A measure of trade induced adjustment in volume and quality space.

In this paper we contribute to the literature on the measurement of international trade flows. Specifically, we combine changes in the volume and quality in matched trade changes to present a simple new index together with a geometric framework that can be used to visualise changes in quality and volume simultaneously. We illustrate the usefulness of our simple extension with data for trade between Malaysia and China between 1994 and 2004

Foreign Direct Investment in Manufacturing Sector in Malaysia

This paper analyses the determinants of foreign direct investment (FDI) in the manufacturing sector in Malaysia from eleven countries during the period 1988 to 2000. The empirical results indicate that gross domestic product, lending interest rate, labour productivity, exports to home country and imports from home country significantly influenced the level of FDI inflows into Malaysia. However, exchange rate, exchange rate variation, wage and openness index were not important in influencing FDI.foreign direct investment, manufacturing sector, International Relations/Trade,

Extending CAM-based XAI methods for Remote Sensing Imagery Segmentation

Current AI-based methods do not provide comprehensible physical interpretations of the utilized data, extracted features, and predictions/inference operations. As a result, deep learning models trained using high-resolution satellite imagery lack transparency and explainability and can be merely seen as a black box, which limits their wide-level adoption. Experts need help understanding the complex behavior of AI models and the underlying decision-making process. The explainable artificial intelligence (XAI) field is an emerging field providing means for robust, practical, and trustworthy deployment of AI models. Several XAI techniques have been proposed for image classification tasks, whereas the interpretation of image segmentation remains largely unexplored. This paper offers to bridge this gap by adapting the recent XAI classification algorithms and making them usable for muti-class image segmentation, where we mainly focus on buildings' segmentation from high-resolution satellite images. To benchmark and compare the performance of the proposed approaches, we introduce a new XAI evaluation methodology and metric based on "Entropy" to measure the model uncertainty. Conventional XAI evaluation methods rely mainly on feeding area-of-interest regions from the image back to the pre-trained (utility) model and then calculating the average change in the probability of the target class. Those evaluation metrics lack the needed robustness, and we show that using Entropy to monitor the model uncertainty in segmenting the pixels within the target class is more suitable. We hope this work will pave the way for additional XAI research for image segmentation and applications in the remote sensing discipline

Trainable Noise Model as an XAI evaluation method: application on Sobol for remote sensing image segmentation

eXplainable Artificial Intelligence (XAI) has emerged as an essential requirement when dealing with mission-critical applications, ensuring transparency and interpretability of the employed black box AI models. The significance of XAI spans various domains, from healthcare to finance, where understanding the decision-making process of deep learning algorithms is essential. Most AI-based computer vision models are often black boxes; hence, providing explainability of deep neural networks in image processing is crucial for their wide adoption and deployment in medical image analysis, autonomous driving, and remote sensing applications. Recently, several XAI methods for image classification tasks have been introduced. On the contrary, image segmentation has received comparatively less attention in the context of explainability, although it is a fundamental task in computer vision applications, especially in remote sensing. Only some research proposes gradient-based XAI algorithms for image segmentation. This paper adapts the recent gradient-free Sobol XAI method for semantic segmentation. To measure the performance of the Sobol method for segmentation, we propose a quantitative XAI evaluation method based on a learnable noise model. The main objective of this model is to induce noise on the explanation maps, where higher induced noise signifies low accuracy and vice versa. A benchmark analysis is conducted to evaluate and compare performance of three XAI methods, including Seg-Grad-CAM, Seg-Grad-CAM++ and Seg-Sobol using the proposed noise-based evaluation technique. This constitutes the first attempt to run and evaluate XAI methods using high-resolution satellite images

Economic integration and the evolution of trade: a geometric interpretation of trade measures

The increase in global trade and the ongoing erosion of trade barriers makes the analysis of trade patterns one of the key areas in international economics. Much of the post-war expansion of trade took the form of intra-industry trade (IIT). This paper presents a simple geometric tool to analyse trade patterns specifically inter and intra-industry trade and the compatibility between levels and measures of IIT. The applicability our methodology is demonstrated using the UKs trade experience during the critical period of EU integration 1988-1997

Ribonucleotide reductase inhibition restores platinum-sensitivity in platinum-resistant ovarian cancer: a Gynecologic Oncology Group Study

BACKGROUND: The potent ribonucleotide reductase (RNR) inhibitor 3-aminopyridine-2-carboxyaldehyde-thiosemicarbazone (3-AP) was tested as a chemosensitizer for restored cisplatin-mediated cytotoxicity in platinum-resistant ovarian cancer. METHODS: Preclinical in vitro platinum-resistant ovarian cancer cell survival, RNR activity, and DNA damage assays were done after cisplatin or cisplatin plus 3-AP treatments. Six women with platinum-resistant ovarian cancer underwent four-day 3-AP (96 mg/m(2), day one to four) and cisplatin (25 mg/m(2), day two and three) infusions every 21 days until disease progression or adverse effects prohibited further therapy. Pre-therapy ovarian cancer tissues were analyzed by immunohistochemistry for RNR subunit expression as an indicator of cisplatin plus 3-AP treatment response. RESULTS: 3-AP preceding cisplatin exposure in platinum-resistant ovarian cancer cells was not as effective as sequencing cisplatin plus 3-AP together in cell survival assays. Platinum-mediated DNA damage (i.e., γH2AX foci) resolved quickly after cisplatin-alone or 3-AP preceding cisplatin exposure, but persisted after a cisplatin plus 3-AP sequence. On trial, 25 four-day overlapping 3-AP and cisplatin cycles were administered to six women (median 4.2 cycles per patient). 3-AP-related methemoglobinemia (range seven to 10%) occurred in two (33%) of six women, halting trial accrual. CONCLUSIONS: When sequenced cisplatin plus 3-AP, RNR inhibition restored platinum-sensitivity in platinum-resistant ovarian cancers. 3-AP (96 mg/m(2)) infusions produced modest methemoglobinemia, the expected consequence of ribonucleotide reductase inhibitors disrupting collateral proteins containing iron. TRIAL REGISTRY: ClinicalTrials.gov NCT0008127

On the measurement of product quality in intra-industry trade: an empirical test for China

A relatively recent development in the intra-industry trade (IIT) literature is the measurement of the simultaneous import and export of quality-differentiated products, commonly known as vertical and horizontal IIT. A recent paper from Azhar and Elliott [Azhar, A. K. M. & Elliott, R. J. R. (2006), On the Measurement of Product Quality in Intra-Industry Trade, Review of World Economics, Vol 142 no 3, pp 476–495] analyses various approaches for disentangling vertical and horizontal IIT and suggests a complementary methodology. To investigate the robustness and sensitivity of the existing approaches we examine data on the nature of trade flows between China and its East Asian neighbours and show that in 2002 China tended to export low quality versions of its manufactured goods to Malaysia, Thailand and the Philippines

Structural dynamic response of an unreinforced masonry house using non-destructive forced vibration

The results of non-destructive forced vibration tests on a small-scale unreinforced masonry house with a flexible timber diaphragm are presented. The primary purpose of this study was to investigate the dynamic responses between the as-built and retrofitted structures. This includes assessment of diaphragm response, wall-diaphragm connection details, in-plane wall response, out-of-plane wall response, and the response of wall corners. The test protocols were designed to investigate two types of retrofit techniques consisting of a plywood-retrofit on the diaphragm, and a connection-retrofit between the wall and diaphragm. From the results, one can see that the natural frequency and mode shapes of the first translational mode were affected. The force transfer mechanism of the as-built structure was significantly improved after applying both retrofits whereas each technique shows distinctive enhancements on the structure overall response

Proteases of haematophagous arthropod vectors are involved in blood-feeding, yolk formation and immunity : a review

Ticks, triatomines, mosquitoes and sand flies comprise a large number of haematophagous arthropods considered vectors of human infectious diseases. While consuming blood to obtain the nutrients necessary to carry on life functions, these insects can transmit pathogenic microorganisms to the vertebrate host. Among the molecules related to the blood-feeding habit, proteases play an essential role. In this review, we provide a panorama of proteases from arthropod vectors involved in haematophagy, in digestion, in egg development and in immunity. As these molecules act in central biological processes, proteases from haematophagous vectors of infectious diseases may influence vector competence to transmit pathogens to their prey, and thus could be valuable targets for vectorial control

Photo-induced enhanced Raman spectroscopy for universal ultra-trace detection of explosives, pollutants and biomolecules

Surface-enhanced Raman spectroscopy is one of the most sensitive spectroscopic techniques available, with single-molecule detection possible on a range of noble-metal substrates. It is widely used to detect molecules that have a strong Raman response at very low concentrations. Here we present photo-induced-enhanced Raman spectroscopy, where the combination of plasmonic nanoparticles with a photo-activated substrate gives rise to large signal enhancement (an order of magnitude) for a wide range of small molecules, even those with a typically low Raman cross-section. We show that the induced chemical enhancement is due to increased electron density at the noble-metal nanoparticles, and demonstrate the universality of this system with explosives, biomolecules and organic dyes, at trace levels. Our substrates are also easy to fabricate, self-cleaning and reusable