Screening in New Credit Markets: Can Individual Lenders Infer Borrower Creditworthiness in Peer-to-Peer Lending?

The current banking crisis highlights the challenges faced in the traditional lending model, particularly in terms of screening smaller borrowers. The recent growth in online peer-to-peer lending marketplaces offers opportunities to examine different lending models that rely on screening by multiple peers. This paper evaluates the screening ability of lenders in such peer-to-peer markets. Our methodology takes advantage of the fact that lenders do not observe a borrower's true credit score but only see an aggregate credit category. We find that lenders are able to use available information to infer a third of the variation in creditworthiness that is captured by a borrower's credit score. This inference is economically significant and allows lenders to lend at a 140-basis-points lower rate for borrowers with (unobserved to lenders) better credit scores within a credit category. While lenders infer the most from standard banking "hard" information, they also use non-standard (subjective) information. Our methodology shows, without needing to code subjective information that lenders learn even from such "softer" information, particularly when it is likely to provide credible signals regarding borrower creditworthiness. Our findings highlight the screening ability of peer-to-peer markets and suggest that these emerging markets may provide a viable complement to traditional lending markets, especially for smaller borrowers.

Encapsulated virgin coconut oil as a nanoscale in vitro solution against multiple drug resistant Staphylococcus aureus

Abstract Niosomes are excellent nanoscale vehicular systems that can carry a variety of drugs and (bioactive) compounds entrapped inside them. Virgin coconut oil (VCO) is the finest grade of coconut oil that is highly enriched with phenolic content, antioxidant activity and also comprises medium chain triglycerides. In this work, niosomes were encapsulated with VCO synthesized by a simple chemical method. The electron microscopy confirmed that spherical nanostructured lipid carrier molecules with a diameter in the range of 180–190 nm were produced. A zeta potential value of −42 mV was a testimony that these nanovehicles were having good stability. The natural oil loaded nanocarrier spheres proved to be potent antibacterial nano‐antibiotics against multiple drug resistant (MDR) bacteria. The antibacterial activity of these magic nano‐spheres was found to be better than ZnO (metallic oxides) nanoparticles. The nano‐antibiotics resulted in 17, 14 and 12 mm zones of inhibition against methicillin‐resistant Staphylococcus aureus (MRSA), vancomycin‐resistant S. aureus (VRSA) and a (general) MDR strain of S. aureus in contrast to nanoparticles that resulted in zones of inhibitions 7, 8 and 6 mm for the same bacterial strains. Niosomes prove to be an excellent nanocarrier system that can encapsulate a number of bio‐active compounds

An environmental equalizer for underwater acoustic communications Tested at Hydralab III

It is known that small changes in source and receiver locations can cause significant changes in underwater acoustic channel impulse responses. At HYDRALAB III an underwater acoustic experiment was conducted to show that a source depth-shift causes a frequency-shift in the channel impulse response and that such behavior can be used to implement an environmental-based equalizer for underwater communications that compensates for the performance loss due to the source depth-shift

A pedestrian path-planning model in accordance with obstacle's danger with reinforcement learning

Most microscopic pedestrian navigation models use the concept of "forces" applied to the pedestrian agents to replicate the navigation environment. While the approach could provide believable results in regular situations, it does not always resemble natural pedestrian navigation behaviour in many typical settings. In our research, we proposed a novel approach using reinforcement learning for simulation of pedestrian agent path planning and collision avoidance problem. The primary focus of this approach is using human perception of the environment and danger awareness of interferences. The implementation of our model has shown that the path planned by the agent shares many similarities with a human pedestrian in several aspects such as following common walking conventions and human behaviours

International Health Regulations—What Gets Measured Gets Done

Focus on goals and metrics for 4 core capacities illustrates 1 approach to implementing IHR

Classification of skin disease using deep learning neural networks with mobilenet V2 and LSTM

Deep learning models are efficient in learning the features that assist in understanding complex patterns precisely. This study proposed a computerized process of classifying skin disease through deep learning-based MobileNet V2 and Long Short Term Memory (LSTM). The MobileNet V2 model proved to be efficient with a better accuracy that can work on lightweight computational devices. The proposed model is efficient in maintaining stateful information for precise predictions. A grey-level co-occurrence matrix is used for assessing the progress of diseased growth. The performance has been compared against other state-of-the-art models such as Fine-Tuned Neural Networks (FTNN), Convolutional Neural Network (CNN), Very Deep Convolutional Networks for Large-Scale Image Recognition developed by Visual Geometry Group (VGG), and convolutional neural network architecture that expanded with few changes. The HAM10000 dataset is used and the proposed method has outperformed other methods with more than 85% accuracy. Its robustness in recognizing the affected region much faster with almost 2x lesser computations than the conven-tional MobileNet model results in minimal computational efforts. Furthermore, a mobile application is designed for instant and proper action. It helps the patient and dermatologists identify the type of disease from the affected region’s image at the initial stage of the skin disease. These findings suggest that the proposed system can help general practitioners efficiently and effectively diagnose skin conditions, thereby reducing further complications and morbidity

Acetone-Gasoline Blend as an Alternative Fuel in SI Engines: A Novel Comparison of Performance, Emission, and Lube Oil Degradation

The disproportionate use of petroleum products and stringent exhaust emissions has emphasized the need for alternative green fuels. Although several studies have been conducted to ascertain the performance of acetone-gasoline blends in spark-ignition (SI) engines, limited work has been done to determine the influence of fuel on lubricant oil deterioration. The current study fills the gap through lubricant oil testing by running the engine for 120 h on pure gasoline (G) and gasoline with 10% by volume acetone (A10). Compared to gasoline, A10 produced better results in 11.74 and 12.05% higher brake power (BP) and brake thermal efficiency (BTE), respectively, at a 6.72% lower brake-specific fuel consumption (BSFC). The blended fuel A10 produced 56.54, 33.67, and 50% lower CO, CO2, and HC emissions. However, gasoline remained competitive due to lower oil deterioration than A10. The flash-point and kinematic viscosity, compared to fresh oil, decreased by 19.63 and 27.43% for G and 15.73 and 20.57% for A10, respectively. Similarly, G and A10 showed a decrease in total base number (TBN) by 17.98 and 31.46%, respectively. However, A10 is more detrimental to lubricating oil due to a 12, 5, 15, and 30% increase in metallic particles like aluminum, chromium, copper, and iron, respectively, compared to fresh oil. Performance additives like calcium and phosphorous in lubricant oil for A10 decreased by 10.04 and 4.04% in comparison to gasoline, respectively. The concentration of zinc was found to be 18.78% higher in A10 when compared with gasoline. A higher proportion of water molecules and metal particles were found in lubricant oil for A10

Intussusception of the appendix secondary to endometriosis: a case report

<p>Abstract</p> <p>Introduction</p> <p>Intussusception of the appendix is an extremely rare condition that ranges from partial invagination of the appendix to involvement of the entire colon. Endometriosis is an exceptionally rare cause of appendiceal intussusception and only very few cases have been reported in the literature to date.</p> <p>Case presentation</p> <p>A 40 year-old woman presented to clinic with a long history of lower abdominal pain, loose motions and painful, heavy periods. Subsequent colonoscopy revealed submucosal endometriotic nodules in the sigmoid as well as a polyp thought to be arising from the appendix, which had inverted itself. She was referred to a colorectal surgeon because the polyp could not be removed endoscopically despite several attempts. At laparotomy, the appendix had intussuscepted but it was possible to reduce it and therefore a simple appendicectomy was carried out. On histology, there were widespread endometrial deposits within the wall of the appendix and this was thought to be the basis for the intussusception.</p> <p>Conclusion</p> <p>Histological evidence of the lead point is of crucial importance in cases of appendiceal intussusception, in order to exclude an underlying neoplastic process. Consequently, surgical resection is necessary either through an open or a laparoscopic approach. Gastrointestinal endometriosis should be considered as a cause of appendiceal intussusception in post-menarchal women with episodic symptoms and proven disease.</p