The environmental footprint of international business in Africa; The role of natural resources

This paper examines whether the effect of foreign direct investment and trade on the environment differs between natural and non-natural resource countries of Africa. We employ robust econometric modelings such as co-integration, Fully Modified Ordinary Least Square (FMOLS), and causality techniques on 46 African countries between 1985 and 2014. Consistent with the pollution halo hypothesis, we find that both foreign direct investment and trade have a positive impact on non-natural resource-rich countries. On the contrary, in line with the pollution haven argument, we find that FDI and trade to natural resource-rich countries are associated with low environmental quality. Our results, therefore, suggest that non-natural resources-rich countries benefit from FDI and trade via technological transfer from developed countries

Clustering-Based Multi-instance Learning Network for Whole Slide Image Classification

International audienceAutomated and accurate classification of Whole Slide Image (WSI) is of great significance for the early diagnosis and treatment of cancer, which can be realized by Multi-Instance Learning (MIL). However, the current MIL method easily suffers from over-fitting due to the weak supervision of slide-level labels. In addition, it is difficult to distinguish discriminative instances in a WSI bag in the absence of pixel-level annotations. To address these problems, we propose a novel Clustering-Based Multi-Instance Learning method (CBMIL) for WSI classification. The CBMIL constructs feature set from phenotypic clusters to augment data for training the aggregation network. Meanwhile, a contrastive learning task is incorporated into the CBMIL for multi-task learning, which helps to regularize the feature aggregation process. In addition, the centroid of each phenotypic cluster is updated by the model, and the weights of the WSI patches are calculated by their similarity to the phenotypic centroids to highlight the significant patches. Our method is evaluated on two public WSI datasets (CAMELYON16 and TCGA-Lung) for binary tumor and cancer sub-types classification and achieves better performance and great interpretability compared with the state-of-the-art methods. The code is available at: https://github.com/wwu98934/CBMIL

X-ray photoelectron spectroscopy studies of indium-tin-oxide treated via oxygen plasma immersion ion implantation

Surface modification was performed on the indium-tin-oxide (ITO) thin films by oxygen inductive coupling plasma (O-ICP) and oxygen plasma immersion ion implantation (O-PIII). The electronic states of ITO surfaces were characterized by X-ray photoelectron spectroscopy (XPS). The observed peak shifts of O 1s, In 3d5/2 and Sn d5/2 core levels showed that the work function of ITO can be further enhanced by O-PIII treatment, compared with that of untreated and O-ICP treated surfaces. The deconvolution of O 1s spectrum and calculation of stoichiometry showed that the work function improvement should be attributed to the increase of effective oxygen content, namely, the elimination of oxygen vacancies. In addition, the measurement of Kelvin probe confirmed that an increment of the ITO work function by 1.1 eV was obtained on O-PIII treated sample and the results sustained our proposal

Improved U-net network asphalt pavement crack detection method.

Road crack detection is one of the important parts of road safety detection. Aiming at the problems such as weak segmentation effect of basic U-Net on pavement crack, insufficient precision of crack contour segmentation, difficult to identify narrow crack and low segmentation accuracy, this paper proposes an improved U-net network pavement crack segmentation method. VGG16 and Up_Conv (Upsampling Convolution) modules are introduced as backbone network and feature enhancement network respectively, and the more abstract features in the image are extracted by using the Block depth separable convolution blocks, and the multi-scale features are captured and enhanced by higher level semantic information to improve the recognition accuracy of narrow cracks in the road surface. The improved network embedded the Ca(Channel Attention) attention mechanism in U-net's jump connection to enhance the crack portion to suppress background noise. At the same time, DG_Conv(Depthwise GSConv Convolution) module and UnetUp(Unet Upsampling) module are added in the decoding part to extract richer features through more convolutional layers in the network, so that the model pays more attention to the detailed part of the crack, so the segmentation accuracy can be improved. In order to verify the model's ability to detect cracks in complex backgrounds, experiments were carried out on CFD and Deepcrack datasets. The experimental results show that compared with the traditional U-net network F1-score and mIoU have increased by 13.6% and 9.9% respectively. Superior to advanced models such as U-net, Segnet and Linknet in accuracy and generalization ability, the improved model provides a new method for asphalt pavement crack detection. The model is more conducive to practical application and ground deployment, and can be applied in road maintenance projects

Data_Sheet_1_The effectiveness and safety of acupuncture for chemotherapy-induced peripheral neuropathy: A systematic review and meta-analysis.docx

ObjectivesThis systematic review and meta-analysis aimed to evaluate the effectiveness and safety of acupuncture on chemotherapy-induced peripheral neuropathy (CIPN).MethodsWe searched for relevant randomized controlled trials (RCTs) in PubMed, Cochrane Library, and Embase databases from their inception to 1 April 2022. The Functional Assessment of Cancer Therapy/Gynecologic Oncology Group-Neurotoxicity (FACT/GOG-Ntx), Brief Pain Inventory-Short Form (BPI-SF), the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-Core30 (EORTC QLQ-C30), Numerical Rating Scale (NRS), and adverse events were the outcome measures. All studies had at least one of these outcome measures. Mean differences (MDs) with 95% confidence intervals (CIs) were assessed in the meta-analysis using the RevMan 5.3 software.ResultsFive studies were included in the analysis. The results showed that acupuncture and placebo acupuncture were not significantly different in reducing chemotherapy-induced neurotoxicity and functional disability (random-effects estimates; MD: 4.30; 95% CI: −0.85~9.45; P = 0.10; I2 = 74%). Acupuncture was better than placebo acupuncture in reducing pain severity and pain interference with patients' daily function (fixed-effect estimates; MD: −1.14; 95% CI: 1.87 to −0.42; P = 0.002; I2 = 13%). Acupuncture was not significantly different from placebo acupuncture in relieving CIPN symptoms (MD: −0.81; 95% CI: −2.02 to 0.40, P = 0.19). Acupuncture improved quality of life better than placebo acupuncture (MD: 10.10; 95% CI: 12.34 to 17.86, P = 0.01). No severe adverse events were recorded in all five studies.ConclusionThis meta-analysis suggests that acupuncture may be more effective and safer in reducing pain severity and pain interference with patients' daily function than placebo acupuncture. Additionally, acupuncture may improve the quality of life of patients with CIPN. However, large sample size studies are needed to confirm this conclusion.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=324930, identifier: CRD42022324930.</p

Electrical characteristics of monofilaments in dielectric barrier discharge plasma jets at atmospheric pressure

Electrical characteristics of monofilaments in dielectric barrier discharge plasma jets were investigated at atmospheric pressure. It is found that the shapes of monofilaments, the discharge current, the number of discharges, the breakdown voltage and the input power are dependent not only on the Ar flow rate but also on the applied voltage and exhibit complicated behaviors. Especially, the discharge current is irregular and has the oscillating pulses with positive and negative polarities. The influence of wall charges on the above parameters was discussed

Tim-3 protects against cisplatin nephrotoxicity by inhibiting NF-κB-mediated inflammation

Abstract The impact of Tim-3 (T cell immunoglobulin and mucin domain-containing protein 3) on cisplatin-induced acute kidney injury was investigated in this study. Cisplatin-induced Tim-3 expression in mice kidney tissues and proximal tubule-derived BUMPT cells in a time-dependent manner. Compared with wild-type mice, Tim-3 knockout mice have higher levels of serum creatinine and urea nitrogen, enhanced TUNEL staining signals, more severe 8-OHdG (8-hydroxy-2’ -deoxyguanosine) accumulation, and increased cleavage of caspase 3. The purified soluble Tim-3 (sTim-3) protein was used to intervene in cisplatin-stimulated BUMPT cells by competitively binding to the Tim-3 ligand. sTim-3 obviously increased the cisplatin-induced cell apoptosis. Under cisplatin treatment conditions, Tim-3 knockout or sTim-3 promoted the expression of TNF-α (tumor necrosis factor-alpha) and IL-1β (Interleukin-1 beta) and inhibited the expression of IL-10 (interleukin-10). NF-κB (nuclear factor kappa light chain enhancer of activated B cells) P65 inhibitor PDTC or TPCA1 lowed the increased levels of creatinine and BUN (blood urea nitrogen) in cisplatin-treated Tim-3 knockout mice serum and the increased cleavage of caspase 3 in sTim-3 and cisplatin-treated BUMPT cells. Moreover, sTim-3 enhanced mitochondrial oxidative stress in cisplatin-induced BUMPT cells, which can be mitigated by PDTC. These data indicate that Tim-3 may protect against renal injury by inhibiting NF-κB-mediated inflammation and oxidative stress