryover) and the firm's objective (i.e., market clearance or profit maximization). [ABSTRACT FROM AUTHOR]

The variability in strata of foundation soil in marine environments makes it tedious to design foundations for offshore structures. Hence, it is essential to investigate and evaluate the strength properties of this type of soil. This study investigates the variability of the soil strata (which is quantified by the index of the mixing degree between coarse and fine particles) and its influence on the stability of the soil by mixing coarse and fine particles at varying proportions. A series of discrete element method triaxial shear tests were conducted on binary geotechnical mixtures with a varying proportion of coarse content (25%, 50% and 75%) and different mixing degrees (ranging from 0.0 to 1.0). The macroscopic results show that the peak shear strength increases with an increase in mixing degree, and the increase is more obvious with increasing coarse content, while the critical shear strength is independent of the mixing degree. The main evaluation of the number, mean normal force and distribution of the coarse–fine (cf) contact helps to clarify the meso-mechanisms that result in the variations in peak shear strength and critical shear strength with mixing degree. The increase in the peak strength may primarily be due to the increased number and globalized distribution of coarse–fine contact. However, the decreased contact force of coarse–fine contact counterbalances the strength gain due to the increased number and globalized distribution, which maintain the stability of the critical strength. [ABSTRACT FROM AUTHOR]

The boronized Ti6Al4V/HA composite is deemed to be an important biomaterial because of its potential remarkable mechanical and biological properties. This paper reports the osteogenesis performance of the boronized Ti6Al4V/HA composite, which was prepared by microwave sintering of powders of Ti6Al4V, hydroxyapatite (HA), and TiB2 in high-purity Ar gas at 1050 °C for 30 min, as dental implant based on both cell experiments in vitro and animal experiments in vivo. The comparison between the boronized Ti6Al4V/HA composite and Ti, Ti6Al4V, and boronized Ti6Al4V in the terms of adhesion, proliferation, alkaline phosphate (ALP) activity, and mineralization of MG-63 cells on their surfaces confirmed that the composite exhibited the best inductive osteogenesis potential. It exerted a more significant effect on promoting the early osteogenic differentiation of osteoblasts and exhibited the maximum optical density (OD) value in the MTT assay and the highest levels of ALP activity and mineralization ability, primarily ascribed to its bioactive HA component, porous structure, and relatively rough micro-morphology. The in vivo study in rabbits based on the micro-computed tomography (micro-CT) analysis, histological and histomorphometric evaluation, and biomechanical testing further confirmed that the boronized Ti6Al4V/HA composite had the highest new bone formation potential and the best osseointegration property after implantation for up to 12 weeks, mainly revealed by the measured values of bone volume fraction, bone implant contact, and maximum push-out force which, for example, reached 48.64%, 61%, and 150.3 ± 6.07 N at the 12th week. Owing to these inspiring features, it can serve as a highly promising dental implant. [ABSTRACT FROM AUTHOR]

Multiple synthetic beacons are required for atmospheric-turbulence compensation in an extended-field-of-view multi-conjugate adaptive optics (MCAO) telescope. In this paper, we report on the first successful implementation of a microsecond-pulse sodium guidestars constellation laser system, based on a small angle precise polarized combining and splitting technology. At Lijiang Observatory of China, four-ways ∼20 W yellow laser beam with kHz repetition-rate and hundred- μ s pulse width were projected into the sky through one small-aperture launching telescope, and generated a distinctive four-point grouping on a field of view of 40″ with variable configurations of linear, parallelogram, rhomboid and square. The sodium return signal could easily avoid Rayleigh light interference by the pulse synchro controlling technology delivering a higher spatial resolution. Moreover, the increase in return photons for alternated circularly and alternated linearly polarized light has been investigated. We believe that the above results could serve as a future reference for the MCAO system on large-aperture telescopes worldwide. [ABSTRACT FROM AUTHOR]

BACKGROUND: Although parasitoids can precisely locate hidden gall‐inducing insects, the host location mechanism is unknown. In this study, our aim was to clarify the olfactory responses of the parasitoid Quadrastichus mendeli to eucalyptus volatiles induced by the gall wasp Leptocybe invasa. RESULTS: Q. mendeli preferred volatiles from gall‐damaged plants compared with those produced by mechanically damaged and undamaged plants. Coupled gas chromatographic–electroantennographic detection results demonstrated that 3‐carene, decanal, d‐limonene, ethanone,1‐(4‐ethylphenyl)‐, p‐cymene and benzene,1‐methyl‐4‐(1‐methylpropyl)‐ from DH 201‐2 (Eucalyptus grandis × Eucalyptus tereticornis) elicited significant antennal responses in Q. mendeli in all treatments. Q. mendeli was repelled by decanal and d‐limonene and was attracted to 3‐carene, benzene,1‐methyl‐4‐(1‐methylpropyl)‐, ethanone,1‐(4‐ethylphenyl) and p‐cymene. Quaternary blends containing 3‐carene, p‐cymene, benzene,1‐methyl‐4‐(1‐methylpropyl)‐ and ethanone,1‐(4‐ethylphenyl)‐ at a ratio of 1:1:1:1 were attractive to Q. mendeli. However, quaternary blends with added decanal and d‐limonene alone or both together induced significant repellence in Q. mendeli. CONCLUSION: Our report is the first to demonstrate that volatiles produced by galls induced by L. invasa are attractive to Q. mendeli, which suggests that this parasitoid could utilize herbivore‐induced plant volatiles to locate its host. The results are beneficial for understanding the function of plant volatiles in host searching by parasitoids of gall‐forming insect pests. © 2022 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

We demonstrated a high-peak-power acousto-optic Q-switched Nd:YAG laser emitting at 1338 nm. The resonator adopted a symmetrical convex-convex cavity with a two-rod configuration, which is side-pumped by a $\mu $ s long pulse laser diode. At the beginning, the free running mode and Q-switched mode operated with single-wavelength emission at 1319 nm and dual-wavelength emission at 1319 and 1338 nm, respectively. By means of using a 8 mm-thick birefringence filter to increase the intra-cavity loss at 1319 nm, single wavelength operation of 1338 nm was achieved with spectral width of 0.31 nm. Under the pump power of 390 W, the Q-switched laser delivers 28.7 W of average output power with an optical conversion efficiency of 7.4%. The pulse width was measured to be 124 ns with a repetition rate of 400 Hz, and the corresponding peak power is up to 0.58 MW. [ABSTRACT FROM AUTHOR]

Problem definition: Providing fast and reliable delivery services is key to running a successful online retail business. To achieve a better delivery time guarantee policy, we study how to estimate and promise delivery time for new customer orders in real time. Academic/practical relevance: Delivery time promising is critical to managing customer expectations and improving customer satisfaction. Simply overpromising or underpromising is undesirable because of the negative impacts on short-/long-term sales. To the best of our knowledge, we are the first to develop a data-driven framework to predict the distribution of order delivery time and set promised delivery time to customers in a cost-effective way. Methodology: We apply and extend tree-based models to generate distributional forecasts by exploiting the complicated relationship between delivery time and relevant operational predictors. To account for the cost-sensitive decision-making problem structure, we develop a new split rule for quantile regression forests that incorporates an asymmetric loss function in split point selection. We further propose a cost-sensitive decision rule to decide the promised delivery day from the predicted distribution. Results: Our decision rule is proven to be optimal given certain cost structures. Tested on a real-world data set shared from JD.com, our proposed machine learning–based models deliver superior forecasting performance. In addition, we demonstrate that our framework has the potential to provide better promised delivery time in terms of sales, cost, and accuracy as compared with the conventional promised time set by JD.com. Specifically, our simulation results indicate that the proposed delivery time promise policy can improve the sales volume by 6.1% over the current policy. Managerial implications: Through a more accurate estimation of the delivery time distribution, online retailers can strategically set the promised time to maximize customer satisfaction and boost sales. Our data-driven framework reveals the importance of modeling fulfillment operations in delivery time forecasting and integrating the decision-making problem structure with the forecasting model. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Central South University is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We study a risk‐averse newsvendor problem where demand distribution is unknown. The focal product is new, and only the historical demand information of related products is available. The newsvendor aims to maximize its expected profit subject to a profit risk constraint. We develop a model with a value‐at‐risk constraint and propose a data‐driven approximation to the theoretical risk‐averse newsvendor model. Specifically, we use machine learning methods to weight the similarity between the new product and the previous ones based on covariates. The sample‐dependent weights are then embedded to approximate the expected profit and the profit risk constraint. We show that the data‐driven risk‐averse newsvendor solution entails a closed‐form quantile structure and can be efficiently computed. Finally, we prove that this data‐driven solution is asymptotically optimal. Experiments based on real data and synthetic data demonstrate the effectiveness of our approach. We observe that under data‐driven decision‐making, the average realized profit may benefit from a stronger risk aversion, contrary to that in the theoretical risk‐averse newsvendor model. In fact, even a risk‐neutral newsvendor can benefit from incorporating a risk constraint under data‐driven decision‐making. This situation is due to the value‐at‐risk constraint that effectively plays a regularizing role (via reducing the variance of order quantities) in mitigating issues of data‐driven decision‐making, such as sampling error and model misspecification. However, the above‐mentioned effects diminish with the increase in the size of the training data set, as the asymptotic optimality result implies. [ABSTRACT FROM AUTHOR]