Critical Analysis of the Evolving Process of Neoliberal Global Capitalism

This chapter aims to make a critical analysis of the evolving process of neoliberal capitalism globalization. It begins with the assumption that the neoliberal capitalism system is undergoing a mutation in the globalization processes as a dynamic element in continuous economic and financial crisis representing the development of the logic of capital based on the neoliberal ideology that promotes the free market. The evolving process of globalization is the history of international free trade framed by the classical liberal and neoliberal economic theory. The discussion focuses on a critical analysis of the paradigm of deglobalization as an alternative to the global capitalist regime that proposes local and regional economic protectionism solutions as an alternative to keep growing the national economies but still neglecting social justice and inequality inclusiveness and socio-ecological development.

The Importance of the Extracellular Matrix in HPV-Associated Diseases

The extracellular matrix (ECM) is the non-cellular component of the tissues of our organism. It is the dynamic element that maintains a biochemical structure capable of supporting the organization and architecture of the tissue constituents. The diversity of ECM’s constituents gives it the biochemical and biophysical properties necessary to regulate its behavior and differentiation. ECM has an important role in the biology of cancer cell development and progression. Human papillomavirus infection (HPV) is the principal etiological agent of the most common sexually transmitted diseases. It is a virus that can cause lesions precursors of epithelial squamous and glandular tumors. Type 16 (HPV16) is the leading cause of pre-malignant lesions and invasive cancers in these tissues. This work will focus on HPV infection to understand the role of ECM in the invasion, spread, and pathogenesis of the lesions caused by this virus. Cancer is no longer considered a pathology explained only by uncontrolled proliferation and apoptosis but also by the deregulation of the microenvironment.

LiDAR-Based SLAM under Semantic Constraints in Dynamic Environments

Facing the realistic demands of the application environment of robots, the application of simultaneous localisation and mapping (SLAM) has gradually moved from static environments to complex dynamic environments, while traditional SLAM methods usually result in pose estimation deviations caused by errors in data association due to the interference of dynamic elements in the environment. This problem is effectively solved in the present study by proposing a SLAM approach based on light detection and ranging (LiDAR) under semantic constraints in dynamic environments. Four main modules are used for the projection of point cloud data, semantic segmentation, dynamic element screening, and semantic map construction. A LiDAR point cloud semantic segmentation network SANet based on a spatial attention mechanism is proposed, which significantly improves the real-time performance and accuracy of point cloud semantic segmentation. A dynamic element selection algorithm is designed and used with prior knowledge to significantly reduce the pose estimation deviations caused by SLAM dynamic elements. The results of experiments conducted on the public datasets SemanticKITTI, KITTI, and SemanticPOSS show that the accuracy and robustness of the proposed approach are significantly improved.

A Potentiostat Readout Circuit with a Low-Noise and Mismatch-Tolerant Current Mirror Using Chopper Stabilization and Dynamic Element Matching for Electrochemical Sensors

This paper presents a potentiostat readout circuit with low-noise and mismatch-tolerant current mirror using chopper stabilization and dynamic element matching (DEM) for electrochemical sensors. Current-mode electrochemical sensors are widely used to detect the blood glucose and viruses in the diagnosis of various diseases such as diabetes, hyperlipidemia, and the H5N1 avian influenza virus (AIV). Low-noise and mismatch-tolerant characteristics are essential for sensing applications that require high reliability and high sensitivity. To achieve these characteristics, a proposed potentiostat readout circuit is implemented using the chopper stabilization scheme and the DEM technique. The proposed potentiostat readout circuit consists of a chopper-stabilized programmable gain transimpedance amplifier (TIA), gain-boosted cascode current mirror, and a control amplifier (CA). The chopper scheme, which is implemented in the TIA and CA, can reduce low frequency noise components, such as 1/f noise, and can obtain low-noise levels. The mismatch offsets of the cascode current mirror can be reduced by the DEM operation. The proposed current-mirror-based potentiostat readout circuit is designed using a standard 0.18 μm CMOS process and can measure the sensor current from 350 nA to 2.8 μA. The input-referred noise integrated from 0.1 Hz to 1 kHz is 21.7 pARMS, and the power consumption was 287.9 μW with a 1.8 V power supply.

An alternative method for windup prevention

Windup effects can be subdivided into controller windup and plant windup. Controller windup can be prevented by stabilizing the compensator during saturation and plant windup by an additional dynamic element. When using a compensating design, i. e., the zeros and poles of the plant are compensated by the poles and zeros of the controller, plant windup does not occur. The compensating control is parametrized by one parameter allowing nearly arbitrary disturbance attenuation. This type of control is restricted to minimum-phase systems. But it has a number of advantages. It simplifies the SISO and especially the MIMO design of compensators with integral action considerably, it has good robustness properties and it allows a diagonal decoupling of the reference behavior for arbitrary MIMO system. Two examples demonstrate the results achievable.