Green credit policy and energy consumption intensity in China: Firm-level evidence and insights.

The transition to sustainable development has become a global priority, with energy transformation serving as a key component. In this context, green financial instruments play a crucial role in shaping corporate energy-saving behaviors and promoting sustainable development. This paper examines the impact and mechanism of China's first green credit policy (GCP) on energy consumption intensity (ECI) of manufacturing firms in China, using a difference-in-difference (DID) approach with micro-level data (2004-2009).

Spatiotemporal distribution characteristics and impact factors of hepatitis C in Chongqing, China, 2014-2020.

Objectives: This study aimed to explore the spatial and temporal distribution of hepatitis C and its influencing factors in Chongqing, providing a scientific basis for the relevant departments to formulate targeted preventive measures for the high prevalence of hepatitis C in the region and population.

Design: We collected data on hepatitis C cases in Chongqing (located in the southwest of China) from 2014 to 2020, and analysed the spatiotemporal heterogeneity of hepatitis C incidence in different populations and identified factors that might influence the incidence of hepatitis C by constructing a Bayesian spatiotemporal model.

Settings: The study subjects included clinically diagnosed cases and confirmed cases of hepatitis C with current address in Chongqing and onset date between 1 January 2014 and 31 December 2020.

Prediction of midpalatal suture maturation stage based on transfer learning and enhanced vision transformer.

Background: Maxillary expansion is an important treatment method for maxillary transverse hypoplasia. Different methods of maxillary expansion should be carried out depending on the midpalatal suture maturation levels, and the diagnosis was validated by palatal plane cone beam computed tomography (CBCT) images by orthodontists, while such a method suffered from low efficiency and strong subjectivity. This study develops and evaluates an enhanced vision transformer (ViT) to automatically classify CBCT images of midpalatal sutures with different maturation stages.

A study of prehospital EMS response time and influencing factors in the main urban area of Chongqing, China.

Shortening the prehospital emergency medical service (EMS) response time is crucial for saving lives and lowering mortality and disability rates in patients with sudden illnesses. Descriptive analyses of prehospital EMS response time and each component were conducted separately using ambulance trip data from the 120 Dispatch Command Centre in the main urban area of Chongqing in 2021, and then, logistic regression analyses were used to explore the influencing factors. The median prehospital EMS response time in the main urban area of Chongqing was 14.

Revolutionizing energy practices: Unleashing the power of artificial intelligence in corporate energy transition.

Corporate energy transition is crucial for long-term sustainable development. The widely discussed Artificial Intelligence (AI), as a disruptive technological innovation, is highly potential for enhancing environment performance. However, the specific impact of AI on the process of corporate energy transition and its underlying mechanisms have not been fully explored.

Federated Learning Backdoor Attack Based on Frequency Domain Injection.

Federated learning (FL) is a distributed machine learning framework that enables scattered participants to collaboratively train machine learning models without revealing information to other participants. Due to its distributed nature, FL is susceptible to being manipulated by malicious clients. These malicious clients can launch backdoor attacks by contaminating local data or tampering with local model gradients, thereby damaging the global model.

Stable and Fast Deep Mutual Information Maximization Based on Wasserstein Distance.

Deep learning is one of the most exciting and promising techniques in the field of artificial intelligence (AI), which drives AI applications to be more intelligent and comprehensive. However, existing deep learning techniques usually require a large amount of expensive labeled data, which limit the application and development of deep learning techniques, and thus it is imperative to study unsupervised machine learning. The learning of deep representations by mutual information estimation and maximization (Deep InfoMax or DIM) method has achieved unprecedented results in the field of unsupervised learning.

Low distortion reversible database watermarking based on hybrid intelligent algorithm.

In many fields, such as medicine and the computer industry, databases are vital in the process of information sharing. However, databases face the risk of being stolen or misused, leading to security threats such as copyright disputes and privacy breaches. Reversible watermarking techniques ensure the ownership of shared relational databases, protect the rights of data owners and enable the recovery of original data.

Secure Ring Signature Scheme for Privacy-Preserving Blockchain.

Blockchain integrates peer-to-peer networks, distributed consensus, smart contracts, cryptography, etc. It has the unique advantages of weak centralization, anti-tampering, traceability, openness, transparency, etc., and is widely used in various fields, e.

Wasserstein Distance-Based Deep Leakage from Gradients.

Federated learning protects the privacy information in the data set by sharing the average gradient. However, "Deep Leakage from Gradient" (DLG) algorithm as a gradient-based feature reconstruction attack can recover privacy training data using gradients shared in federated learning, resulting in private information leakage. However, the algorithm has the disadvantages of slow model convergence and poor inverse generated images accuracy.

Image Adversarial Example Generation Method Based on Adaptive Parameter Adjustable Differential Evolution.

Adversarial example generation techniques for neural network models have exploded in recent years. In the adversarial attack scheme for image recognition models, it is challenging to achieve a high attack success rate with very few pixel modifications. To address this issue, this paper proposes an adversarial example generation method based on adaptive parameter adjustable differential evolution.

A Parallel Multi-Modal Factorized Bilinear Pooling Fusion Method Based on the Semi-Tensor Product for Emotion Recognition.

Multi-modal fusion can exploit complementary information from various modalities and improve the accuracy of prediction or classification tasks. In this paper, we propose a parallel, multi-modal, factorized, bilinear pooling method based on a semi-tensor product (STP) for information fusion in emotion recognition. Initially, we apply the STP to factorize a high-dimensional weight matrix into two low-rank factor matrices without dimension matching constraints.

The Impact of Financial Deepening on Carbon Reductions in China: Evidence from City- and Enterprise-Level Data.

This study extends the limited evidence of the China context by establishing a panel fixed-effect model to identify the nexus between financial deepening and carbon emissions. Using newly compiled city-level (287 prefecture-level and above cities) and enterprise-level (resource enterprises listed on the Chinese A-shares) datasets from 2007 to 2019, this study quantitatively evaluated finance deepening and analysed the impact of financial deepening on carbon emissions in China, with a particular consideration of green innovation. Our results document that financial deepening contributes to carbon reductions, as shown by the considerably decreased carbon dioxide (CO) emissions.

Optimal 3D Angle of Arrival Sensor Placement with Gaussian Priors.

Sensor placement is an important factor that may significantly affect the localization performance of a sensor network. This paper investigates the sensor placement optimization problem in three-dimensional (3D) space for angle of arrival (AOA) target localization with Gaussian priors. We first show that under the A-optimality criterion, the optimization problem can be transferred to be a diagonalizing process on the AOA-based Fisher information matrix (FIM).

A Multi-Modal Fusion Method Based on Higher-Order Orthogonal Iteration Decomposition.

Multi-modal fusion can achieve better predictions through the amalgamation of information from different modalities. To improve the performance of accuracy, a method based on Higher-order Orthogonal Iteration Decomposition and Projection (HOIDP) is proposed, in the fusion process, higher-order orthogonal iteration decomposition algorithm and factor matrix projection are used to remove redundant information duplicated inter-modal and produce fewer parameters with minimal information loss. The performance of the proposed method is verified by three different multi-modal datasets.

QuantifyPolarity, a new tool-kit for measuring planar polarized protein distributions and cell properties in developing tissues.

The coordination of cells or structures within the plane of a tissue is known as planar polarization. It is often governed by the asymmetric distribution of planar polarity proteins within cells. A number of quantitative methods have been developed to provide a readout of planar polarized protein distributions.

An Efficient Plaintext-Related Chaotic Image Encryption Scheme Based on Compressive Sensing.

With the development of mobile communication network, especially 5G today and 6G in the future, the security and privacy of digital images are important in network applications. Meanwhile, high resolution images will take up a lot of bandwidth and storage space in the cloud applications. Facing the demands, an efficient and secure plaintext-related chaotic image encryption scheme is proposed based on compressive sensing for achieving the compression and encryption simultaneously.

Underdetermined DOA Estimation for Wideband Signals via Focused Atomic Norm Minimization.

In underwater acoustic signal processing, direction of arrival (DOA) estimation can provide important information for target tracking and localization. To address underdetermined wideband signal processing in underwater passive detection system, this paper proposes a novel underdetermined wideband DOA estimation method equipped with the nested array (NA) using focused atomic norm minimization (ANM), where the signal source number detection is accomplished by information theory criteria. In the proposed DOA estimation method, especially, after vectoring the covariance matrix of each frequency bin, each corresponding obtained vector is focused into the predefined frequency bin by focused matrix.

Miniaturized all fiber probe for optical coherence tomography and pH detection of biological tissue.

We present a novel all-fiber probe with 710-μm outside diameter for combined optical coherence tomography and pH detection. In cancer surgery, a significant challenge is how to completely remove the malignant tumor without cutting too much normal tissue. The difference between cancer tissue and normal tissue not only lies in morphology and structure but also in tissue pH, where malignant tissue has a lower pH.

Assembly pattern of multicomponent supramolecular oleogel composed of ceramide and lecithin in sunflower oil: self-assembly or self-sorting?

Ceramide (CER) is a novel food-grade organogelator with beneficial health effects. Lecithin (LEC) is not an effective gelator; however, it may alter the crystal morphology of the host gelator in a multicomponent system. In this paper, LEC and CER were mixed at various molar ratios in sunflower oil leading to different gelation behaviors.

Modification of atrioventricular node in a special condition treating paroxysmal supraventricular tachycardia.

Modification of atrioventricular node is a usual and necessary operation to cure atrioventricular nodal reentrant tachycardia (AVNRT). In this operation, atrioventricular block is the most severe complication and its prevention is of our great concern. This complication always occurs under some special circumstances with potential risk.

Successfully ablated atrioventricular nodal reentrant tachycardia in unconventional presentation.

Background: #ENTITYSTARTX02014; Sometime, it's difficult to distinguish the electrophysiological mechanism of some tachycardia, and so, influencing the efficacy and safety of ablation operation. Therefore, it's helpful to analysis some tachycardia in particular mechanism, as in this case.

Methods And Results: #ENTITYSTARTX02014; A 49 years old Chinese male patient had a history of paroxysmal palpitation for 25 years, and recurred more frequently in the month before admission.