An open-data, agent-based model of alcohol related crime

The allocation of resources to challenge city centre violent crime traditionally relies on historical data to identify hot-spots. The usefulness of such data-driven approaches is limited when historical data is scarce or unavailable (e.g. planning of a new city) or insufficiently representative (e.g. does not account for novel events, such as Olympic Games). In some cities, crime data is not systematically accumulated at all. We present a graph-constrained agent based simulation model of alcohol-related violent crime that is capable of predicting areas of likely violent crime without requiring any historical data. The only inputs to our simulation are publicly available geographical data, which makes our method immediately applicable to a wide range of tasks, such as optimal city planning, police patrol optimisation, devising alcohol licensing policies. In experiments, we evaluate our model and demonstrate agreement of our model's predictions on where and when violence will occur with real-world violent crime data. Analyses indicate that our agent based model may be able to make a significant contribution to attempts to prevent violence through deterrence or by design

Association of violence with urban points of interest

The association between alcohol outlets and violence has long been recognised, and is commonly used to inform policing and licensing policies (such as staggered closing times and zoning). Less investigated, however, is the association between violent crime and other urban points of interest, which while associated with the city centre alcohol consumption economy, are not explicitly alcohol outlets. Here, machine learning (specifically, LASSO regression) is used to model the distribution of violent crime for the central 9 km2 of ten large UK cities. Densities of 620 different Point of Interest types (sourced from Ordnance Survey) are used as predictors, with the 10 most explanatory variables being automatically selected for each city. Cross validation is used to test generalisability of each model. Results show that the inclusion of additional point of interest types produces a more accurate model, with significant increases in performance over a baseline univariate alcohol-outlet only model. Analysis of chosen variables for city-specific models shows potential candidates for new strategies on a per-city basis, with combined-model variables showing the general trend in POI/violence association across the UK. Although alcohol outlets remain the best individual predictor of violence, other points of interest should also be considered when modelling the distribution of violence in city centres. The presented method could be used to develop targeted, city-specific initiatives that go beyond alcohol outlets and also consider other locations

Outlier detection of vital sign trajectories from COVID-19 patients

There is growing interest in continuous wearable vital sign sensors for monitoring patients remotely at home. These monitors are usually coupled to an alerting system, which is triggered when vital sign measurements fall outside a predefined normal range. Trends in vital signs, such as an increasing heart rate, are often indicative of deteriorating health, but are rarely incorporated into alerting systems. In this work, we present a novel outlier detection algorithm to identify such abnormal vital sign trends. We introduce a distance-based measure to compare vital sign trajectories. For each patient in our dataset, we split vital sign time series into 180 minute, non-overlapping epochs. We then calculated a distance between all pairs of epochs using the dynamic time warp distance. Each epoch was characterized by its mean pairwise distance (average link distance) to all other epochs, with large distances considered as outliers. We applied this method to a pilot dataset collected over 1561 patient-hours from 8 patients who had recently been discharged from hospital after contracting COVID-19. We show that outlier epochs correspond well with patients who were subsequently readmitted to hospital. We also show, descriptively, how epochs transition from normal to abnormal for one such patient.Comment: 4 pages, 4 figures, 1 table. Submitted to IEEE BHI 2022, decision pendin

Structural dynamics of a metal-organic framework induced by CO2 migration in its non-uniform porous structure

Stimuli-responsive behaviors of flexible metal-organic frameworks (MOFs) make these materials promising in a wide variety of applications such as gas separation, drug delivery, and molecular sensing. Considerable efforts have been made over the last decade to understand the structural changes of flexible MOFs in response to external stimuli. Uniform pore deformation has been used as the general description. However, recent advances in synthesizing MOFs with non-uniform porous structures, i.e. with multiple types of pores which vary in size, shape, and environment, challenge the adequacy of this description. Here, we demonstrate that the CO -adsorption-stimulated structural change of a flexible MOF, ZIF-7, is induced by CO migration in its non-uniform porous structure rather than by the proactive opening of one type of its guest-hosting pores. Structural dynamics induced by guest migration in non-uniform porous structures is rare among the enormous number of MOFs discovered and detailed characterization is very limited in the literature. The concept presented in this work provides new insights into MOF flexibility

Structural dynamics of a metal-organic framework induced by CO2 migration in its non-uniform porous structure.

Stimuli-responsive behaviors of flexible metal-organic frameworks (MOFs) make these materials promising in a wide variety of applications such as gas separation, drug delivery, and molecular sensing. Considerable efforts have been made over the last decade to understand the structural changes of flexible MOFs in response to external stimuli. Uniform pore deformation has been used as the general description. However, recent advances in synthesizing MOFs with non-uniform porous structures, i.e. with multiple types of pores which vary in size, shape, and environment, challenge the adequacy of this description. Here, we demonstrate that the CO2-adsorption-stimulated structural change of a flexible MOF, ZIF-7, is induced by CO2 migration in its non-uniform porous structure rather than by the proactive opening of one type of its guest-hosting pores. Structural dynamics induced by guest migration in non-uniform porous structures is rare among the enormous number of MOFs discovered and detailed characterization is very limited in the literature. The concept presented in this work provides new insights into MOF flexibility

The interaction between a sexually transferred steroid hormone and a female protein regulates oogenesis in the malaria mosquito anopheles gambiae

Molecular interactions between male and female factors during mating profoundly affect the reproductive behavior and physiology of female insects. In natural populations of the malaria mosquito Anopheles gambiae, blood-fed females direct nutritional resources towards oogenesis only when inseminated. Here we show that the mating-dependent pathway of egg development in these mosquitoes is regulated by the interaction between the steroid hormone 20-hydroxy-ecdysone (20E) transferred by males during copulation and a female Mating-Induced Stimulator of Oogenesis (MISO) protein. RNAi silencing of MISO abolishes the increase in oogenesis caused by mating in blood-fed females, causes a delay in oocyte development, and impairs the function of male-transferred 20E. Co-immunoprecipitation experiments show that MISO and 20E interact in the female reproductive tract. Moreover MISO expression after mating is induced by 20E via the Ecdysone Receptor, demonstrating a close cooperation between the two factors. Male-transferred 20E therefore acts as a mating signal that females translate into an increased investment in egg development via a MISO-dependent pathway. The identification of this male–female reproductive interaction offers novel opportunities for the control of mosquito populations that transmit malaria

What a girl’s gotta do: the labour of the biopolitical celebrity in austerity Britain

This article debunks the wide-spread view that young female celebrities, especially those who rise to fame through reality shows and other forms of media-orchestrated self-exposure, dodge ‘real’ work out of laziness, fatalism and a misguided sense of entitlement. Instead, we argue that becoming a celebrity in a neoliberal economy such as that of the United Kingdom, where austerity measures disproportionately disadvantage the young, women and the poor is not as irregular or exceptional a choice as previously thought, especially since the precariousness of celebrity earning power adheres to the current demands of the neoliberal economy on its workforce. What is more, becoming a celebrity involves different forms of labour that are best described as biopolitical, since such labour fully involves and consumes the human body and its capacities as a living organism. Weight gain and weight loss, pregnancy, physical transformation through plastic surgery, physical symptoms of emotional distress and even illness and death are all photographically documented and supplemented by extended textual commentary, usually with direct input from the celebrity, reinforcing and expanding on the visual content. As well as casting celebrity work as labour, we also maintain that the workings of celebrity should always be examined in the context of wider cultural and real economies

BSSF: a fingerprint based ultrafast binding site similarity search and function analysis server

<p>Abstract</p> <p>Background</p> <p>Genome sequencing and post-genomics projects such as structural genomics are extending the frontier of the study of sequence-structure-function relationship of genes and their products. Although many sequence/structure-based methods have been devised with the aim of deciphering this delicate relationship, there still remain large gaps in this fundamental problem, which continuously drives researchers to develop novel methods to extract relevant information from sequences and structures and to infer the functions of newly identified genes by genomics technology.</p> <p>Results</p> <p>Here we present an ultrafast method, named BSSF(Binding Site Similarity & Function), which enables researchers to conduct similarity searches in a comprehensive three-dimensional binding site database extracted from PDB structures. This method utilizes a fingerprint representation of the binding site and a validated statistical Z-score function scheme to judge the similarity between the query and database items, even if their similarities are only constrained in a sub-pocket. This fingerprint based similarity measurement was also validated on a known binding site dataset by comparing with geometric hashing, which is a standard 3D similarity method. The comparison clearly demonstrated the utility of this ultrafast method. After conducting the database searching, the hit list is further analyzed to provide basic statistical information about the occurrences of Gene Ontology terms and Enzyme Commission numbers, which may benefit researchers by helping them to design further experiments to study the query proteins.</p> <p>Conclusions</p> <p>This ultrafast web-based system will not only help researchers interested in drug design and structural genomics to identify similar binding sites, but also assist them by providing further analysis of hit list from database searching.</p

BSSF: a fingerprint based ultrafast binding site similarity search and function analysis server

<p>Abstract</p> <p>Background</p> <p>Genome sequencing and post-genomics projects such as structural genomics are extending the frontier of the study of sequence-structure-function relationship of genes and their products. Although many sequence/structure-based methods have been devised with the aim of deciphering this delicate relationship, there still remain large gaps in this fundamental problem, which continuously drives researchers to develop novel methods to extract relevant information from sequences and structures and to infer the functions of newly identified genes by genomics technology.</p> <p>Results</p> <p>Here we present an ultrafast method, named BSSF(Binding Site Similarity & Function), which enables researchers to conduct similarity searches in a comprehensive three-dimensional binding site database extracted from PDB structures. This method utilizes a fingerprint representation of the binding site and a validated statistical Z-score function scheme to judge the similarity between the query and database items, even if their similarities are only constrained in a sub-pocket. This fingerprint based similarity measurement was also validated on a known binding site dataset by comparing with geometric hashing, which is a standard 3D similarity method. The comparison clearly demonstrated the utility of this ultrafast method. After conducting the database searching, the hit list is further analyzed to provide basic statistical information about the occurrences of Gene Ontology terms and Enzyme Commission numbers, which may benefit researchers by helping them to design further experiments to study the query proteins.</p> <p>Conclusions</p> <p>This ultrafast web-based system will not only help researchers interested in drug design and structural genomics to identify similar binding sites, but also assist them by providing further analysis of hit list from database searching.</p