Sexual homicide offenders as repeat and nonrepeat offenders:An empirical study of sexual homicide cases in Mainland China

The comparative examination of different groups of sexual homicide offenders (SHOs) is currently limited. To expand our understanding of Chinese sexual homicides, this study aimed to distinguish between the modus operandi (MO) characteristics of repeat (i.e., with previous arrest and/or conviction) and nonrepeat (i.e., without previous arrest and/or conviction) offenders. Data were gathered from police arrest records, court documents, and published case reports in mainland China, covering a 31‐year period (1988–2018). A sample of 86 male SHOs (31 repeat and 55 nonrepeat offenders) was identified and the offenders' MO characteristics were examined. Compared with nonrepeat offenders, repeat offenders were significantly more likely to commit sexual murder in outdoor locations, approach their victims initially using a non‐surprise approach, engage in nonvaginal penetration of their victims, use a personal weapon to kill their victims, and move their victims' bodies away from the crime scene. However, repeat offenders were less likely to be arrested immediately after committing the murder. The findings have practical implications for police investigative strategies, such as suspect prioritization

Applications of physical methods in high-frequency futures markets

In the present work we demonstrate the application of different physical methods to high-frequency or tick-by-tick financial time series data. In particular, we calculate the Hurst exponent and inverse statistics for the price time series taken from a range of futures indices. Additionally, we show that in a limit order book the relaxation times of an imbalanced book state with more demand or supply can be described by stretched exponential laws analogous to those seen in many physical systems.Comment: 14 Pages and 10 figures. Proceeding to the SPIE conference, 4 - 7 December 2007 Australian National Univ. Canberra, ACT, Australi

Risky Sexual Behavior and Psychopathy:Testing the Relationship in a Non-Clinical Sample of Young Adults in Hong Kong

This study aims to investigate the relationship between risky sexual behavior (RSB) and psychopathy in a non-clinical sample of 714 Hong Kong adults, shedding light on sex differences. Our findings reveal that males exhibit significantly higher mean levels of RSB (general, penetrative, and nonpenetrative), as well as egocentric (Factor 1) and callous (Factor 3) traits of psychopathy, along with increased sexual desire compared to females. Regression analyses indicate that elevated levels of antisociality (Factor 2) and callousness (Factor 3) traits of psychopathy, along with sexual desire, emerge as significant risk factors for engaging in general, penetrative, and nonpenetrative RSB. Intriguingly, higher age and being in a long-term relationship are associated with RSB. The implications of this study suggest potential avenues for reducing, if not entirely preventing, the inclination to engage in RSB in the presence of psychopathic traits

Distinct neural networks underlie encoding of categorical versus coordinate spatial relations during active navigation

It has been proposed that spatial relations are encoded either categorically, such that the relative positions of objects are defined in prepositional terms; or in terms of visual coordinates, such that the precise distances between objects are represented. In humans, it has been assumed that a left hemisphere neural network sub-serves categorical representations, and that coordinate representations are right lateralised. However, evidence in support of this distinction has been garnered exclusively from tasks that involved static, two-dimensional (2D) arrays. We used functional magnetic resonance imaging (fMRI) to identify neural circuits underlying categorical and coordinate representations during active spatial navigation. Activity in the categorical condition was significantly greater in the parietal cortex, whereas the coordinate condition revealed greater activity in medial temporal cortex and dorsal striatum. In addition, activity in the categorical condition was greater in parietal cortex within the left hemisphere than within the right Our findings are consistent with analogous studies in rodents, and support the suggestion of distinct neural circuits underlying categorical and coordinate representations during active spatial navigation. The findings also support the claim of a left hemispheric preponderance for the processing of categorical spatial relations. (C) 2012 Elsevier Inc. All rights reserved

Classification of Protein-Binding Sites Using a Spherical Convolutional Neural Network

The analysis and comparison of protein-binding sites aid various applications in the drug discovery process, e.g., hit finding, drug repurposing, and polypharmacology. Classification of binding sites has been a hot topic for the past 30 years, and many different methods have been published. The rapid development of machine learning computational algorithms, coupled with the large volume of publicly available protein–ligand 3D structures, makes it possible to apply deep learning techniques in binding site comparison. Our method uses a cutting-edge spherical convolutional neural network based on the DeepSphere architecture to learn global representations of protein-binding sites. The model was trained on TOUGH-C1 and TOUGH-M1 data and validated with the ProSPECCTs datasets. Our results show that our model can (1) perform well in protein-binding site similarity and classification tasks and (2) learn and separate the physicochemical properties of binding sites. Lastly, we tested the model on a set of kinases, where the results show that it is able to cluster the different kinase subfamilies effectively. This example demonstrates the method’s promise for lead hopping within or outside a protein target, directly based on binding site information