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Drawing on insights from sociology and new institutional economics, Extralegal Governance provides the first comprehensive account of China's illegal markets by applying a socio-economic approach. It considers social legitimacy and state repression in examining the nature of illegal markets. It examines how power dynamics and varying levels of punishment shape exchange relationships between buyers and sellers. It identifies context-specific risks and explains how private individuals and organizations address these risks by developing extralegal governance institutions to facilitate social cooperation across various illegal markets. Adopting a multiple-case study design to sample China's illegal markets, this book utilizes four cases - street vending, small-property-rights housing, corrupt exchanges, and online loan sharks - to examine how market participants foster cooperation and social order in illegal markets.
Channel coding lies at the heart of digital communication and data storage. Fully updated, including a new chapter on polar codes, this detailed introduction describes the core theory of channel coding, decoding algorithms, implementation details, and performance analyses. This new edition includes over 50 new end-of-chapter problems and new figures and worked examples throughout. The authors emphasize the practical approach and present clear information on modern channel codes, including turbo and low-density parity-check (LDPC) codes, detailed coverage of BCH codes, Reed-Solomon codes, convolutional codes, finite geometry codes, product codes as well as polar codes for error correction and detection, providing a one-stop resource for classical and modern coding techniques. Assuming no prior knowledge in the field of channel coding, the opening chapters begin with basic theory to introduce newcomers to the subject. Later chapters then extend to advanced topics such as code ensemble performance analyses and algebraic code design.
Energy inefficiency and environmental damages caused by this inefficiency are increasingly common in developing countries. As the largest developing country, China is experiencing a rapid growth in outward foreign direct investment (OFDI). Do OFDI firms have higher energy efficiency in the same sector? After OFDI, how does the energy efficiency of the firms change? In this study, we employ the data from Chinese industrial firms to empirically investigate these questions. Our results show that OFDI firms have higher energy efficiency and total factor energy efficiency (TFEE) relative to non-OFDI firms in the same sector. After OFDI, firms improve energy efficiency and TFEE through expanding output scale. In addition, these effects are found to be heterogeneous in terms of energy types as well as OFDI motivations and destinations. In general, this study provides some initial evidence for the relationship between OFDI and energy performance at the firm level.
Confinement quality in fusion plasma is influenced significantly by the presence of heavy impurities, which can lead to radiative heat loss and reduced confinement. This study explores the clustering of heavy impurity, i.e. tungsten in edge plasma, using high-resolution direct numerical simulations of the Hasegawa–Wakatani equations. We use the Stokes number to quantify the inertia of impurity particles. It is found that particle inertia will cause spatial intermittency in particle distribution and the formation of large-scale structures, i.e. the clustering of particles. The degrees of clustering are influenced by the Stokes number. To quantify these observations, we apply a modified Voronoi tessellation, which assigns specific volumes to impurity particles. By determining time changes of these volumes, we can calculate the impurity velocity divergence, which allows the clustering dynamics to be assessed. To quantify the clustering statistically, several approaches are applied, such as probability density function (PDF) of impurity velocity divergence and joint PDF of volume and divergence.
Dissecting the exposome linked to mental health outcomes can help identify potentially modifiable targets to improve mental well-being. However, the multiplicity of exposures and the complexity of mental health phenotypes pose a challenge that requires data-driven approaches.
Methods
Guided by our previous systematic approach, we conducted hypothesis-free exposome-wide analyses to identify factors associated with 7 psychiatric diagnostic domains and 19 symptom dimensions in 157,298 participants from the UK Biobank Mental Health Survey. After quality control, 294 environmental, lifestyle, behavioral, and economic variables were included. An Exposome-Wide Association Study was conducted per outcome in two equally split datasets. Variables associated with each outcome were then tested in a multivariable model.
Results
Across all diagnostic domains and symptom dimensions, the top three exposures were childhood adversities and traumatic events. Cannabis use was associated with common psychiatric disorders (depressive, anxiety, psychotic, and bipolar manic disorders), with ORs ranging from 1.10 to 1.79 in the multivariable models. Additionally, differential associations were identified between specific outcomes—such as neurodevelopmental disorders, eating disorders, and self-harm behaviors—and exposures, including early life experiences (being adopted), lifestyle (time spent using computers), and dietary habits (vegetarian diet).
Conclusions
This comprehensive mapping of the exposome revealed that several factors, particularly in the domains of those previously well-studied were shared across mental health phenotypes, providing further support for transdiagnostic pathoetiology. Our findings also showed that distinct relations might exist. Continued exposome research through multimodal mechanistic studies guided by the transdiagnostic mental health framework is required to better inform public health policies.
The emotion regulation network (ERN) in the brain provides a framework for understanding the neuropathology of affective disorders. Although previous neuroimaging studies have investigated the neurobiological correlates of the ERN in major depressive disorder (MDD), whether patients with MDD exhibit abnormal functional connectivity (FC) patterns in the ERN and whether the abnormal FC in the ERN can serve as a therapeutic response signature remain unclear.
Methods
A large functional magnetic resonance imaging dataset comprising 709 patients with MDD and 725 healthy controls (HCs) recruited across five sites was analyzed. Using a seed-based FC approach, we first investigated the group differences in whole-brain resting-state FC of the 14 ERN seeds between participants with and without MDD. Furthermore, an independent sample (45 MDD patients) was used to evaluate the relationship between the aforementioned abnormal FC in the ERN and symptom improvement after 8 weeks of antidepressant monotherapy.
Results
Compared to the HCs, patients with MDD exhibited aberrant FC between 7 ERN seeds and several cortical and subcortical areas, including the bilateral middle temporal gyrus, bilateral occipital gyrus, right thalamus, calcarine cortex, middle frontal gyrus, and the bilateral superior temporal gyrus. In an independent sample, these aberrant FCs in the ERN were negatively correlated with the reduction rate of the HAMD17 score among MDD patients.
Conclusions
These results might extend our understanding of the neurobiological underpinnings underlying unadaptable or inflexible emotional processing in MDD patients and help to elucidate the mechanisms of therapeutic response.
The vitamin K (VK) levels vary greatly among different populations and in different regions. Currently, there is a lack of reference intervals for VK levels in healthy individuals, The aim of this study is to establish and validate the reference intervals of serum vitamin K1 (VK1) and vitamin K2 (VK2, specifically including menaquinone-4 (MK4) and menaquinone-7 (MK7)) levels in some healthy populations in Beijing. Serum VK1, MK4, and MK7 were firstly measured by high-performance liquid chromatography and mass spectrometry in 434 subjects. The reference intervals for three indicators were established by calculating the data of 2.5 and 97.5 percentiles. Finally, preliminary clinical validation was conducted on 60 apparent healthy individuals undergoing physical examination. In the young, middle-aged, and elderly groups, the reference intervals of VK1 were 0.180 ng/mL ∼ 1.494 ng/mL, 0.247 ng/mL ∼ 1.446 ng/mL, and 0.167 ng/mL ∼ 1.445 ng/mL, respectively. The reference intervals of MK4 were 0.009 ng/mL ∼ 0.115 ng/mL, 0.002 ng/mL ∼ 0.103 ng/mL, and 0.003 ng/mL ∼ 0.106 ng/mL, respectively. The reference intervals of MK7 were 0.169 ng/mL ∼ 0.881 ng/mL, 0.238 ng/mL ∼ 0.936 ng/mL, and 0.213 ng/mL ∼ 1.012 ng/mL, respectively. The reference intervals had been validated by the samples of healthy individuals for physical examination. In conclusion, the reference intervals of VK established in this study with different age groups have certain clinical applicability, providing data support for further multicentre studies.
A transverse ledge climbing robot inspired by athletic locomotion is a customized robot aiming to travel through horizontal ledges in vertical walls. Due to the safety issue and complex configurations in graspable ledges such as horizontal, inclined ledges, and gaps between ledges, existing well-known vision-based navigation methods suffering from occlusion problems may not be applicable to this special kind of application. This study develops a force feedback-based motion planning strategy for the robot to explore and make feasible grasping actions as it continuously travels through reachable ledges. A contact force detection algorithm developed using a momentum observer approach is implemented to estimate the contact force between the robot’s exploring hand and the ledge. Then, to minimize the detection errors due to dynamic model uncertainties and noises, a time-varying threshold is integrated. When the estimated contact force exceeds the threshold value, the robot control system feeds the estimated force into the admittance controller to revise the joint motion trajectories for a smooth transition. To handle the scenario of gaps between ledges, several ledge-searching algorithms are developed to allow the robot to grasp the next target ledge and safely overcome the gap transition. The effectiveness of the proposed motion planning and searching strategy has been justified by simulation, where the four-link transverse climbing robot successfully navigates through a set of obstacle scenarios modeled to approximate the actual environment. The performance of the developed grasping ledge searching methods for various obstacle characteristics has been evaluated.
An increasing number of observational studies have reported associations between frailty and mental disorders, but the causality remains ambiguous.
Aims
To assess the bidirectional causal relationship between frailty and nine mental disorders.
Method
We conducted a bidirectional two-sample Mendelian randomisation on genome-wide association study summary data, to investigate causality between frailty and nine mental disorders. Causal effects were primarily estimated using inverse variance weighted method. Several secondary analyses were applied to verify the results. Cochran's Q-test and Mendelian randomisation Egger intercept were applied to evaluate heterogeneity and pleiotropy.
Results
Genetically determined frailty was significantly associated with increased risk of major depressive disorder (MDD) (odds ratio 1.86, 95% CI 1.36–2.53, P = 8.1 × 10−5), anxiety (odds ratio 2.76, 95% CI 1.56–4.90, P = 5.0 × 10−4), post-traumatic stress disorder (PTSD) (odds ratio 2.56, 95% CI 1.69–3.87, P = 9.9 × 10−6), neuroticism (β = 0.25, 95% CI 0.11–0.38, P = 3.3 × 10−4) and insomnia (β = 0.50, 95% CI 0.25–0.75, P = 1.1 × 10−4). Conversely, genetic liability to MDD, neuroticism, insomnia and suicide attempt significantly increased risk of frailty (MDD: β = 0.071, 95% CI 0.033–0.110, P = 2.8 × 10−4; neuroticism: β = 0.269, 95% CI 0.173–0.365, P = 3.4 × 10−8; insomnia: β = 0.160, 95% CI 0.141–0.179, P = 3.2 × 10−61; suicide attempt: β = 0.056, 95% CI 0.029–0.084, P = 3.4 × 10−5). There was a suggestive detrimental association of frailty on suicide attempt and an inverse relationship of subjective well-being on frailty.
Conclusions
Our findings show bidirectional causal associations between frailty and MDD, insomnia and neuroticism. Additionally, higher frailty levels are associated with anxiety and PTSD, and suicide attempts are correlated with increased frailty. Understanding these associations is crucial for the effective management of frailty and improvement of mental disorders.
Real-time systems need to be built out of tasks for which the worst-case execution time is known. To enable accurate estimates of worst-case execution time, some researchers propose to build processors that simplify that analysis. These architectures are called precision-timed machines or time-predictable architectures. However, what does this term mean? This paper explores the meaning of time predictability and how it can be quantified. We show that time predictability is hard to quantify. Rather, the worst-case performance as the combination of a processor, a compiler, and a worst-case execution time analysis tool is an important property in the context of real-time systems. Note that the actual software has implications as well on the worst-case performance. We propose to define a standard set of benchmark programs that can be used to evaluate a time-predictable processor, a compiler, and a worst-case execution time analysis tool. We define worst-case performance as the geometric mean of worst-case execution time bounds on a standard set of benchmark programs.
We identify a new mechanism of opportunistic insider trading linked to attention-driven mispricing. Insiders are more likely to sell their company’s stock during periods of heightened retail attention and more inclined to buy when attention diminishes. The results are particularly pronounced for lottery-type stocks and firms with substantial retail ownership. We demonstrate that our findings—which relate to indicators of mispricing, retail order imbalances, and Robinhood herding episodes—extend to seasoned equity issuances and cannot be solely explained by firm fundamentals. Attention-based insider trading is less likely to result in SEC enforcement actions and persists across different regulatory regimes.
Scabies is a neglected tropical disease caused by the ectoparasitic mite, Sarcoptes scabiei var. hominis (S. scabiei). Common scabies, the most prevalent clinical subtype of scabies, is characterized by pruritus, multiple skin lesions and low mite burden. In contrast, crusted scabies, an extremely contagious variant, is characterized by hyperkeratosis and high mite burden, with or without pruritus. Scabies can be diagnosed based on clinical manifestations, with confirmation obtained through microscopic identification of diagnostic features of S. scabiei. However, owing to the diversity and non-specific nature of its clinical manifestations and insufficient knowledge regarding early-stage clinical manifestations, the diagnosis of crusted scabies continues to be delayed. Herein, we present three cases of scabies with varying degrees of crusting and mite burden. Three patients with physical and microscopic results suggesting scabies were selected for this study. Case 1 had mild crusting and low mite burden, case 2 had severe crusting and high mite burden and case 3 had mild crusting and high mite burden. In this case report, ‘the initial stage of crusted scabies’ refers to the progression from common to crusted scabies. The discussion regarding the diagnostic characteristics of the initial stage of crusted scabies is expected to aid the early diagnosis of crusted scabies.
In this paper, on–off switching digitization of a W-band variable gain power amplifier (VGPA) with above 60 dB dynamic range is introduced for large-scale phased array. Digitization techniques of on–off switching modified stacking transistors with partition are proposed to optimize configuration of control sub-cells. By the proposed techniques, gain control of a radio frequency variable gain amplifier (VGA) could be highly customized for both coarse and fine switching requirements instead of using additional digital-to-analog converters to tune the overall amplifier bias. The designed VGA in 130 nm SiGe has achieved switchable gain range from −46.4 to 20.6 dB and power range from −25.0 to 15.7 dBm at W band. The chip size of the fabricated VGPA is about 0.31 mm × 0.1 mm.
Human activity recognition (HAR) is a vital component of human–robot collaboration. Recognizing the operational elements involved in an operator’s task is essential for realizing this vision, and HAR plays a key role in achieving this. However, recognizing human activity in an industrial setting differs from recognizing daily living activities. An operator’s activity must be divided into fine elements to ensure efficient task completion. Despite this, there is relatively little related research in the literature. This study aims to develop machine learning models to classify the sequential movement elements of a task. To illustrate this, three logistic operations in an integrated circuit (IC) design house were studied, with participants wearing 13 inertial measurement units manufactured by XSENS to mimic the tasks. The kinematics data were collected to develop the machine learning models. The time series data preprocessing involved applying two normalization methods and three different window lengths. Eleven features were extracted from the processed data to train the classification models. Model validation was carried out using the subject-independent method, with data from three participants excluded from the training dataset. The results indicate that the developed model can efficiently classify operational elements when the operator performs the activity accurately. However, incorrect classifications occurred when the operator missed an operation or awkwardly performed the task. RGB video clips helped identify these misclassifications, which can be used by supervisors for training purposes or by industrial engineers for work improvement.
The linear collisionless plasma response to a zonal-density perturbation in quasisymmetric stellarators is studied, including the geodesic-acoustic-mode oscillations and the Rosenbluth–Hinton residual flow. While the geodesic-acoustic-mode oscillations in quasiaxisymmetric configurations are similar to tokamaks, they become non-existent in quasi-helically symmetric configurations when the effective safety factor in helical-angle coordinates is small. Compared with concentric-circular tokamaks, the Rosenbluth–Hinton residual is also found to be multiplied by a geometric factor $\mathcal {C}$ that arises from the flux-surface-averaged classical polarization. Using the near-axis-expansion framework, we derive an analytic expression for $\mathcal {C}$, which varies significantly among different configurations. These analytic results are compared with numerical simulation results from the global gyrokinetic particle-in-cell code GTC, and good agreement with the theoretical Rosenbluth–Hinton residual level is achieved when the quasisymmetry error is small enough.