Machine learning techniques for anti-money laundering (AML) solutions in suspicious transaction detection: a review

Money laundering has been affecting the global economy for many years. Large sums of money are laundered every year, posing a threat to the global economy and its security. Money laundering encompasses illegal activities that are used to make illegally acquired funds appear legal and legitimate. This paper aims to provide a comprehensive survey of machine learning algorithms and methods applied to detect suspicious transactions. In particular, solutions of anti-money laundering typologies, link analysis, behavioural modelling, risk scoring, anomaly detection, and geographic capability have been identified and analysed. Key steps of data preparation, data transformation, and data analytics techniques have been discussed; existing machine learning algorithms and methods described in the literature have been categorised, summarised, and compared. Finally, what techniques were lacking or under-addressed in the existing research has been elaborated with the purpose of pinpointing future research directions.     

Synthesis of amino-cosubstituted polyorganophosphazenes and fabrication of their nanoparticles for anticancer drug delivery

The development of safe drug carriers is cardinal in cancer therapy, which can target the cancer cells and release the loaded drug on-demand without damaging the healthy cells of the body. In our work, we synthesized three different biodegradable polymers, poly[(ethyl aminobezoate) (ethyl glycinato) phosphazenes] (PABGPs), in different mole ratio of side groups. The successful synthesis of these PABGPs was confirmed by ¹H NMR, ³¹P NMR, FT-IR, and gel permeation chromatography. These PABGPs were fabricated into drug (camptothecin, CPT, a hydrophobic anticancer drug) loaded nanoparticles. These drug-loaded nanoparticles showed good drug release behaviors under normal physiological conditions (pH 7.4 and temperature 37°C). These PABGPs-based nanoparticles may find their application as effective drug carriers for cancer therapy.     

Improvement of physical and mechanical properties of electrospun poly(lactic acid) nanofibrous structures

Iranian Polymer Journal - The electrospinning of stereocomplexed poly(lactic acid) (Sc-PLA) twisted yarns was our approach to produce PLA-based nanofibrous structures with improved physical and...     

Theoretical and experimental studies of a new aniline derivative corrosion inhibitor for mild steel in acid medium

4-Chloro-N-(pyridin-2-ylmethyl)aniline (CPYA) was synthesized by a simple and inexpensive method and tested as a corrosion inhibitor in acid medium for mild steel by using gravimetric studies and electrochemical measurements. An average maximum efficiency of 96.0% was achieved at 4.59 mmol/L. Corrosion kinetic and thermodynamic parameters were also analyzed. Surface analyses (atomic force microscopy and scanning electron microscopy) show that protection is enabled by adsorption on the metal, forming a film. Quantum chemical calculations were performed to access information regarding the molecular structure in the corrosive medium and to support interpretation of the results obtained by experimental methods.     

Nutritive value of maize silage in relation to dairy cow performance and milk quality

Maize silage has become the major forage component in the ration of dairy cows over the last few decades. This review provides information on the mean content and variability in chemical composition, fatty acid (FA) profile and ensiling quality of maize silages, and discusses the major factors which cause these variations. In addition, the effect of the broad range in chemical composition of maize silages on the total tract digestibility of dietary nutrients, milk production and milk composition of dairy cows is quantified and discussed. Finally, the optimum inclusion level of maize silage in the ration of dairy cows for milk production and composition is reviewed. The data showed that the nutritive value of maize silages is highly variable and that most of this variation is caused by large differences in maturity at harvest. Maize silages ensiled at a very early stage (dry matter (DM) < 250 g kg^?1) were particularly low in starch content and starch/neutral detergent fibre (NDF) ratio, and resulted in a lower DM intake (DMI), milk yield and milk protein content. The DMI, milk yield and milk protein content increased with advancing maturity, reaching an optimum level for maize silages ensiled at DM contents of 300–350 g kg^?1, and then declined slightly at further maturity beyond 350 g kg^?1. The increases in milk (R² = 0.599) and protein (R² = 0.605) yields with maturity of maize silages were positively related to the increase in starch/NDF ratio of the maize silages. On average, the inclusion of maize silage in grass silage‐based diets improved the forage DMI by 2 kg d^?1, milk yield by 1.9 kg d^?1 and milk protein content by 1.2 g kg^?1. Further comparisons showed that, in terms of milk and milk constituent yields, the optimum grass/maize silage ratio depends on the quality of both the grass and maize silages. Replacement of grass silage with maize silage in the ration, as well as an increasing maturity of the maize silages, altered the milk FA profile of the dairy cows, notably, the concentration of the cis‐unsaturated FAs, C18:3n‐3 and n‐3/n‐6 ratio decreased in milk fat. Despite variation in nutritive value, maize silage is rich in metabolizable energy and supports higher DMI and milk yield. Harvesting maize silages at a DM content between 300 and 350 g kg^?1 and feeding in combination with grass silage results in a higher milk yield of dairy cows. © 2014 Society of Chemical Industry