Miracle-dz/UniFAR-FTUs huggingface dataset:
Selected Topics of Social Physics: Equilibrium Systems

The paper gives an introduction to the physics approach to social systems providing the main definitions and notions used in the modeling of these systems. The behavior of social systems is illustrated by several quite simple, typical models. The present part considers equilibrium systems. Nonequilibrium systems will be presented in the second part of the review. The style of the paper combines the features of a tutorial and a survey, which, from one side, makes it simpler to read for nonspecialists aiming to grasp the basics of social physics, and from the other side, describes several rather recent original models containing new ideas that could be of interest to experienced researchers in the field. The selection of the material is limited and motivated by the author’s research interests.
Tunable Random Fiber Laser Based on Dual-Grating Structure

In order to reduce the pumping threshold and achieve a short-cavity single-mode transmission with a narrow-linewidth random fiber laser, we propose a tunable random fiber laser based on the combination of random grating and highly reflective fiber Bragg grating (FBG). Theoretical modeling of a random refractive index-modulated fiber grating was carried out. Random grating is regarded as a linear combination of uniform fiber gratings with different periods. Simulation calculations were performed using the transfer matrix method to determine the preparation parameters. Under the premise of satisfying light localization, a point-by-point method was used to write a random grating in a single-mode fiber using a femtosecond laser according to the simulated parameters. We constructed a random fiber laser with a linewidth of 1.68 kHz and a threshold of 29.2 mW using a random grating and a highly reflective FBG combined with an erbium-doped fiber. Due to the broad scattered wavelength range of the random grating, by changing the central wavelength of the high-reflection FBG, the tunable wavelength of the output laser was realized, and the tunable range was 0.847 nm (1549.110–1549.957 nm). Moreover, the laser’s central wavelength and output power are stable for a long time. Compared with other lasers, the proposed laser has the advantages of a lower threshold, shorter cavity length, narrower linewidth, and a relatively simple structure.
A Good Crisis: Emergencies and the Reframing of American Higher Education, 1944–1965

ABSTRACT The purported “Golden Age” of American higher education, typically associated with the two decades following World War II, was marked by increasingly generous federal support of the nation’s postsecondary institutions and their students. Unlike analyses that attribute this largesse to factors like geopolitics (i.e., a response to the Cold War) or demographics (i.e., expansion to accommodate the Baby Boom generation), this article argues that a deliberate strategy rooted in rhetoric enabled “higher education partisans” to successfully push generous higher education policy in Washington, DC. Specifically, the language of crisis and emergency enabled these advocates to frame college-going as a tool that could solve social and economic problems, defend the nation and its values, and chip away at prejudice and inequality. Their success is evident in a “policy cascade” initiated by the 1944 GI Bill and reaching its apex with the 1965 Higher Education Act. This article relies on new archival research and document analysis to examine the trajectories of six key pieces of federal policymaking, which together constituted “a sheep in wolf’s clothing” by couching funding for colleges and universities as a response to urgent, even existential, crises.
Polynomial Based Design of Linear Phase Recursive and Non Recursive Filters

In this dissertation, several algorithms to design linear phase Finite Impulse Response (FIR) and Infinite Impulse Response (IIR) filters have been discussed. Contrary to various already existing standard algorithms,the proposed methods approximate magnitude and phase characteristics simultaneously. The basic mechanism used in this study is polynomial based design of digital filters. We have used several already existing polynomials; e.g., Chebyshev polynomials, Legendre polynomials, to develop linear phase digital filters and developed some two dimensional polynomials following orthogonal properties to design digital filters for image processing, their design methodology have also been discussed. Filters of proposed type can be used for applications where exact linear phase is required. Another application of this type of filters is the design of filters with zero group delay. IIR filters are designed with absolute linear phase and zero group delay. The algorithms proposed in the present thesis allow user to design filters with his set of constraints, which is required in practical filter design problems. Very narrow band 1D and 2D linear phase FIR filters can easily be designed by the proposed methodology. The IIR filters proposed provide the guarantee to result in a stable filter. All the algorithms have been discussed stepwise to make sure that any one with basic programming capability can easily design them. We have not used any standard routine of any particular platform, therefore any freely available programming platform (like C, C++, Scilab, Octave, etc.) can be used to design these filters. te l-0 03 71 38 5, v er si on 1 27 M ar 2 00 9
A Sustainable Development Evaluation Framework for Chinese Electricity Enterprises Based on SDG and ESG Coupling

In 2021, China’s power generation industry took the lead in launching carbon emissions trading, ushering in a major challenge and opportunity for the sustainable development of power enterprises. Assessing the sustainable development performance of power enterprises has become the key to the sustainable financing and development of power enterprises in this new developmental stage. Based on the integration of the long-term UN Sustainable Development Goals (SDGs) and the ESG (Environmental, Social, and Governance) evaluation indicators of listed companies, this paper constructed an index system for the evaluation of the sustainable development of electric power companies consisting of 75 indicators corresponding to four dimensions: economic, social, environmental, and governance. Given the vision for the sustainable development of electric power companies, the assessment thresholds for each indicator were determined by the practical exploration and typical progress assessment of SDGs. Aggregate assessment and dashboard assessment techniques for the sustainable development of electric power companies were established, and we conducted a robustness analysis of the evaluation system. The results revealed the following details: (1) The disclosure of sustainable development indicators of Chinese electricity enterprises was 94.13%, among which the four dimensions of economy, environment, society, and governance were 99.89%, 82.62%, 94.00%, and 97.71%, respectively. (2) The aggregate sustainable development index for Chinese power companies was 59.34, and the environment, society, governance, and economic scores were 62.10, 64.49, 76.79, and 41.37, respectively. (3) Based on the results of the dashboard, investment in innovation, public welfare, emissions of greenhouse gases, and economic sustainability are the key factors limiting the achievement of sustainable development. (4) The framework’s robustness analysis showed that the results of the evaluation of this paper’s indicator framework fell within a reasonable range of variation using different ranking and weighting systems. Chinese electricity companies should comprehensively control costs and expenses, strengthen capital management, expand funding channels, focus on enhancing R&D capabilities, enhance their scientific and technological innovation management systems, and improve their disclosure of information about greenhouse gas emissions, resource consumption and use, and employee issues to improve the overall level of sustainable development. The evaluation system developed in this paper further enriches the evaluation of corporate sustainability performance. This paper explored the application of the SDG index and dashboard construction methods at the national level to the evaluation of sustainability at the corporate level, providing a clear picture of corporate performance with respect to various dimensions, issues, criteria, and indicators.
The Impact of Sustainable Investing: A Multidisciplinary Review

We conduct a multidisciplinary review of how sustainable investing impacts the environment and society. Our review starts from the insight that shareholders can create impact not only through (1) portfolio screening and (2) shareholder engagement (two impact strategies most used by mainstream shareholders) but also through (3) field building (an impact strategy most used by shareholders at the periphery of the financial sector). Based on this framework of three impact strategies, we integrate insights from four disciplines (management, finance, sociology, and ethics/sustainability) to reconstruct how each impact strategy influences corporate sustainability. We identify 15 impact mechanisms through which the impact strategies produce three types of impact: portfolio screening and shareholder engagement mostly create direct impact on companies, while field building creates indirect impact via other shareholders and indirect impact via the institutional context. Our review suggests that shareholder impact emerges gradually as different types of shareholders build on each other’s efforts, which we use to outline a research agenda on shareholder impact as a distributed process.
Enhanced Information Graph Recursive Network for Traffic Forecasting

Accurate traffic forecasting is crucial for the advancement of smart cities. Although there have been many studies on traffic forecasting, the accurate forecasting of traffic volume is still a challenge. To effectively capture the spatio-temporal correlations of traffic data, a deep learning-based traffic volume forecasting model called the Enhanced Information Graph Recursive Network (EIGRN) is presented in this paper. The model consists of three main parts: a Graph Embedding Adaptive Graph Convolution Network (GE-AGCN), a Modified Gated Recursive Unit (MGRU), and a local information enhancement module. The local information enhancement module is composed of a convolutional neural network (CNN), a transposed convolutional neural network, and an attention mechanism. In the EIGRN, the GE-AGCN is used to capture the spatial correlation of the traffic network by adaptively learning the hidden information of the complex topology, the MGRU is employed to capture the temporal correlation by learning the time change of the traffic volume, and the local information enhancement module is employed to capture the global and local correlations of the traffic volume. The EIGRN was evaluated using the real datasets PEMS-BAY and PeMSD7(M) to assess its predictive performance The results indicate that the forecasting performance of the EIGRN is better than the comparison models.
Factors Impacting Occupational Safety among Women Engineers

On the one hand, in the present era, construction companies are one of Egypt’s fastest-growing industries and provide significant economic returns. On the other hand, construction industries significantly put individuals in danger of accidental death. In this study, the researchers examined the factors that affect Occupational Safety (OCS) measures among women engineers working in Egypt’s construction industries. This is a quantitative study that used cross-sectional data, and the researchers used 376 usable samples. By applying Structural Equation Modeling (SEM), this study’s findings demonstrate that the Work Environment (WEN), Personal Protection (PP), Training and Education of Safety Skills (TESS), Familiarity with Safety Regulations (FSR) and Safety Commitment (SCT) influence OCS. This study’s findings will help policymakers and planners design effective safety policies on construction sites. This study’s findings about adopting precautionary and safety measures will help reduce the death rates on Egypt’s construction sites. Finally, particularly in developing countries, this study’s findings will contribute to the health and safety and environment and health literature.
Pathogenicity and Genomic Characterization of a Novel Genospecies, Bacillus shihchuchen, of the Bacillus cereus Group Isolated from Chinese Softshell Turtle (Pelodiscus sinensis)

The Chinese softshell turtle (CST; Pelodiscus sinensis) is a freshwater aquaculture species of substantial economic importance that is commercially farmed across Asia, particularly in Taiwan. Although diseases caused by the Bacillus cereus group (Bcg) pose a major threat to commercial CST farming systems, information regarding its pathogenicity and genome remains limited. Here, we investigated the pathogenicity of Bcg strains isolated in a previous study and performed whole-genome sequencing. Pathogenicity analysis indicated that QF108-045 isolated from CSTs caused the highest mortality rate, and whole-genome sequencing revealed that it was an independent group distinct from other known Bcg genospecies. The average nucleotide identity compared to other known Bcg genospecies was below 95%, suggesting that QF108-045 belongs to a new genospecies, which we named Bacillus shihchuchen. Furthermore, genes annotation revealed the presence of anthrax toxins, such as edema factor and protective antigen, in QF108-045. Therefore, the biovar anthracis was assigned, and the full name of QF108-045 was Bacillus shihchuchen biovar anthracis. In addition to possessing multiple drug-resistant genes, QF108-045 demonstrated resistance to various types of antibiotics, including penicillins (amoxicillin and ampicillin), cephalosporins (ceftifour, cephalexin, and cephazolin), and polypeptides, such as vancomycin.
Comparing the Spatial Distribution of Popular Destinations in the Era of Mobile Internet: Case Studies of 9 Cities in the Pearl River Delta

In the era of mobile Internet, the development of the influencer economy has given rise to emerging consumer spaces and popular destinations, which are new hot topics for urban public space research. Based on TikTok popular destinations check-in data and using statistical analysis, kernel density analysis, and optimized hotspot method, this study quantitatively measures different spatial distributions of popular destinations in the Pearl River Delta and nine cities within it and explores the relationship between spatial structure and built environment and the causes. The results show that the spatial distribution of popular destinations shows an obvious dual structure, and the spatial hotness spreads and decreases from the central cities (Guangzhou and Shenzhen) to the peripheral cities. Meanwhile, the spatial distribution characteristics of popular destinations within different cities have obvious heterogeneity, and the heterogeneity of developed cities is weaker than that of less developed cities.
A Critical Review on Vasoactive Nutrients for the Management of Endothelial Dysfunction and Arterial Stiffness in Individuals under Cardiovascular Risk

Pathophysiological conditions such as endothelial dysfunction and arterial stiffness, characterized by low nitric oxide bioavailability, deficient endothelium-dependent vasodilation and heart effort, predispose individuals to atherosclerotic lesions and cardiac events. Nitrate (NO3−), L-arginine, L-citrulline and potassium (K+) can mitigate arterial dysfunction and stiffness by intensifying NO bioavailability. Dietary compounds such as L-arginine, L-citrulline, NO3− and K+ exert vasoactive effects as demonstrated in clinical interventions by noninvasive flow-mediated vasodilation (FMD) and pulse-wave velocity (PWV) prognostic techniques. Daily L-arginine intakes ranging from 4.5 to 21 g lead to increased FMD and reduced PWV responses. Isolated L-citrulline intake of at least 5.6 g has a better effect compared to watermelon extract, which is only effective on endothelial function when supplemented for longer than 6 weeks and contains at least 6 g of L-citrulline. NO3− supplementation employing beetroot at doses greater than 370 mg promotes hemodynamic effects through the NO3−-NO2-/NO pathway, a well-documented effect. A potassium intake of 1.5 g/day can restore endothelial function and arterial mobility, where decreased vascular tone takes place via ATPase pump/hyperpolarization and natriuresis, leading to muscle relaxation and NO release. These dietary interventions, alone or synergically, can ameliorate endothelial dysfunction and should be considered as adjuvant therapies in cardiovascular diseases.
Nafion-Based Layer-by-Layer Coatings with Antimicrobial Activity

: With the need for non-antibiotic approaches to microbial pathogenesis being ever present, the development of alternatives centred around infection prevention is of deep importance. Antimicrobial surface coatings offer a promising approach, as they can possess multiple favourable qualities such as low toxicity, longevity, and the capacity for re-coating. Of the possible coating methods, layer-by-layer (LbL) deposition provides a particularly useful approach, allowing for the facile creation of multilayered coatings on pre-existing surfaces. For these LbL coatings, Naﬁon, a synthetic polymer with excellent mechanical properties, was used as a stable foundation for two model trilayer systems. Both sets of systems comprised Naﬁon layered alongside compounds with well-established antimicrobial activity: lysozyme, chitosan, and carbon dots (CDots). In addition to their antimicrobial properties, lysozyme and chitosan are both nontoxic and biocompatible, making them ideal for biomedical applications. Similarly, CDots have low toxicity but also possess ﬂuorescent properties, opening up the potential for the assessment of coating integrity, making these coatings suitable for high-wear surfaces. As such, the two trilayer systems were made of, respectively, Naﬁon, lysozyme, and chitosan; and Naﬁon, lysozyme, and CDots. When assessed against the represen-tative Gram-negative and Gram-positive species Escherichia coli ( E. coli ) and Staphylococcus aureus ( S. aureus ), respectively, both trilayer systems showed excellent antimicrobial activity, producing up to 3 log reductions in colony-forming units compared with a control. The activity of both sets of systems, alongside the similar activity between systems, showed both good synergy between and interchangeability of layer components, opening up the possibility for further tailoring in future.
The Effect of Enterprise Risk Management and Environmental Performance Toward Corporate Social Responsibility Disclosure (CSRD): Study in Mining Sector

The population is 47 Mining companies in IDX 2016-2018. Have PROPER rating and published annual report. The purpose to examine the effect of enterprise risk management(ERM) and environmental performance (EP) toward CSR Disclosure. Data were obtained from 63 samples and used sample selection method, purposive sampling method and IBM SPSS 26. The analysis statistic used is multiple linear regression analysis method. The ERM used COSO ERM Framework to disclosure 108 items, EP used PROPER rating represent in 5 ranking and CSRD used GRI G4 CSR index consisting 91 items, 3 categories. The study result shows that ERM have positive and significant effect on CSRD, while EP does not have significant affect on CSRD.
Effect of Chemical Refining on the Reduction of β-Carboline Content in Sesame Seed Oil

β-carbolines (harman and norharman) are potentially mutagenic and have been reported in some vegetable oils. Sesame seed oil is obtained from roasted sesame seeds. During sesame oil processing, roasting is the key procedure to aroma enhancement, in which β-carbolines are produced. Pressed sesame seed oils cover most market share, while leaching solvents are used to extract oils from the pressed sesame cake to improve the utilization of the raw materials. β-carbolines are nonpolar heterocyclic aromatic amines with good solubility in leaching solvents (n-hexane); therefore, the β-carbolines in sesame cake migrated to the leaching sesame seed oil. The refining procedures are indispensable for leaching sesame seed oil, in which some small molecules can be reduced. Thus, the critical aim is to evaluate the changes in β-carboline content during the refining of leaching sesame seed oil and the key process steps for the removal of β-carbolines. In this work, the levels of β-carbolines (harman and norharman) in sesame seed oil during chemical refining processes (degumming, deacidification, bleaching and deodorization) have been determined using solid phase extraction and high performance liquid chromatography-mass spectrometry (LC-MS). The results indicated that in the entire refining process, the levels of total β-carbolines greatly decreased, and the adsorption decolorization was the most effective process in reducing β-carbolines, which might be related to the adsorbent used in the decolorization process. In addition, the effects of adsorbent type, adsorbent dosage and blended adsorbent on β-carbolines in sesame seed oil during the decolorization process were investigated. It was concluded that oil refining can not only improve the quality of sesame seed oil, but also reduce most of the harmful β-carbolines.
Complex Valued Long Short Term Memory Based Architecture for Frequency Domain Photoacoustic Imaging

Frequency domain photoacoustic (FDPA) imaging has great potential in a clinical setting compared to time-domain photoacoustic imaging due to its reduced cost and small form factors. However FDPA system struggles with lower signal to noise ratio, necessitating the need for advanced image reconstruction methods. Most of the image reconstruction approaches in FDPA imaging are based on analytical or model based schemes. Very less emphasis has been placed on developing deep learning based approaches for FDPA imaging. In this work, a image translation network was developed with the ability to directly map from sinogram data (complex-valued) to the initial pressure rise distribution (real-valued) for FD-PA imaging. This architecture was based on a Long Short Term Memory (LSTM) backbone (with adjoined real and imaginary parts of the complex sinogram data as input) followed by a fully connected layer, which is then passed through a convolution and transposed convolution layer pair. The result of the FDPA-LSTM architecture was compared with direct translational networks based on ResNet, UNet and AUTOMAP and found to have an improvement of about 15% in terms of PSNR and 10% in terms of SSIM with $150^{\circ }$ data acquisition limited-view angle. Further, the FDPA-LSTM was also compared with post-processing UNet architecture on backprojection and Tikhonov regularized reconstruction. A 20% improvement in terms of PSNR with backprojection and post-processing UNet was observed. Further FDPA-LSTM had similar performance as Tikhonov and post-processing UNet (with 75 times acceleration). The developed scheme will indeed be very useful for achieving accelerated and accurate frequency domain photoacoustic imaging.