How Officers Create Guardianship: An Agent-based Model of Policing

Crime is a complex phenomenon, emerging from the interactions of offenders, victims, and their environment, and in particular from the presence or absence of capable guardians. Researchers have historically struggled to understand how police officers create guardianship. This presents a challenge because, in order to understand how to advise the police, researchers must have an understanding of how the current system works. The work presents an agent-based model that simulates the movement of police vehicles, using a record of real calls for service and real levels of police staffing in spatially explicit environments to emulate the demands on the police force. The GPS traces of the simulated officers are compared with real officer movement GPS data in order to assess the quality of the generated movement patterns. The model represents an improvement on existing standards of police simulation, and points the way toward more nuanced understandings of how police officers influence the criminological environment

A group-blind multiuser receiver for MC-CDMA systems

In this paper, a group-blind multiuser receiver is investigated for multicarrier code division multiple access (MC-CDMA) systems. In uplink transmissions, the receiver has the knowledge of the spreading sequences of the users within the cell, while the spreading sequences of the users from other cells are unknown. By imposing linear vector constraints on the multiuser detector, group-blind detection can efficiently suppress the known interferers, while mitigating the unknown interferers based on the minimum mean square error (MMSE) principle. A subspace-based channel estimation algorithm is proposed to blindly estimate the channel information. An adaptive implementation of the group-blind multiuser detection is also developed by using signal and noise subspace tracking algorithms. Numerical results show that the performance of the group-blind detector is much better than the subspace-based blind linear MMSE detector.published_or_final_versio

THE performance and robust implementation of a blind CMOE receiver for MC-CDMA systems

This paper studies a new robust constrained minimum output energy (CMOE)-based blind detector for multicarrier code division multiple access (MC-CDMA) systems. The proposed receiver intends to minimize the receiver's output energy while preserving the components of the desired user. By imposing quadratic weight constraints, the CMOE detector is made more robust against signal modeling errors, and a better performance over the standard CMOE detector is obtained. Steady-state signal-to-interference-plus-noise ratio (SINR) analysis of the blind CMOE detector and the minimum mean-squared error (MMSE) method with training sequences is presented. Numerical results show that the performance of the new robust detector is comparable to subspace-based method using exact singular value decomposition (SVD).published_or_final_versio

New approximate qr-ls algorithms for minimum output energy (MOE) receivers in ds-cdma communication systems

This paper proposes a new family of approximate QR-based least-squares (LS) adaptive algorithms called p-AQR- LS for blind minimum output energy (MOE) detection in CDMA communications systems. It extends the A-QR-LS algorithm by retaining different numbers of diagonal plus p -1 off-diagonals of the triangular factor of the augmented data matrix. For p =1 and N ( N is the length of the weighting vector), it reduces to the A-QR-LS and the QR-RLS algorithms, respectively. It not only provides a link between the QR-LMS-type and the QR-RLS algorithms through a well-structured family of algorithms, but also offers more freedom in the complexity-performance tradeoffs for practical receiver design in communication systems. The performance of the proposed algorithm is verified by computer simulations. © 2005 IEEE.published_or_final_versio

Characterization of volatile organic compounds at a roadside environment in Hong Kong: An investigation of influences after air pollution control strategies

Vehicular emission is one of the important anthropogenic pollution sources for volatile organic compounds (VOCs). Four characterization campaigns were conducted at a representative urban roadside environment in Hong Kong between May 2011 and February 2012. Carbon monoxide (CO) and VOCs including methane (CH4), non-methane hydrocarbons (NMHCs), halocarbons, and alkyl nitrates were quantified. Both mixing ratios and compositions of the target VOCs show ignorable seasonal variations. Except CO, liquefied petroleum gas (LPG) tracers of propane, i-butane and n-butane are the three most abundant VOCs, which increased significantly as compared with the data measured at the same location in 2003. Meanwhile, the mixing ratios of diesel- and gasoline tracers such as ethyne, alkenes, aromatics, halogenated, and nitrated hydrocarbons decreased by at least of 37%. The application of advanced multivariate receptor modeling technique of positive matrix factorization (PMF) evidenced that the LPG fuel consumption is the largest pollution source, accounting for 60 ± 5% of the total quantified VOCs at the roadside location. The sum of ozone formation potential (OFP) for the target VOCs was 300.9 μg-O3 m-3, which was 47% lower than the value of 567.3 μg-O3 m-3 measured in 2003. The utilization of LPG as fuel in public transport (i.e., taxis and mini-buses) contributed 51% of the sum of OFP, significantly higher than the contributions from gasoline- (16%) and diesel-fueled (12%) engine emissions. Our results demonstrated the effectiveness of the switch from diesel to LPG-fueled engine for taxis and mini-buses implemented by the Hong Kong Special Administrative Region (HKSAR) Government between the recent ten years, in additional to the execution of substitution to LPG-fueled engine and restrictions of the vehicular emissions in compliance with the updated European emission standards

Developing an online cooperative police patrol routing strategy

A cooperative routing strategy for daily operations is necessary to maintain the effects of hotspot policing and to reduce crime and disorder. Existing robot patrol routing strategies are not suitable, as they omit the peculiarities and challenges of daily police patrol including minimising the average time lag between two consecutive visits to hotspots, as well as coordinating multiple patrollers and imparting unpredictability to patrol routes. In this research, we propose a set of guidelines for patrol routing strategies to meet the challenges of police patrol. Following these guidelines, we develop an innovative heuristic-based and Bayesian-inspired real-time strategy for cooperative routing police patrols. Using two real-world cases and a benchmark patrol strategy, an online agent-based simulation has been implemented to testify the efficiency, flexibility, scalability, unpredictability, and robustness of the proposed strategy and the usability of the proposed guidelines

Selection bias in build-operate-transfer transportation project appraisals

Recent empirical studies have found widespread inaccuracies in traffic forecasts despite the fact that travel demand forecasting models have been significantly improved over the past few decades. We suspect that an intrinsic selection bias may exist in the competitive project appraisal process, in addition to the many other factors that contribute to inaccurate traffic forecasts. In this paper, we examine the potential for selection bias in the governmental process of Build-Operate-Transfer (BOT) transportation project appraisals. Although the simultaneous consideration of multiple criteria is typically used in practice, traffic flow estimate is usually a key criterion in these appraisals. For the purposes of this paper, we focus on the selection bias associated with the highest flow estimate criterion. We develop two approaches to quantify the level and chance of inaccuracy caused by selection bias: the expected value approach and the probability approach. The expected value approach addresses the question “to what extent is inaccuracy caused by selection bias?”. The probability approach addresses the question “what is the chance of inaccuracy due to selection bias?”. The results of this analysis confirm the existence of selection bias when a government uses the highest traffic forecast estimate as the priority criterion for BOT project selection. In addition, we offer some insights into the relationship between the extent/chance of inaccuracy and other related factors. We do not argue that selection bias is the only reason for inaccurate traffic forecasts in BOT projects; however, it does appear that it could be an intrinsic factor worthy of further attention and investigation.postprin

Herba Epimedii: Anti-oxidative properties and its medical implications

Herba Epimedii is a Chinese herbal medicine with proven efficacy in treating cardiovascular diseases and osteoporosis, and in improving sexual and neurological functions. This efficacy is found to be related to the potent anti-oxidative ability of Herba Epimedii and its flavonoid components, with icarrin as the main effective constituent, along with polysaccharides and vitamin C. These ingredients have been proven to be effective against oxidative-stress related pathologies (cardiovascular diseases, Alzheimer's disease and inflammation) in animal rodent models and in vitro studies. Their antioxidative properties are found to be related to an inductive effect on endogenous freeradical scavenging enzymes such as catalase and glutathione peroxidase and the inherent electron-donating ability of flavonoids. © 2010 licensee MDPI, Basel, Switzerland.published_or_final_versio

Mechanism for controlling the monomer-dimer conversion of SARS coronavirus main protease

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Adiponectin is protective against oxidative stress induced cytotoxicity in amyloid-beta neurotoxicity

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