Riverside landslides present a significant geohazard globally, posing threats to infrastructure and human lives. In line with the United Nations’ Sustainable Development Goals (SDGs), which aim to address global challenges, professionals in the field have developed diverse methodologies to analyze, assess, and predict the occurrence of landslides, including quantitative, qualitative, and semi-quantitative approaches. With the advent of computer programs, quantitative techniques have gained prominence, with computational intelligence and knowledge-based methods like artificial neural networks (ANNs) achieving remarkable success in landslide susceptibility assessments. This article offers a comprehensive review of the literature concerning the utilization of ANNs for landslide susceptibility assessment, focusing specifically on riverside areas, in alignment with the SDGs. Through a systematic search and analysis of various references, it has become evident that ANNs have emerged as the preferred method for these assessments, surpassing traditional approaches. The application of ANNs aligns with the SDGs, particularly Goal 11: Sustainable Cities and Communities, which emphasizes the importance of inclusive, safe, resilient, and sustainable urban environments. By effectively assessing riverside landslide susceptibility using ANNs, communities can better manage risks and enhance the resilience of cities and communities to geohazards. While the number of ANN-based studies in landslide susceptibility modeling has grown in recent years, the overarching objective remains consistent: researchers strive to develop more accurate and detailed procedures. By leveraging the power of ANNs and incorporating relevant SDGs, this survey focuses on the most commonly employed neural network methods for riverside landslide susceptibility mapping, contributing to the overall SDG agenda of promoting sustainable development, resilience, and disaster risk reduction. Through the integration of ANNs in riverside landslide susceptibility assessments, in line with the SDGs, this review aims to advance our knowledge and understanding of this field. By providing insights into the effectiveness of ANNs and their alignment with the SDGs, this research contributes to the development of improved risk management strategies, sustainable urban planning, and resilient communities in the face of riverside landslides.

A prospective randomized clinical trial was carried out to observe the analgesic efficacy of ropivacaine for postoperative pain following thoracolumbar spinal surgery. Seventy-one patients with elective posterior thoracolumbar spinal surgery were randomly divided into two groups. Local group received 0.33 % ropivacaine by pump through the wound, and intravenous group received flurbiprofen axetil, pentazocine and palonosetron via intravenous pump. We evaluated the level of pain, the incidence of adverse reactions at 2, 4, 6, 12, 24, 36 and 48 h after operation, and the occurrence of chronic pain 3 months later. There were no significant differences in the pain level between the two groups. However, the incidence of nausea, vomiting and chronic pain was significantly lower in the local group. Our results showed that local infusion of ropivacaine achieved similar analgesic effects to intravenous delivery of analgesic drugs, but significantly reduced incidence of nausea, vomiting and chronic pain.

Rapid urban development and increase in construction have significantly altered the surface coverage of cities, resulting in a rise in impervious surfaces such as roofs, streets, and pavements. These changes act as barriers against rainwater infiltration into the soil, leading to a substantial increase in surface runoff. Managing surface runoff has become a critical task in civil engineering and urban planning, as it can mitigate damage and provide opportunities for utilizing excess water. However, traditional flood control and guidance systems tend to be extensive and expensive, prompting researchers to explore cost-effective alternatives that consider all design parameters and variables. In this research, we propose an innovative approach that combines the NSDE (non-dominated sorting differential evolution) metaheuristic algorithm as an optimizer with the SWMM (storm water management model) as a simulator. The objective is to design efficient surface runoff collection networks by thoroughly investigating their hydraulic behaviors. This study focuses on the Chitgar watershed in Tehran, Iran, utilizing the SWMM model and NSDE multi-objective metaheuristic algorithm to determine the optimal dimensions of the channel and its intersecting structures. The aim is to minimize costs and reduce water leakage from the network. A comparison is made between the optimized design results and the existing network plan (without any design modifications). The analysis reveals substantial reductions in water leakage for all three design scenarios: a 7.66% reduction when considering only bridges, a 7.35% reduction with only the canal, and an impressive 95.26% reduction when both the canal and bridges are incorporated. These findings demonstrate the superiority of the optimized designs in terms of cost-effectiveness and the efficient management of surface runoff.

This study considers two-stage bilateral matching of teams and scientific and technological talents in new R&D organizations and proposes a two-stage dual-objective bilateral matching method based on prospect theory. The matching of teams and scientific and technological talent in new R&D institutions is divided into two stages: elimination matching in the first stage and selection matching in the second stage. In the first stage, the evaluation index of the team to talent and the cost index of talent are constructed, the dual reference points of peer and expectation are set for evaluating talent, and the bottom-line reference points are set for talent cost. The comprehensive prospect value in the first stage is calculated based on prospect theory, and the matching in the first stage is completed based on the dual-objective optimization model with the highest evaluation value and the lowest cost value. In the second stage, using the matching results of the first stage, the team evaluates the talent again, while the talent ranks the team to obtain the satisfaction value, and completes the second stage of bilateral matching based on prospect theory and the dual-objective optimization model with the highest evaluation value and the highest satisfaction value. Finally, a case study and method comparison show that the proposed method is feasible and effective.

An alternating-direction implicit finite-difference (ADI-FDTD) based time-domain inverse algorithm is proposed in this paper. The imaging algorithm based on forward-backward time-stepping (FBTS) method. By comparing the processing results, it was found that the proposed ADI-FDTD method can substitute for the conventional finite-difference time-domain (FDTD) method, strongly validating the former's usefulness and accuracy. Moreover, processing time can be reduced significantly for microwave tomography.

Backgroud: Waldenström macroglobulinemia (WM) is an uncommon indolent B cell non-Hodgkin lymphoma, which has heterogeneous clinical presentations and indications for treatment. Mostly the choice of first-line therapy is based on the individual patient's characteristic and indications for treatment. In China, previous studies on WM are mostly from single-center with small sample size, limiting the information available on treatment and outcome patterns. To address this knowledge gap, we present data from an analysis based on a nationwide multicenter registry with 17-years follow-up. Our study focuses on the clinical presentation, first-line therapies, as well as outcome and prognosis of WM in China. Methods: Patients diagnosed with WM between January 2003 and December 2019 at 35 academic hospitals in China, which have been entered in the database of the China Waldenström macroglobulinemia Registration (CWMG), were included in this retrospective study. Data including baseline clinical features, symptoms requiring treatment, treatment and survival were collected. The overall survival (OS) was defined as the duration from the diagnosis of WM to the date of death or last follow-up. Results: Overall 1141 patients were enrolled, 829 patients were male (72.7%), with a male-to-female ratio of 2.7:1. The median age at diagnosis was 64 years (range, 29-89 years), which 472 patients (41.4%) were older than 65 years, and 126 patients (11.0%) were older than 75 years. The patients' family histories included 6 WM and 4 other lymphoproliferative disorders. Symptoms leading to treatment initiation including anemia in 828 patients (72.6%), organomegaly in 441 patients (38.7%), thrombocytopenia in 302 (26.5%), neutropenia in 246 (21.6%), constitutional symptoms in 203 (17.8%), Bing-Neel syndrome in 13 (1.1%), IgM-related symptoms in including secondary amyloidosis in 32 (2.8%), secondary autoimmune hemolysis in 25 (2.2%), peripheral neuropathy in 23 (2.0%), secondary cold agglutinin disease in 21 (1.8%), secondary cryoglobulinemia in 11 (1.0%). At the time of diagnosis, 1125 patients had full information for IPSS-WM risk stratification. Among them, 194 patients (17.2%) were classified as low risk, 436 patients (38.8%) were intermediate risk, and 495 patients (44.0%) were high risk. Overall, 734 patients had documented treatment information. 75 patients (10.2%) received monotherapy, 264 (36.0%) received chemoimmunotherapy, and 395 (53.8%) receive other combination regimens (Figure 1). The most frequently used monotherapy was chlorambucil (3.1%), followed by ibrutinib (2.9%) and rituximab (2.5%). Rituximab, cyclophosphamide and dexamethasone or prednisone (DRC or RCP) were the most frequently used chemoimmunotherapy (10.8%). Followed by rituximab plus cyclophosphasmide, vincristine/vincristine and prednisone/prednisolone (R-COP) (6.8%), R-COP plus doxorubicin/epirubicin (R-CHOP) (6.1%), rituximab plus fludarabine, cyclophosphamide (R-FC) (4.5%), rituximab plus bortezomib based regimen (3.5%). Other combination regimens including bortezomib based regimen (18.6%), FC (10.6%), CHOP (9.3%), immunomodulatory drug based regimen (5.7%), chlorambucil plus prednisone (4.4%). After a median of 23 months (range 1-201 months) follow-up, 123 patients died. The estimated 5-year OS was 74.9%. Median OS were similar among patients who received monotherapy, chemoimmunotherapy or other combination regimens. To evaluate the prognostic factors of OS using multivariate Cox regression model, age > 65 years old (P=0.011, HR 0.622, 95% CI 0.431-0.898), platelet < 100×10⁹/L (P=0.006, HR 0.570, 95% CI 0.381-0.853), serum albumin <3.5 g/dl (P=0.020, HR 0.582, 95% CI 0.369-0.918), β-2 microglobulin concentration ≥4 mg/L (P=0.019, HR 0.630, 95% CI 0.429-0.926), LDH≥250 IU/L (P=0.016, HR 0.538, 95% CI 0.326-0.890) and secondary amyloidosis (P<0.001, HR 0.277, 95% CI 0.137-0.562) at baseline had significantly shorter OS . Conclusion: Frontline treatment choices of WM are wide heterogeneity due to various clinical presentations and the rarity of the disease. Old age, low platelet, low albumin, high β-2 microglobulin, high LDH and secondary amyloidosis indicate worse prognosis in WM. These findings may provide guidance for management of WM and better prognostic stratification of risk-adapted treatment strategies.