Location, inventory and testing decisions in closed-loop supply chains: a multimedia company

Our partnering firm is a Chinese manufacturer of multimedia products that needs guidance developing its imminent Closed-Loop Supply Chain (CLSC). To study this problem, we take into account location, inventory, and testing decisions in a CLSC setting with stochastic demands of new and time-sensitive returned products. Our analysis pays particular attention to the different roles assigned to the reverse Distribution Centers (DCs) and how each option affects the optimal CLSC design. The roles considered are collection and consolidation, additional testing tasks, and direct shipments with no reverse DCs. The problem concerning our partnering firm is formulated as a scenario-based chance-constrained mixed-integer program and it is reformulated to a conic quadratic mixed-integer program that can be solved efficiently via commercial optimization packages. The completeness of the model proposed allows us to develop a decision support tool for the firm and to offer several useful managerial insights. These insights are inferred from our computational experiments using data from the Chinese firm and a second data set based on the U.S. geography. Particularly interesting insights are related to how changes in the reverse flows can impact the forward supply chain and the inventory dynamics concerning the joint DCs.This research is partially supported by the National Natural Science Foundation of China under grants 71771135, 71371106 and 71332005

Curative effect and technical key points of laparoscopic surgery for choledochal cysts in children

ObjectiveThe purpose of this study was to investigate the curative effect of and experience with laparoscopic surgery for congenital choledochal cysts in children.MethodsThis is a retrospective analysis of 33 children diagnosed with congenital choledochal cyst in the pediatric surgery department of the Affiliated Hospital of Southwest Medical University between January 2019 and December 2021. The cohort included 8 males and 25 females aged 0.25–13.7 years (median age, 3.2 years), including 21 cases of type I and 12 cases of type IV choledochal cyst (Todani classification). Laparoscopic choledochal cyst resection and hepaticojejunostomy with Roux-en-Y anastomosis were performed in all the patients.ResultsLaparoscopy without transit opening was successfully performed in the 33 cases. The duration of the procedure was 235–460 min (mean ± SD, 316 ± 61 min), and intraoperative blood loss volume was 15–40 ml (23 ± 7.6 ml). Postoperative hospital stay was 7–14 days (9 ± 1.8 days). Postoperative biliary fistula and pancreatitis occurred in two cases each, and all four patients were successfully treated with conservative treatment. No anastomotic stenosis, delayed bleeding, cholangitis, intestinal obstruction, or other complications occurred. All the children were followed up for 2–36 months (median period, 17.2 months). The clinical symptoms disappeared, and no obvious hepatic dysfunction was found on abdominal color ultrasound and liver function examination.ConclusionLaparoscopic surgery for congenital choledochal cyst in children is safe and effective, as it is a minimally invasive surgery that is associated with a low degree of trauma and bleeding, rapid postoperative recovery, and satisfactory aesthetic appearance

Votetrust: Leveraging friend invitation graph to defend against social network sybils

Online social networks (OSNs) suffer from the creation of fake accounts that introduce fake product reviews, malware and spam. Existing defenses focus on using the social graph structure to isolate fakes. However, our work shows that Sybils could befriend a large number of real users, invalidating the assumption behind social-graph-based detection. In this paper, we present VoteTrust, a scalable defense system that further leverages user-level activities. VoteTrust models the friend invitation interactions among users as a directed, signed graph, and uses two key mechanisms to detect Sybils over the graph: a voting-based Sybil detection to find Sybils that users vote to reject, and a Sybil community detection to find other colluding Sybils around identified Sybils. Through evaluating on Renren social network, we show that VoteTrust is able to prevent Sybils from generating many unsolicited friend requests. We also deploy VoteTrust in Renen, and our real experience demonstrates that VoteTrust can detect large-scale collusion among Sybils

Crystal structure of rhodopsin bound to arrestin by femtosecond X-ray laser.

G-protein-coupled receptors (GPCRs) signal primarily through G proteins or arrestins. Arrestin binding to GPCRs blocks G protein interaction and redirects signalling to numerous G-protein-independent pathways. Here we report the crystal structure of a constitutively active form of human rhodopsin bound to a pre-activated form of the mouse visual arrestin, determined by serial femtosecond X-ray laser crystallography. Together with extensive biochemical and mutagenesis data, the structure reveals an overall architecture of the rhodopsin-arrestin assembly in which rhodopsin uses distinct structural elements, including transmembrane helix 7 and helix 8, to recruit arrestin. Correspondingly, arrestin adopts the pre-activated conformation, with a ∼20° rotation between the amino and carboxy domains, which opens up a cleft in arrestin to accommodate a short helix formed by the second intracellular loop of rhodopsin. This structure provides a basis for understanding GPCR-mediated arrestin-biased signalling and demonstrates the power of X-ray lasers for advancing the frontiers of structural biology

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Welding Distortion Prediction in 5A06 Aluminum Alloy Complex Structure via Inherent Strain Method

Finite element (FE) simulation with inherent deformation is an ideal and practical computational approach for predicting welding stress and distortion in the production of complex aluminum alloy structures. In this study, based on the thermal elasto-plastic analysis, FE models of multi-pass butt welds and T-type fillet welds were investigated to obtain the inherent strain distribution in a 5A06 aluminum alloy cylindrical structure. The angular distortion of the T-type joint was used to investigate the corresponding inherent strain mechanism. Moreover, a custom-designed experimental system was applied to clarify the magnitude of inherent deformation. With the mechanism investigation of welding-induced buckling by FE analysis using inherent deformation, an application for predicting and mitigating the welding buckling in fabrication of complex aluminum alloy structure was developed

Enhanced Catalytic Effect of Ti2CTx-MXene on Thermal Decomposition Behavior of Ammonium Perchlorate

Transition metal carbonitrides (MXenes) are promising catalysts due to their special structures. Recently, many studies have shown that MXenes have a catalytic effect on the thermal decomposition of ammonium perchlorate (AP). However, the catalytic effects have not been extensively investigated. Therefore, it is important to illustrate the catalytic mechanisms of pure MXene in AP thermal decomposition. Herein, the catalytic properties of Ti2CTx for ammonium perchlorate (AP) thermal decomposition were investigated by numerous catalytic experiments. The results showed that the high-temperature decomposition (HTD) decreased by 83 °C, and the decomposition heat of AP mixed with Ti2CTx increased by 1897.3 J/g. Moreover, the mass spectrum (MS) data showed that the NH3, H2O, O2, N2O, NO, HCl, and NO2 were formed. In addition, according to the X-ray diffraction (XRD), Raman spectrum, high-resolution transmission electron microscopy (HRTEM), selected area electron diffraction (SAED), and X-ray photoelectron spectra (XPS) results, the Ti2CTx nanosheets can adsorb the gaseous products and react with them in-situ, generating anatase-TiO2 and carbon layers. The Ti2CTx, as-resulted anatase-TiO2, and carbon can synergize and further catalyze the thermal decomposition of AP when both electron and proton transfers are accelerated during AP decomposition

A Stochastic Damage Model for Bond Stress-Slip Relationship of Rebar-Concrete Interface under Monotonic Loading

The stochastic bond stress-slip behavior is an essential topic for the rebar-concrete interface. However, few theoretical models incorporating stochastic behavior in current literature can be traced. In this paper, a stochastic damage model based on micro-mechanical approach for bond stress-slip relationship of the interface under monotonic loading was proposed. In order to describe the mechanical behaviors of the rebar-concrete interface, a microscopic damage model was proposed. By introducing a micro-element consists of parallel spring element, friction element and a switch element, the model is formulated. In order to reflect the randomness of the bond stress-slip behavior contributed by the micro-fracture in the interface, a series of paralleled micro-elements are adopted with the failure threshold of individual spring element is set as a random variable. The expression of both mean and variance for the bond stress-slip relationship was derived based on statistical damage mechanics. Furthermore, by utilizing a search heuristic global optimization algorithm (i.e., a genetic algorithm), parameters of the proposed model are able to be identified from experimental results, which a lognormal distribution has adopted. The prediction was verified against experimental results, and it reveals that the proposed model is capable of capturing the random nature of the micro-structure and characterizing the stochastic behavior