Reassessing Military Assistance to the Civil Powers: Are Traditional British Anti-Terrorist Responses Still Effective?

The provision of Military Assistance to the Civil Powers (MACP) encapsulates the traditional approach towards countering terrorism on the British mainland, which emphasises minimum force, proportionality, police primacy and the rule of law, with the military retained as a supporting instrument, being employed only as a measure of last resort. Recent terrorist incidents in major urban centres do, however, question the effectiveness of these established methods. This analysis initially codifies the conceptual issues that underscore the tensions between civil policing and military anti-terrorist approaches in the UK, and proceeds to evaluate and compare a number of operations that indicate the nature of the challenges facing the MACP apparatus. In particular, potential shortcomings in the MACP provisions are identified in the form of threat perception and deployment and enforcement gaps. The assessment finds that there are facets of MACP that are of enduring relevance in the current era, yet a continuing need persists to reconcile police and military imperatives toward serious civil disorder contingencies and conditions of emergency.     

Equity in genetic newborn screening

State‐level newborn screening allows for early treatment of genetic disorders, which can substantially improve health outcomes for newborns. As the cost of genetic testing decreases, it is becoming an essential part of newborn screening. A genetic disorder can be caused by many mutation variants; therefore, an important decision is to determine which variants to search for (ie, the panel design), under a testing budget. The frequency of variants that cause a disorder and the incidence of the disorder vary by racial/ethnic group. Consequently, it is important to consider equity issues in panel design, so as to reduce disparities among different groups. We study the panel design problem using cystic fibrosis (CF) as a model disorder, considering the trade‐offs between equity and accuracy, under a limited budget. Most states use a genetic test in their CF screening protocol, but panel designs vary, and, due to cost, no state's panel includes all CF‐causing variants. We develop models that design equitable genetic testing panels, and compare them with panels that maximize sensitivity in the general population. Our case study, based on realistic CF data, highlights the value of equitable panels and provides important insight for newborn screening practices.     

Real-time prediction of projectile penetration to laminates by training machine learning models withfinite element solver as the trainer

Studies on ballistic penetration to laminates is complicated, but important for design effective protection of structures. Experimental means of study is expensive and can often be dangerous. Numerical simu-lation has been an excellent supplement, but the computation is time-consuming. Main aim of this thesis was to develop and test an effective tool for real-time prediction of projectile penetrations to laminates by training a neural network and a decision tree regression model. A large number of finite element models were developed;the residual velocities of projectiles fromfinite element simulations were used as the target data and processed to produce sufficient number of training samples. Study focused on steel 4340tpolyurea laminates with various configurations. Four different 3D shapes of the projectiles were modeled and used in the training. The trained neural network and decision tree model was tested using independently generated test samples using finite element models. The predicted projectile velocity values using the trained machine learning models are then compared with thefinite element simulation to verify the effectiveness of the models. Additionally, both models were trained using a published experimental data of projectile impacts to predict residual velocity of projectiles for the unseen samples. Performance of both the models was evaluated and compared. Models trained with Finite element simulation data samples were found capable to give more accurate predication, compared to the models trained with experimental data, becausefinite element modeling can generate much larger training set, and thus finite element solvers can serve as an excellent teacher. This study also showed that neural network model performs better with small experimental dataset compared to decision tree regression model.     

A platform for initial testing of multiple camouflage patterns

The human visual system is still an important factor in military warfare; military personnel receive training on effective search strategies, and camouflage that can effectively conceal objects and personnel is a key component of a successful integrated survivability strategy. Previous methods of camouflage assessment have, amongst others, used psychophysics to generate distinctiveness metrics. However, the population from which the human observers are drawn is often not well defined, or necessarily appropriate. In this experiment we designed a new platform for testing multiple patterns based on a camouflaged object detection task, and investigate whether trained military observers perform better than civilians. We use a two-alternative forced choice paradigm, with participants searching images of woodland for a replica military helmet displaying Olive Green, Multi Terrain Pattern, US Marine Pattern or, as a conspicuous control, UN Peacekeeper Blue. Our data show that there is no difference in detection performance between the two observer groups but that there are clear differences in the effectiveness of the different helmet colour patterns in a temperate woodland environment. We conclude that when tasks involve very short stimulus presentation times, task-specific training has little effect on the success of target detection and thus this paradigm is particularly suitable for robust estimates of camouflage efficacy.     

Experimental investigation for machinability aspects of graphene oxide/carbon fiber reinforced polymer nanocomposites and predictive modeling using hybrid approach

This article explores the drilling behavior of polymer nanocomposites reinforced by Graphene oxide/Carbon fiber using a hybrid method of Grey theory and Principal component analysis (GR-PCA). An online digital dynamometer was employed for the evaluation of Thrust Force and Torque. The image processing technique computes the delamination. Response surface methodology (RSM) considers the parameters, namely, drilling speed (S), feed rate (F), Graphene Oxide wt.% (G) in designing the experimentation array. Principal component analysis (PCA) was used to tackle the response priority weight during the combination of multiple functions. Analysis of variance (ANOVA) scrutinized the influence of parameters and intended the regression models to predict the response. GR-PCA evaluated the optimal parametric setting and remarked that feed rate acts as the most predominant factor. The higher feed rate and wt.% of G is responsible for surface damages like fiber pull-out, fiber fracture and cracks. A significant improvement in drilling responses has been obtained and also validates through confirmatory test and microstructure investigations.     

ECONOMIC GROWTH AND VIOLENT INTERNATIONAL CONFLICT: 1875–1999

This paper extends the joint product model of military alliances to apply to the new strategic doctrine adopted by NATO in the 1990s. In particular, a choice must be made between protecting one's own territory and pooling forces for an alliancewide rapid reaction force. This new model accounts for a host of externalities and their implications for burden sharing, full financing, and allocative efficiency. The Pigouvian taxes that adjust for force thinning and attack deflection are shown to finance optimal border‐protecting forces under a variety of circumstances. Second‐best considerations arise owing to the pure publicness of rapid reaction forces. The ideal toll arrangement does not currently characterize NATO financing, nor is it likely to do so.     

ACQUIRING FOREIGN NUCLEAR ASSISTANCE IN THE MIDDLE EAST

The United Arab Emirates (UAE) has laid out an ambitious plan to become the first Arab country to possess a civilian nuclear energy program. Central to that effort has been the Emirati government's ability to obtain foreign nuclear assistance. This article traces the UAE's strategies for overcoming the obstacles that stood in the way of nuclear suppliers providing assistance. It examines the approach taken by the UAE to assuage the safety and security concerns of nuclear suppliers, how the UAE leveraged its alliances with France and the United States to obtain their cooperation, and its strategies for engaging domestic interest groups in supplier states. The generalizable elements of the UAE's strategies are discussed and used to provide insight into the prospects for other Middle Eastern states' bids to obtain similar assistance. The article concludes with a discussion of the potentially transformative aspects of the strategies employed by the UAE in shaping other countries' pursuit of nuclear energy in the region.     

Nuclear weapons,existential threats,and the stability–instability paradox

Recent scholarship has largely ignored systematic differences in the existential threats that nuclear-weapon possessors pose to other states. This study theorizes that the capacity to pose existential threats shapes nuclear-armed states’ willingness to use military force against one another. We explore three hypotheses regarding how nuclear-based existential threats can deter conflict or encourage it, including under the conditions proposed by the stability–instability paradox. We rely on a statistical analysis of nuclear-armed dyads from 1950 to 2001 and employ the Nuclear Annihilation Threat (NAT) Index to capture variation in the existential threats nuclear-armed states pose to one another. We find that being able to pose an existential threat to another state emboldens potential initiators to use military force but does not deter attacks. The emboldening effects are particularly strong under the hypothesized conditions of the stability–instability paradox. Our study provides unique contributions to ongoing debates over the political effects of nuclear weapons.