Due-Window Assignment and Scheduling with Multiple Rate-Modifying Activities under the Effects of Deterioration and Learning

This paper discusses due-window assignment and scheduling with multiple rate-modifying activities. Multiple types of rate-modifying activities are allowed to perform on a single machine. The learning effect and job deterioration are also integrated concurrently into the problem which makes the problem more realistic. The objective is to find jointly the optimal location to perform multiple rate-modifying activities, the optimal job sequence, and the optimal location and size of the due window to minimize the total earliness, tardiness, and due-window-related costs. We propose polynomial time algorithms for all the cases of the problem under study

EVNet: An Explainable Deep Network for Dimension Reduction

Dimension reduction (DR) is commonly utilized to capture the intrinsic structure and transform high-dimensional data into low-dimensional space while retaining meaningful properties of the original data. It is used in various applications, such as image recognition, single-cell sequencing analysis, and biomarker discovery. However, contemporary parametric-free and parametric DR techniques suffer from several significant shortcomings, such as the inability to preserve global and local features and the pool generalization performance. On the other hand, regarding explainability, it is crucial to comprehend the embedding process, especially the contribution of each part to the embedding process, while understanding how each feature affects the embedding results that identify critical components and help diagnose the embedding process. To address these problems, we have developed a deep neural network method called EVNet, which provides not only excellent performance in structural maintainability but also explainability to the DR therein. EVNet starts with data augmentation and a manifold-based loss function to improve embedding performance. The explanation is based on saliency maps and aims to examine the trained EVNet parameters and contributions of components during the embedding process. The proposed techniques are integrated with a visual interface to help the user to adjust EVNet to achieve better DR performance and explainability. The interactive visual interface makes it easier to illustrate the data features, compare different DR techniques, and investigate DR. An in-depth experimental comparison shows that EVNet consistently outperforms the state-of-the-art methods in both performance measures and explainability.Comment: 18 pages, 15 figures, accepted by TVC

Prediction of high-Tc superconductivity in ternary lanthanum borohydrides

The study of superconductivity in compressed hydrides is of great interest due to measurements of high critical temperatures (Tc) in the vicinity of room temperature, beginning with the observations of LaH10 at 170-190 GPa. However, the pressures required for synthesis of these high Tc superconducting hydrides currently remain extremely high. Here we show the investigation of crystal structures and superconductivity in the La-B-H system under pressure with particle-swarm intelligence structure searches methods in combination with first-principles calculations. Structures with six stoichiometries, LaBH, LaBH3, LaBH4, LaBH6, LaBH7 and LaBH8, were predicted to become stable under pressure. Remarkably, the hydrogen atoms in LaBH8 were found to bond with B atoms in a manner that is similar to that in H3S. Lattice dynamics calculations indicate that LaBH7 and LaBH8 become dynamically stable at pressures as low as 109.2 and 48.3 GPa, respectively. Moreover, the two phases were predicted to be superconducting with a critical temperature (Tc) of 93 K and 156 K at 110 GPa and 55 GPa, respectively. Our results provide guidance for future experiments targeting new hydride superconductors with both low synthesis pressures and high Tc.Comment: 16 pages, 5 figures

Phase transitions of alkaline-earth metal sulfides under pressure

We have systematically explored the crystal structures of alkaline-earth metal sulfides under pressure by using a swarm-intelligence structural prediction method. At low pressures we successfully reproduced their known structures and phase transition sequences. Under high pressure, MgS is predicted to transform from B28 to a β-NbP-type structure at 262 GPa. CaS and SrS present the same phase transition sequence, from B2 to a β-NbP-type structure, while BaS is predicted to transform to a Imma structure. The Imma structure is actually similar to the β-NbP-type structure, as it can be seen as a modulated distortion of the latter structure. The absence of any imaginary phonon mode for the predicted structures suggests that they are dynamically stable. The calculated electronic band structures and density of states reveal that all the predicted phases are metallic, except that MgS is a semiconductor. Subsequent electron-phonon coupling calculations suggest that Imma BaS is a superconductor with a low Tc of 1.32 K, while β-NbP MgS, CaS and SrS are not superconductors. The current study provides a comprehensive analysis of phase transitions for alkaline-earth metal sulfides up to 300 GPa and might stimulate experimental studies in the future.The work was supported by National Natural Science Foundation of China (91963115, 52022089), the PhD Foundation by Yanshan University (B970), Science and Technology Project of Hebei Education Department (Grant No. QN2021136). A.B. acknowledges financial support from the Spanish Ministry of Science and Innovation (PID2019-105488GB-I00).Peer reviewe

Price and service competition with maintenance service bundling

In many equipment manufacturing industries, firms compete with each other not only on products price, but also on maintenance service. More and more traditional products oriented firms are offering their customers products bundled with maintenance service (P&S bundles). In this study, we examine firms’ incentive to offer customers products bundling with long-term maintenance or repair support service in a duopoly competitive environment. When providing P&S bundles, a firm need to determine the service level (in terms of average response time guarantee for the service in this paper) to offer and needs to build a service facility to handle the maintenance service requirements. Based on the analysis of three sub-game models, we characterize the market conditions in which only one firm, both firms or neither firm will offer P&S bundles. Finally, we analyze the affects of several market factors on firms’ strategy choices

Efficacy of chimeric antigen receptor T cell therapy and autologous stem cell transplant in relapsed or refractory diffuse large B-cell lymphoma: A systematic review

BackgroundWe aimed to compare the efficacy of chimeric antigen receptor T (CAR-T) cell therapy with that of autologous stem cell transplantation (auto-HSCT) in relapsed/refractory diffuse large B cell lymphoma (R/R DLBCL).Research design and methodsWe searched eligible publications up to January 31st, 2022, in PubMed, Cochrane Library, Springer, and Scopus. A total of 16 publications with 3484 patients were independently evaluated and analyzed using STATA SE software.ResultsPatients who underwent CAR-T cell therapy showed a better overall response rate (ORR) and partial response (PR) than those treated with auto-HSCT (CAR-T vs. auto-HSCT, ORR: 80% vs. 73%, HR:0.90,95%CI:0.76-1.07,P = 0.001; PR: 20% vs. 14%, HR:0.65,95%CI:0.62-0.68,P = 0.034). No significant difference was observed in 6-month overall survival (OS) (CAR-T vs. auto-HSCT, six-month OS: 81% vs. 84%, HR:1.23,95%CI:0.63-2.38, P = 0.299), while auto-HSCT showed a favorable 1 and 2-year OS (CAR-T vs. auto-HSCT, one-year OS: 64% vs. 73%, HR:2.42,95%CI:2.27-2.79, P < 0.001; two-year OS: 54% vs. 68%, HR:1.81,95%CI:1.78-1.97, P < 0.001). Auto-HSCT also had advantages in progression-free survival (PFS) (CAR-T vs. auto-HSCT, six-month PFS: 53% vs. 76%, HR:2.81,95%CI:2.53-3.11,P < 0.001; one-year PFS: 46% vs. 61%, HR:1.84,95%CI:1.72-1.97,P < 0.001; two-year PFS: 42% vs. 54%, HR:1.62,95%CI:1.53-1.71, P < 0.001). Subgroup analysis by age, prior lines of therapy, and ECOG scores was performed to compare the efficacy of both treatment modalities.ConclusionAlthough CAR-T cell therapy showed a beneficial ORR, auto-HSCT exhibited a better long-term treatment superiority in R/R DLBCL patients. Survival outcomes were consistent across different subgroups

Identification of microtubule-associated biomarkers in diffuse large B-cell lymphoma and prognosis prediction

Background: Diffuse large B-cell lymphoma (DLBCL) is a genetically heterogeneous disease with a complicated prognosis. Even though various prognostic evaluations have been applied currently, they usually only use the clinical factors that overlook the molecular underlying DLBCL progression. Therefore, more accurate prognostic assessment needs further exploration. In the present study, we constructed a novel prognostic model based on microtubule associated genes (MAGs).Methods: A total of 33 normal controls and 1360 DLBCL samples containing gene-expression from the Gene Expression Omnibus (GEO) database were included. Subsequently, the univariate Cox, the least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis were used to select the best prognosis related genes into the MAGs model. To validate the model, Kaplan-Meier curve, and nomogram were analyzed.Results: A risk score model based on fourteen candidate MAGs (CCDC78, CD300LG, CTAG2, DYNLL2, MAPKAPK2, MREG, NME8, PGK2, RALBP1, SIGLEC1, SLC1A1, SLC39A12, TMEM63A, and WRAP73) was established. The K-M curve presented that the high-risk patients had a significantly inferior overall survival (OS) time compared to low-risk patients in training and validation datasets. Furthermore, knocking-out TMEM63A, a key gene belonging to the MAGs model, inhibited cell proliferation noticeably.Conclusion: The novel MAGs prognostic model has a well predictive capability, which may as a supplement for the current assessments. Furthermore, candidate TMEM63A gene has therapeutic target potentially in DLBCL