Project Code Research Articles

A Recursive Construction for Projective Reed-Muller Codes

A Recursive Construction for Projective Reed-Muller Codes

Enforcement of consumer rights protection laws and intention to reuse digital financial services among Generation Z youth: Empirical evidence from Vietnamese commercial banks

Digital financial services are crucial in boosting the competitive edge of businesses and economies in numerous developing nations. This study aims to explore the factors that affect consumers’ perceptions of the implementation of consumer protection laws and their willingness to continue using digital financial services. Data were collected through interviews with 689 Gen Z consumers (born after 1996) who have used digital financial services in Vietnamese commercial banks. The results of the partial least square – structural equation modeling indicate that six factors influence attitudes toward the enforcement of consumer protection laws, in descending order: perceived benefits, understanding of legal regulations, perceived asymmetry, perceived risk, understanding of technology and digital finance, and understanding of dispute resolution. Additionally, attitudes toward law enforcement, as well as understanding of technology and digital finance, positively impact consumers’ intention to reuse digital financial services, while perceived risk has the opposite effect. Furthermore, all six independent factors impact the intention to reuse digital financial services through the mediating role of attitudes toward the enforcement of consumer protection laws. The study’s findings also lay the groundwork for policy recommendations for legislative authorities and strategic guidance for service providers and consumers in emerging markets in the future. AcknowledgmentThis study is the result of collaboration between researchers from the University of Law, Hue University, and School of Business and Economics, Duy Tan University. The authors would like to thank both institutions for their support and facilitation in the publication of this research. This study was conducted under project code DHH2024-12-85, Decision No. 298/QĐ-ĐHH dated March 27, 2024, issued by the Director of Hue University.

Comparison of codes for calculation of projocted radiation-induced cancer risks.

The lifetime attributable risk (LAR) of cancer caused by radiation exposure is crucial when deciding on radiological protection measures or protective actions for nuclear emergency preparedness and response. Although a model for estimating LAR among the Japanese population has been developed based on epidemiological data from A-bomb survivors, a flexible projection code implementing this model must be developed. This study investigated existing codes to contribute to the development of a projection code. Based on these investigations, we compared their LAR calculation results and explored the causes of their differences.

Safety and efficacy of individual target transcranial magnetic stimulation to stimulate the most negative correlate of DLPFC-pgACC in the treatment of major depressive disorder: study protocol of a double-blind, randomised controlled trial

IntroductionMajor depressive disorder (MDD) is a common mental disorder that is characterised by high morbidity, high rates of relapse, high rates of disability and, in severe cases, suicide ideas or...

Debuting an innovative model for integrated child health care in the Southeast region, Bulgaria

Abstract Background Demographic indicators are fundamental drivers for health policy action. The Southeast Region (SER) is the largest statistical region (NUTS 2) in Bulgaria (BG), distinguished by the highest Infant mortality rates (IMR) and teenage crude fertility rates across the European Union (EU). For instance, the 2022 statistics reveal an IMR of 8.2 per 1000 live births in SER, notably higher than Bulgaria’s average of 4.8 and the EU’s average of 3.3. This disparity highlights the critical need for region-specific health initiatives aimed at curtailing IMR and harmonizing health outcomes throughout the EU territories. This report outlines such an initiative under the project code BG16FFPR003-2.001-012, recently funded by the EU. The novel SER initiative: This is the first presentation of the concept of integrated territory investments (CITI) and the innovative model for integrated child health care in SER, BG. The project impacts child health care across the four districts of SER - Burgas, Sliven, Yambol, Stara Zagora. The municipalities have collaboratively submitted 24 project proposals with educational bodies, NGOs, public institutions, and the Ministry of Health. The theoretical frame of the project’s model is underpinned by three foundational pillars: 1) Prevention in primary healthcare; 2) Child health care in hospitals; 3) Development of human resources, providers of health care. The forthcoming infrastructural, organisational, and capacity-building interventions will remain adaptable yet aligned with the overarching CITI framework. Conclusions A current phase of public discourse on the CITI concept and the innovative integrated model in SER is underway. Stakeholders are actively encouraged to provide input either through discussions or by participating in designated online surveys. Community engagement is instrumental in evaluating and prioritizing these initiatives, which aim to fundamentally transform the SER by leveraging its unique territorial potential. Key messages • Demographic indicators drive health policy. Project BG16FFPR003-2.001-012 targets EU disparities, lowering IMR and balancing fertility rates. • This is the first presentation of the “Innovative model for integrated child health care in SER”. The EPH Conference provides an ideal platform for sharing and discussion.

Increasing the speed of digital devices using the ASMD-FSMD method using non-blocking operators

The ASMD-FSMD method for designing digital devices is considered, which consists of constructing a block diagram of an algorithmic state machine with a data path (ASMD), which describes the behavior of the device, and creating project code in Verilog in the form of a finite state machine with a data processing path. (finite state machine with datapath – FSMD). One of the directions for the development of the ASMD-FSMD methodology is the use of features of the hardware description language (HDL). A hypothesis has been put forward: in the ASMD-FSMD technique, it is possible to apply several non-blocking assignment operators to the same variable in one synchronization cycle, which will lead to an increase in device performance. The hypothesis put forward was investigated in the design of synchronous multipliers that implement the classical multiplication algorithms c and d. Experimental studies have confirmed the validity of the put forward hypothesis, while the speed of the multipliers increases two to three times, and the cost of implementation in most cases decreases compared to the traditional approach.

Napoleon's Civil Code in the Political Discourse of the Alexander Era

Napoleon's "Civil Code" is a fundamental work of European legal thought. M.M. Speransky, appointed by Emperor Alexander I to the Commission for Drafting Laws, of course, could not help but refer to this text; moreover, he actively used it when drafting his famous "Draft Civil Code", but revised many of its provisions when adapting it to the class-based Russian society. Nevertheless, the influence of the Code on Speransky's "Draft" was so noticeable that it caused sharp rejection in conservative circles. The main opponents of the Secretary of State were N.M. Karamzin and A.S. Shishkov, who criticized the "Draft". When writing this article, the main method was the method of discourse analysis. This method, the subject of which is traditionally defined as "speech immersed in life", made it possible to study the extralinguistic aspects of the texts of participants in the communicative field in political disputes around the legislative initiatives of M.M. Speransky in terms of their correlation with Napoleon's Civil Code. Also used were such methods as content analysis, biographical method, comparative-historical and contrastive. Despite all the similarities, the positions of Karamzin and Shishkov differed. If Shishkov categorically did not accept any changes to Russian statehood, defending the need to preserve its absolutist inviolability, then Karamzin, who admired Robespierre in his youth, then idolized Napoleon, openly declared his republicanism. The ambiguity of his position, which has been repeatedly noted by researchers, is fully explained by the phenomenon of the development of republican thought of that time, which is shown in the article. Speransky, responding to criticism of the "Project Code", stated that all such projects are similar, since they have Roman law as their source. But this was not important for his opponents, who used all available tools to discredit him.

Identifying nucleotide-binding leucine-rich repeat receptor and pathogen effector pairing using transfer-learning and bilinear attention network.

Nucleotide-binding leucine-rich repeat (NLR) family is a class of immune receptors capable of detecting and defending against pathogen invasion. They have been widely used in crop breeding. Notably, the correspondence between NLRs and effectors (CNE) determines the applicability and effectiveness of NLRs. Unfortunately, CNE data is very scarce. In fact, we've found a substantial 91291 NLRs confirmed via wet experiments and bioinformatics methods but only 387 CNEs are recognized, which greatly restricts the potential application of NLRs. We propose a deep learning algorithm called ProNEP to identify NLR-effector pairs in a high-throughput manner. Specifically, we conceptualized the CNE prediction task as a protein-protein interaction (PPI) prediction task. Then, ProNEP predicts the interaction between NLRs and effectors by combining the transfer learning with a bilinear attention network. ProNEP achieves superior performance against state-of-the-art models designed for PPI predictions. Based on ProNEP, we conduct extensive identification of potential CNEs for 91291 NLRs. With the rapid accumulation of genomic data, we expect that this tool will be widely used to predict CNEs in new species, advancing biology, immunology, and breeding. The ProNEP is available at http://nerrd.cn/#/prediction. The project code is available at https://github.com/QiaoYJYJ/ProNEP.

The role of NMDA receptors in fish stress response: Assessments based on physiology of the caudal neurosecretory system and defensive behavior.

Stress strongly influences the physiology and behavior of animals, and leads into a pathological condition and disease. NMDA receptors (NMDARs) play a crucial role in the modulation of neural activity. To understand the role of NMDARs in fish stress response, we used NMDARs agonist aspartate to test the functional role of its input on the Dahlgren cell population in the caudal neurosecretory system (CNSS) of the olive flounder. In addition, the effect of the NMDARs antagonist D-AP5 on the expression of genes of the main secretory products of the CNSS after stress was investigated by using qPCR technology and the effect of the NMDARs antagonist D-AP5 on post-stress behavior was explored by behavioral methods. Ex vivo electrophysiological experiments showed that the NMDARs agonist aspartate enhanced the firing frequency of Dahlgren cells. Additionally, aspartate treatment increased the incidence of cells exhibiting bursting firing pattern, this result is corroborated by the observed upregulation in the expression of ion channels and major hormone genes in the CNSS. Furthermore, the excitatory influence of aspartate was effectively counteracted by NMDARs antagonist D-AP5. Interestingly, NMDARs antagonist D-AP5 treatment also significantly decreased the plasma cortisol levels and the expression of CRH, UI, and UII in CNSS after acute stress. Treatment with D-AP5 effectively attenuated the stress response, as evidenced by alterations in respiratory metabolism, sand-burying behavior, swimming distance, simulated capture, and escape response. In conclusion, modulation of Dahlgren cell excitability in the CNSS by NMDARs contributes to the regulation of the stress response, NMDARs antagonist D-AP5 can effectively suppress stress response in flounder by regulating the stress hormone expression and secretion. CLINICAL TRIAL REGISTRATION: Project code SHOU-DW-2022-032.

PERF: Panoramic Neural Radiance Field From a Single Panorama.

Neural Radiance Field (NeRF) has achieved substantial progress in novel view synthesis given multi-view images. Recently, some works have attempted to train a NeRF from a single image with 3D priors. They mainly focus on a limited field of view with a few occlusions, which greatly limits their scalability to real-world 360-degree panoramic scenarios with large-size occlusions. In this paper, we present PERF, a 360-degree novel view synthesis framework that trains a panoramic neural radiance field from a single panorama. Notably, PERF allows 3D roaming in a complex scene without expensive and tedious image collection. To achieve this goal, we propose a novel collaborative RGBD inpainting method and a progressive inpainting-and-erasing method to lift up a 360-degree 2D scene to a 3D scene. Specifically, we first predict a panoramic depth map as initialization given a single panorama and reconstruct visible 3D regions with volume rendering. Then we introduce a collaborative RGBD inpainting approach into a NeRF for completing RGB images and depth maps from random views, which is derived from an RGB Stable Diffusion model and a monocular depth estimator. Finally, we introduce an inpainting-and-erasing strategy to avoid inconsistent geometry between a newly-sampled view and reference views. The two components are integrated into the learning of NeRFs in a unified optimization framework and achieve promising results. Extensive experiments on Replica and a new dataset PERF-in-the-wild demonstrate the superiority of our PERF over state-of-the-art methods. Our PERF can be widely used for real-world applications, such as panorama-to-3D, text-to-3D, and 3D scene stylization applications.

Role of law enforcement, governance, and digital transformation in risk control and management at Vietnamese commercial banks

Risk control and management are essential tasks necessary to ensure the safe and sustainable development of commercial banks, especially in today’s digital business environment. This study aims to identify the factors and their impact on risk control and management through intermediary variables, including law enforcement, corporate governance, and digital transformation, using the partial least square – structural equation modeling. Data for the study were collected through interviews assessing the perceptions of 765 managers in 35 Vietnamese commercial banks. The results indicate that factors directly affecting law enforcement include digital transformation, awareness of risks related to new technologies, training in law and technological knowledge, employee capabilities, monitoring and inspection procedures, size and complexity of bank operations, and corporate governance. However, only law enforcement and corporate governance have an indirect intermediary impact on risk control and management (digital transformation did not show a statistically significant impact). These findings highlight that, according to managerial perceptions in commercial banks, current digital transformations have not significantly influenced risk control and management, emphasizing the need for further enhancement in this area moving forward. This study makes a positive contribution to the development of models and measurement systems, laying the foundation for similar experimental research in the field of commercial banking in various countries in the future. AcknowledgmentThis study is the result of collaboration between a group of scientists from the Faculty of Law – Hue University and Duy Tan University. The authors would like to acknowledge the support and facilitation provided by both institutions for the publication of this research. Furthermore, this work is conducted within the framework of project code B2023-ĐHH-03 under decision No. 2036/QĐ-BGDĐT dated July 22, 2022.

Agritourism as a strategy of remote island’s development: the case study of Kasos

In rural, depopulated areas, agritourism, as a development model, could serve the goal of non- exclusively seasonal tourism while creating additional economic opportunities for the locals who are mainly engaged in agriculture. Kasos is an isolated island of the Dodecanese, Greece, preserving interesting elements of the authentic agricultural practices and architecture like terraces serving the island’s agricultural cultivation, mills and mitata, small stone- built creameries. Kasos served as a case study of AEI program (Sustainable Development of Less Developed Regions and Isolated Areas by Creating New Touristic Resources and Products through Analysis, Documentation and Modelling of Cultural Assets using Innovative ICT Applications, project code:T2EDK- 01278). For thιs island that lies within the wider region of Rhodes, it is possible with the appropriate development of new touristic resources and products through the advancement of the unique architectural, cultural and environmental assets to orient towards them special parts of the touristic flow from Rhodes, creating new touristic activity by increasing the residence beyond the daily or short time tourism, as it stands for now. For the analysis of the study area, research in local archives and communication with the municipality and local stakeholders was conducted. Thus, both the special features of the island and the needs of the local community were identified, organized, classified and presented in GIS maps. The implementation of a GIS for Kasos Island aims to provide a comprehensive representation of the different aspects of the island, providing useful information for policy-making and the development of strategic cultural and agrotourism plans to the local authorities and stakeholders. According to the integrated plan for Kasos by AEI program, the island could preserve its special rural identity while revealing its cultural and environmental assets and attracting external economies within an agritourism model. In this work, we present AEI’s integrated plan for Kasos that refers to the island’s agricultural character, to the existing trail network as well as to the restoration and adaptive reuse of important architectural assets that could serve to the overall revealing of Kasos history and cultural reserve.

SSAGCN: Social Soft Attention Graph Convolution Network for Pedestrian Trajectory Prediction.

Pedestrian trajectory prediction is an important technique of autonomous driving. In order to accurately predict the reasonable future trajectory of pedestrians, it is inevitable to consider social interactions among pedestrians and the influence of surrounding scene simultaneously, which can fully represent the complex behavior information and ensure the rationality of predicted trajectories obeyed realistic rules. In this article, we propose one new prediction model named social soft attention graph convolution network (SSAGCN), which aims to simultaneously handle social interactions among pedestrians and scene interactions between pedestrians and environments. In detail, when modeling social interaction, we propose a new social soft attention function, which fully considers various interaction factors among pedestrians. Also, it can distinguish the influence of pedestrians around the agent based on different factors under various situations. For the scene interaction, we propose one new sequential scene sharing mechanism. The influence of the scene on one agent at each moment can be shared with other neighbors through social soft attention; therefore, the influence of the scene is expanded both in spatial and temporal dimensions. With the help of these improvements, we successfully obtain socially and physically acceptable predicted trajectories. The experiments on public available datasets prove the effectiveness of SSAGCN and have achieved state-of-the-art results. The project code is available at https://github.com/WW-Tong/ssagcn_for_path_prediction.

Delving into CLIP latent space for Video Anomaly Recognition

We tackle the complex problem of detecting and recognising anomalies in surveillance videos at the frame level, utilising only video-level supervision. We introduce the novel method AnomalyCLIP, the first to combine Vision and Language Models (VLMs), such as CLIP, with multiple instance learning for joint video anomaly detection and classification. Our approach specifically involves manipulating the latent CLIP feature space to identify the normal event subspace, which in turn allows us to effectively learn text-driven directions for abnormal events. When anomalous frames are projected onto these directions, they exhibit a large feature magnitude if they belong to a particular class. We also leverage a computationally efficient Transformer architecture to model short- and long-term temporal dependencies between frames, ultimately producing the final anomaly score and class prediction probabilities. We compare AnomalyCLIP against state-of-the-art methods considering three major anomaly detection benchmarks, i.e. ShanghaiTech, UCF-Crime, and XD-Violence, and empirically show that it outperforms baselines in recognising video anomalies. Project website and code are available at https://lucazanella.github.io/AnomalyCLIP/.

The Weight Enumerator Polynomials of the Lifted Codes of the Projective Solomon-Stiffler Codes

The Weight Enumerator Polynomials of the Lifted Codes of the Projective Solomon-Stiffler Codes

The Topology of Projective Codes and the Distribution of Zeros of Odd Maps

The Topology of Projective Codes and the Distribution of Zeros of Odd Maps

Gastric neuroendocrine tumors: 20-Year experience in a reference center.

Few studies have been published on the long-term outcomes of patients with gastric neuroendocrine tumors (gNETs). We analyzed their management over a two-decade period, focusing on endoscopic and clinical outcomes. Clinical, laboratory, endoscopic, surgical, and histopathological data from Types 1 and 3 gNETs histologically diagnosed between March 2000 and December 2021 at the European Institute of Oncology (IEO, Milan) were retrospectively collected. Sixty-nine patients were included (60 Type 1, 9 Type 3): 53 (77%) were treated endoscopically, 6 (9%) surgically, and 10 (14%) did not receive any treatment. Overall, 293 lesions were removed endoscopically: 74% by forceps, 20% by endoscopic mucosal resection (EMR), and 5% by endoscopic submucosal dissection (ESD). No differences were observed between EMR and ESD in terms of complete resection rate (p value = .50) and complications rate (p value = .084). The median follow-up period was 5.8 years (range: 0.3-20.5), during which no gNET-related deaths were observed. Metachronous gNETs developed in 60% of patients with Type 1 gNET. Six patients with lymph node metastases (LNM) were younger (p value = .006) and had larger lesions (p value <.001) than patients without LNM. Most Type 1 gNETs were successfully excised using forceps, with EMR and ESD being equally effective. The presence of incomplete resection was not associated with a worse prognosis, which remains excellent in this highly recurrent disease. Younger age and a size ≥10 mm were associated with an increased risk of LNM. CLINICAL TRIAL REGISTRATION: Project code UID 2854.

Complementary branch fusing class and semantic knowledge for robust weakly supervised semantic segmentation

Leveraging semantically precise pseudo masks derived from image-level class knowledge for segmentation, namely image-level Weakly Supervised Semantic Segmentation (WSSS), remains challenging. Class Activation Maps (CAMs) using CNNs enhance WSSS by focusing on specific class parts like only the face of a human, whereas Vision Transformers (ViT) capture broader semantic parts but often miss complete class-specific details, such as human bodies with nearby objects like dogs. In this work, we propose a Complementary Branch (CoBra), a novel dual-branch framework consisting of two distinct architectures that provide valuable complementary knowledge of class (from CNN) and semantics (from ViT). In particular, we learn Class-Aware Projection (CAP) for the CNN branch and Semantic-Aware Projection (SAP) for the ViT branch, combining their insights to facilitate new patch-level supervision and create effective pseudo masks integrating class and semantic information. Extensive experiments qualitatively and quantitatively investigate how each branch complements the other, showing a significant result. Project Page and code are available: https://micv-yonsei.github.io/cobra2024/.

REVIEW – A VALUABLE EDITORIAL APPEARANCE IN THE FIELD OF THE LOCAL LANDSCAPE: LANDSCAPE AESTHETICS IN FINE ARTS IN MOLDOVA

The monograph Landscape Aesthetics in Fine Arts in Moldova, Chișinău: CEP Publishing House, USM, 2024, second edition (first edition, 2021), is a work carried out within the Postdoctoral Program (2021-2022), Strategic Priority – Societal Challenges, with the theme: Morphological stylistics in interior design, architecture, fine arts in Moldova, with the project code 21.00208.0807.00/PD, authored by Angela Munteanu. The paper discusses the issue of the evolution and constitution of the landscape genre in the fine arts in Moldova. The monograph Landscape Aesthetics in Fine Arts in Moldova reflects the periods of evolution and development of the landscape genre through stylistic trends, representatives of different schools of painting, graphics, and decorative arts, and artistic currents, resulting in a truthful panorama of the artistic process in Moldova.

Dynamic ESG Equilibrium

This paper proposes a conditional asset pricing model that integrates environmental, social, and governance (ESG) demand and supply dynamics. Shocks in the demand for sustainable investing represent a novel risk source, characterized by diminishing marginal utility and positive premium. Green assets exhibit positive exposure to ESG demand shocks, hence commanding higher premia. Conversely, time-varying convenience yield leads to lower expected returns for green assets. Moreover, ESG demand shocks have positive contemporaneous effects on unexpected returns, contributing to large positive payoffs in the green-minus-brown portfolio over extended horizons. The model predictions align closely with evidence on return spreads between green and brown assets, further reinforcing the apparent gap between realized and expected spreads. This paper was accepted by Lin William Cong, finance. Funding: Y. Liu acknowledges funding by the Research Grants Council of the Hong Kong Special Administrative Region, China [Grant T35/710/20R]. A. Tarelli acknowledges funding by the European Union - Next Generation EU [Project Code 2022FWZ2CR]. The views and opinions expressed are only those of the authors. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2022.03491 .