Machine learning-driven credit risk: a systemic review

Credit risk assessment is at the core of modern economies. Traditionally, it is measured by statistical methods and manual auditing. Recent advances in financial artificial intelligence stemmed from a new wave of machine learning (ML)-driven credit risk models that gained tremendous attention from both industry and academia. In this paper, we systematically review a series of major research contributions (76 papers) over the past eight years using statistical, machine learning and deep learning techniques to address the problems of credit risk. Specifically, we propose a novel classification methodology for ML-driven credit risk algorithms and their performance ranking using public datasets. We further discuss the challenges including data imbalance, dataset inconsistency, model transparency, and inadequate utilization of deep learning models. The results of our review show that: 1) most deep learning models outperform classic machine learning and statistical algorithms in credit risk estimation, and 2) ensemble methods provide higher accuracy compared with single models. Finally, we present summary tables in terms of datasets and proposed models

Reasons for tooth extractions and related risk factors in adult patients: a cohort study

Background: The aimof this studywas to evaluate oral status, the reasons for tooth extractions and related risk factors in adult patients attending a hospital dental practice. Methods: 120 consecutive patients ranging from23 to 91 years in age (mean age of 63.3 - 15.8) having a total of 554 teeth extracted were included. Surveys about general health status were conducted and potential risk factors such as smoking, diabetes and age were investigated. Results: a total of 1795 teeth weremissing after extraction procedures and the mean number of remaining teeth after the extraction process was 16.8 ± 9.1 per patient. Caries (52.2%) was the most common reason for extraction along with periodontal disease (35.7%). Males were more prone to extractions, with 394 of the teeth extracted out of the total of 554 (71.1%). Male sex (β = 2.89; 95% CI 1.26, 4.53; p = 0.001) and smoking habit (β = 2.95; 95% CI 1.12, 4.79; p = 0.002) were related to a higher number of teeth extracted. Age (β = -0.24; 95% CI -0.31, -0.16; p < 0.001) and diabetes (β = -4.47; 95% CI -7.61, -1.33; p = 0.006) were related to a higher number of missing teeth at evaluation time. Moreover, periodontal disease was more common as a reason of extraction among diabetic patients than among non-diabetic ones (p = 0.04). Conclusions: caries and periodontal disease were the most common causes of extraction in a relatively old study population: further screening strategies might be required for the early interception of caries and periodontal disease

NEGATIVE SYNERGISM BETWENN THE COMBINATION OF STEROID AND LOW MOLECULAR WEIGHT HEPARIN (LMWH) ON BONE METABOLISM, IN PATIENTS TREATED FOR LYMPHOMA

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The effect of an optimized diet as an adjunct to non-surgical periodontal therapy in subjects with periodontitis: a prospective study

Diet and nutrition are generally categorized as modifiable lifestyle risk factors for the development of periodontal disease because diet may influence a person’s inflammatory status. This study aimed to evaluate the efficacy of the application of a diet plan focused on reducing inflammation and oxidative stress in treating periodontitis. Subjects suffering from periodontitis were divided into two groups. Both groups underwent non-surgical periodontal therapy, and in the optimized diet (OD) group, this treatment was associated with a diet plan. The sample consisted of 60 subjects; 32 (53%) were treated in the non-optimized diet group (ND group) and 28 (47%) in the OD group. In both groups, the periodontal treatment significantly improved the recorded periodontal outcomes between T0 and T1 (FMPS, FMBS, CAL, PPD). Inter-group differences were not statistically significant (p < 0.05). The linear regression models showed that the optimized diet was associated with a higher reduction in PPD and FMBS after the treatment, while patients who had higher LDL levels (over 100 mg/mL) had a less favorable improvement of PPD. The application of an improved diet plan can increase the reduction in PPD and FMBS after non-surgical periodontal therapy when compared with periodontal treatment alone

Catalysis over zinc-incorporated berlinite (ZnAlPO4) of the methoxycarbonylation of 1,6-hexanediamine with dimethyl carbonate to form dimethylhexane-1,6-dicarbamate

<p>Abstract</p> <p>Background</p> <p>The alkoxycarbonylation of diamines with dialkyl carbonates presents promising route for the synthesis of dicarbamates, one that is potentially 'greener' owing to the lack of a reliance on phosgene. While a few homogeneous catalysts have been reported, no heterogeneous catalyst could be found in the literature for use in the synthesis of dicarbamates from diamines and dialkyl carbonates. Because heterogeneous catalysts are more manageable than homogeneous catalysts as regards separation and recycling, in our study, we hydrothermally synthesized and used pure berlinite (AlPO₄) and zinc-incorporated berlinite (ZnAlPO₄) as heterogeneous catalysts in the production of dimethylhexane-1,6-dicarbamate from 1,6-hexanediamine (HDA) and dimethyl carbonate (DMC). The catalysts were characterized by means of XRD, FT-IR and XPS. Various influencing factors, such as the HDA/DMC molar ratio, reaction temperature, reaction time, and ZnAlPO₄/HDA ratio, were investigated systematically.</p> <p>Results</p> <p>The XRD characterization identified a berlinite structure associated with both the AlPO₄and ZnAlPO₄catalysts. The FT-IR result confirmed the incorporation of zinc into the berlinite framework for ZnAlPO₄. The XPS measurement revealed that the zinc ions in the ZnAlPO₄structure possessed a higher binding energy than those in ZnO, and as a result, a greater electron-attracting ability. It was found that ZnAlPO₄catalyzed the formation of dimethylhexane-1,6-dicarbamate from the methoxycarbonylation of HDA with DMC, while no activity was detected on using AlPO₄. Under optimum reaction conditions (i.e. a DMC/HDA molar ratio of 8:1, reaction temperature of 349 K, reaction time of 8 h, and ZnAlPO₄/HDA ratio of 5 (mg/mmol)), a yield of up to 92.5% of dimethylhexane-1,6-dicarbamate (with almost 100% conversion of HDA) was obtained. Based on these results, a possible mechanism for the methoxycarbonylation over ZnAlPO₄was also proposed.</p> <p>Conclusion</p> <p>As a heterogeneous catalyst ZnAlPO₄berlinite is highly active and selective for the methoxycarbonylation of HDA with DMC. We propose that dimethylhexane-1,6-dicarbamate is formed <it>via </it>a catalytic cycle, which involves activation of the DMC by a key active intermediate species, formed from the coordination of the carbonyl oxygen with Zn(II), as well as a reaction intermediate formed from the nucleophilic attack of the amino group on the carbonyl carbon.</p

External shocks, trade margins, and macroeconomic dynamics

This paper studies the role of the exchange rate regime for trade of new products. It first provides VAR evidence that a rise in external productivity shifts trade away from new products and more so in fixed regimes. Then, it presents a model with firm dynamics in line with this evidence. We argue that exchange rate policy can affect firms' entry decisions with consequences for the competitiveness of a country's exports well beyond the short run. In our setup, fixed exchange rates can foster the competitiveness of firms that trade new products, while flexible rates favor firms that produce mature products