Governing autonomous vehicles: emerging responses for safety, liability, privacy, cybersecurity, and industry risks

The benefits of autonomous vehicles (AVs) are widely acknowledged, but there are concerns about the extent of these benefits and AV risks and unintended consequences. In this article, we first examine AVs and different categories of the technological risks associated with them. We then explore strategies that can be adopted to address these risks, and explore emerging responses by governments for addressing AV risks. Our analyses reveal that, thus far, governments have in most instances avoided stringent measures in order to promote AV developments and the majority of responses are non-binding and focus on creating councils or working groups to better explore AV implications. The US has been active in introducing legislations to address issues related to privacy and cybersecurity. The UK and Germany, in particular, have enacted laws to address liability issues, other countries mostly acknowledge these issues, but have yet to implement specific strategies. To address privacy and cybersecurity risks strategies ranging from introduction or amendment of non-AV specific legislation to creating working groups have been adopted. Much less attention has been paid to issues such as environmental and employment risks, although a few governments have begun programmes to retrain workers who might be negatively affected.Comment: Transport Reviews, 201

Design And Analysis Of Auto Security Door Locking System

Mortise locks are generally used for exterior doors due to its high durability in sustaining the security level of house access systems. This type of door lock systems have been implemented on all kinds of houses for more than 70 years. However, the mechanical principle of present mortise locks have remained the same, even though they differ slightly in terms of their exterior that caters to the design of security doors. The mortise principle of this type of lock requires a definite key to lock and unlock the security door. One main drawback of the existing security door lock is that, it is almost impossible to instantly lock the door by inserting the key exactly into the hole of the lock especially during times of emergency. This is the reason why recent burglary reports claim that there is no evidence of breaking-in but the house owner is robbed. Burglary is a crime where unlawful enter a resistanceless house or building through several entrances such as door or window. Burglary may not always happened through the door, yet the percentage of forced entry through housing doors is very high. In addition, this will not only lead to the threat for valuable items, but also to human life. The weak security protection of conventional mortise locks literally renders the premise defenceless against burglaries. The call to enhance functionality of security door locks is imminent. Thus, this present study is undertaken to overcome the drawback stated above by devising and developing an innovative idea of security door locking system. The features of security door locking system included does not require a key or electricity to lock the door, cannot unlock the door without the key and can lock the door instantly. Analytic Hierarchy Process (AHP) decision making tool as well as multi-aspect Quality Function Development (QFD) method are utilised during the stages of design and operational screening. Moreover, sensitivity analysis also had implemented in this study and justified that Concept 1 is the most appropriate design concept of security door locking system compared with another two concepts. The fabricated prototype had go through the simulation and analysis process for performance evaluation and validation. Consequently, the Auto Security Door Locking Syatem (ASD-Lock) will be proposed to attract manufacturers as this solution has high potentials in overcoming the drawbacks of the current mortise locks

Differential Expression of Program Death Ligand 1 in Proliferative Verrucous Leukoplakia

The objective of the study was to evaluate the expression of program death ligand 1 (PD-L1) in lesions of proliferative verrucous leukoplakia (PVL). Eight PVL patients with both low- and high-risk lesions were selected. Their archived biopsy specimens were retrieved from the UNC School of Dentistry Oral Pathology Laboratory. Amalgam tattoo biopsy specimens were selected as control. Immunohistochemistry for PD-L1 was performed on tissue sections. The proportion of epithelial cells expressing PD-L1 was scored. The interobserver agreement for PD-L1 scoring was very good (ICC=0.94). All sixteen controls showed no PD-L1 expression. One of 12 low-risk lesions and 15 of 18 high-risk lesions showed ≥1% PD-L1 expression. There was an association between the risk groups and PD-L1 expression (p=0.004), and the odds ratio of high-risk lesions having ≥1% PD-L1 expression was 54. Our results suggest that anti-PD-1/PD-L1 therapy may be beneficial for patients with PVL who develop high-risk lesions

Penentu Dan Penggunaannya

Objektif projek ini ialah untuk memberi kefahaman yang lebih menyeluruh tentang penentu, projek ini dimulakan dengan sejarah penentu serta takrifannya yang dikaitkan dengan konsep pilihatur. Selain itu, teorem-teorem berkaitan dengannya turut dibincangkan. Kaedah-kaedah yang boleh digunakan untuk mengira penentu termasuklah Petua Sarrus, Kaedah Kofaktor dan Kaedah Penurunan Baris. The objective of this project is to give understanding that is holistic concernmg determinant. This project will introduce the history of determinant as well as its definition with reference to permutations concept. Besides this, related theorems will also be discussed. The approaches used to calculate determinants are Sarrus' Rule, Cofactor Expansion and Row Reduction

Developing A Discrete-Event Simulation Model For Semiconductor Supply Chain

Due to the volatility of demand of integrated circuits (ICs), it is vital to have master planning activity for the manufacturing supply chain to forecast the demand. Production decisions and production planning are based on the demand forecast. With accurate forecasting result, the benefits could be found in the reduction of inventory cost, improvement of order fulfilment, high level of customer satisfaction and many more. In contrast, the most significant impact causes by bad demand forecast are waste of money and time. Specifically for fabless semiconductor company, the shorter duration between placing of sales order by customer and the order requested date compared to the manufacturing cycle time needed for the processes are the most significant challenge faced by the industry. The typical sales order is booked at eight to twelve weeks ahead of the order requested date. Whereas manufacturing cycle time for an end-to-end semiconductor process takes anywhere from 20 to 30 week. Therefore, by developing a discrete-event simulation model, some of the crucial decision variables such as the production quantities of products at different stages, the release quantity of bare wafer to the wafer fab, the amount of inventory of product and bare wafer at the end of a period could be examined in term of planning and control. The simulation model that is constructed in Python will have input parameters such as customers’ demand for product and GDPW (good die per wafer). The model is programmed with stock alarm to alert the user when the quantity of products reaches certain critical level, thus this model could help the company to control the process. On the other hand, the company could utilise the model to simulate the manufacturing activities when comes to planning. Through running the simulation, the company could get to know the duration needed to fulfil the customer’s demand and the level of inventory at each step to avoid high inventory holding costs due to overstocking

Relevance of the Regulatory State in North/South Intersections

Purpose– What seems like a new social anthropology of global regulation is an endeavour much too grand for this paper, even though it has much merit. To contain the analysis which follows, the discussion of social embeddedness will be restricted to a comparison of markets which retain some local or regional integrity from those which have become largely removed from cultural or communal social bonds. An example is between markets trading in goods and services with a consumer base which is local and subsistence, and markets in derivative products that are inextricably dependent on supranational location. The paper aims to discuss these issues.Design/methodology/approach– North World regulatory principle operates within consolidated state frameworks, dislocated market societies and reflects socially disembedded productivity relationships. The same could be said for dominant economic regulatory scholarship. More recent efforts to develop critical analysis of South World regulatory problems and answers have consistently remained connected to the referent of the regulatory state. This paper questions the utility of such a comparative conviction in a global governance reality wherein South World regulatory environments are largely subject to North World state interests and multi-national opportunism fostered by disaggregated, often dysfunctional, domestic states.Findings– If, as in many South World contexts, the state is dysfunctional or destructive in translating regulatory principle, then what are the social bonds which advance the integrity of regulatory principle, and what of externalities which work to draw culturally located principle towards a more hegemonic regulatory project? Could appreciating the relationship between regulatory principle and social bonding be exhibited in degrees of market embeddedness? Might the reimagining of regulatory principle be possible by reflecting on motives and outcomes for regulation that have other than wealth maximization as core value? The paper answers these conjectures as a basis for empirical research.Research limitations/implications– In the spirit of regulatory anthropology it is not helpful to remain immersed in some strained geographic regulatory dichotomy, employing some good state/bad state polarity. Neither World exists in regulatory isolation. International regulatory organizations ensure this through their Western/Northern development models, and perpetuate post-colonial influences over South World development agendas. That said, there are two regulatory worlds, and hybrids between. Despite this, regulatory principle is not immune from cultural forces and social bonding. The paper addresses various dualities in order to propose a new way of viewing South World regulatory paradigms.Practical implications– The framework for analysis will enable a repositioning of critical scholarship and regulatory policy away from the model frameworks of consolidated states and towards the real regulatory needs and potentials of the South World.Social implications– Through applying the analytical technique of social embeddedness above market community paradigms this analysis offers a novel approach to exploring economy in contexts where markets are not dislocated and products are not fictitious. In this way the contemporary materialist economic crisis can be viewed against principles of sustainability rather than growth, productivity and exchange.Originality/value– The paper draws upon established scholarship regarding market embeddedness and social bonding but unique in applying this to a South World void of regulatory discourse set free of comparison with inappropriate regulatory state referents.</jats:sec

Dietary UKMR-1 Roselle supplementation prevents nicotine-induced cardiac injury by inhibiting myocardial oxidative stress

UKMR-1, a local variant of mutant Roselle strain (Hibiscus sabdariffa) is enriched with free radical scavenging polyphenols such as anthocyanin, vitamin C and hydroxycitric acid. However, pharmacological actions of UKMR-1 are not fully known. This study was conducted to determine whether supplementation of aqueous UKMR-1 calyx extract was able to protect against nicotine-induced cardiac injury in rats. In this experimental study, healthy male albino rats were randomly allotted into three groups (n=7 per group): control, nicotine and UKMR-1+Nicotine groups. Nicotine (0.6 mg/kg, i.p.) was administered to both nicotine and UKMR-1+Nicotine groups for 28 consecutive days. UKMR-1+Nicotine group also received 100 mg/kg UKMR-1 extract orally via gavage 30 min prior to nicotine injection, daily. UKMR-1+Nicotine group had significantly (p<0.05) higher lactate dehydrogenase (LDH) activity, as well as lower malondialdehyde content in heart tissue homogenate than nicotine group, suggesting its cardio protective activity by inhibition of lipid peroxidation. UKMR-1 also lowered (p<0.05) the blood pressure in nicotine-administered rats. In addition, UKMR-1 significantly (p<0.05) restored activities of cytosolic superoxide dismutase, glutathione peroxidase and glutathione-S-transferase as well as redox balance ratio (GSH:GSSG). In conclusion, UKMR-1 was able to protect against myocardial injury in rat model of nicotine administration possibly by inhibiting oxidative stress

A Raspberry Pi-based Traumatic Brain Injury Detection System for Single-Channel Electroencephalogram

Traumatic Brain Injury (TBI) is a common cause of death and disability. However, existing tools for TBI diagnosis are either subjective or require extensive clinical setup and expertise. The increasing affordability and reduction in size of relatively high-performance computing systems combined with promising results from TBI related machine learning research make it possible to create compact and portable systems for early detection of TBI. This work describes a Raspberry Pi based portable, real-time data acquisition, and automated processing system that uses machine learning to efficiently identify TBI and automatically score sleep stages from a single-channel Electroen-cephalogram (EEG) signal. We discuss the design, implementation, and verification of the system that can digitize EEG signal using an Analog to Digital Converter (ADC) and perform real-time signal classification to detect the presence of mild TBI (mTBI). We utilize Convolutional Neural Networks (CNN) and XGBoost based predictive models to evaluate the performance and demonstrate the versatility of the system to operate with multiple types of predictive models. We achieve a peak classification accuracy of more than 90% with a classification time of less than 1 s across 16 s - 64 s epochs for TBI vs control conditions. This work can enable development of systems suitable for field use without requiring specialized medical equipment for early TBI detection applications and TBI research. Further, this work opens avenues to implement connected, real-time TBI related health and wellness monitoring systems.Comment: 12 pages, 6 figure