Miracle-dz/UniFAR-FTUs huggingface dataset:
Measuring China's urban digital economy

Digital economy is the core driver of high-quality economic development. How to evaluate the development of the digital economy reasonably and scientifically has become a top priority. Taking 278 prefecture-level cities in the Chinese Mainland from 2010 to 2020 as the research subject, this paper first constructs the digital economy indicator system of Chinese cities from four dimensions: digital industry, digital users, digital innovation, and digital platforms. Then, this paper adopts the gray-target entropy weight method to calculate the digital economy index and sub-indexes of Chinese cities. Finally, this paper analyzes the development of China's urban digital economy from the statistical characteristics and development trends of the index and sub-indexes. The results show that China's urban digital economy and the four dimensions, have experienced stable development from 2010 to 2020, but there is regional heterogeneity. This is mainly reflected in the differences in the development speed of different cities in these dimensions, making the gap among different cities expanding year by year. Additionally, from the perspective of city types, central cities have unique advantages in the development of digital economy, taking a leading position in all dimensions of the digital economy, while non-central cities have great potential for developing digital economy.
Radiovaccination Strategy for Cancer Treatment Integrating Photodynamic Therapy-Generated Vaccines with Radiotherapy

Therapeutic cancer vaccines have become firmly established as a reliable and proficient form of tumor immunotherapy. They represent a promising approach for substantial advancements in the successful treatment of malignant diseases. One attractive vaccine strategy is using, as the vaccine material, the whole tumor cells treated ex vivo by rapid tumor ablation therapies that instigate stress signaling responses culminating in immunogenic cell death (ICD). One such treatment is photodynamic therapy (PDT). The underlying mechanisms and critical elements responsible for the potency of these vaccines are discussed in this review. Radiotherapy has emerged as a suitable component for the combined therapy protocols with the vaccines. Arguments and prospects for optimizing tumor control using a radiovaccination strategy involving X-ray irradiation plus PDT vaccines are presented, together with the findings supporting its validity.
Fatigue and Cognitive Dysfunction Are Associated with Occupational Status in Post-COVID Syndrome

Post-COVID syndrome (PCS) is a medical condition characterized by the persistence of a wide range of symptoms after acute infection by SARS-CoV-2. The work capacity consequences of this disorder have scarcely been studied. We aimed to analyze the factors associated with occupational status in patients with PCS. This cross-sectional study involved 77 patients with PCS on active work before SARS-CoV-2 infection. Patients were evaluated 20.71 ± 6.50 months after clinical onset. We conducted a survey on occupational activity and cognitive and clinical symptoms. The association between occupational activity and fatigue, depression, anxiety, sleep quality, and cognitive testing was analyzed. Thirty-eight (49.4%) patients were working, and thirty-nine (50.6%) patients were not. Of those not working at the moment of the assessment, 36 (92.3%) patients were on sick leave. In 63 patients (81.8% of the sample), sick leave was needed at some point due to PCS. The mean duration of sick leave was 12.07 ± 8.07 months. According to the patient’s perspective, the most disabling symptoms were cognitive complaints (46.8%) and fatigue (31.2%). Not working at the moment of the assessment was associated with higher levels of fatigue and lower cognitive performance in the Stroop test. No association was found between occupational status with depression and anxiety questionnaires. Our study found an influence of PCS on work capacity. Fatigue and cognitive issues were the most frequent symptoms associated with loss of work capacity.
Reliability and Utility of Various Methods for Evaluation of Bone Union after Anterior Cervical Discectomy and Fusion

Most surgical procedures performed on account of degenerative disease of the cervical spine involve a discectomy and interbody fixation. Bone fusion at the implant placement site is evaluated post-operatively. It is agreed that computed tomography is the best modality for assessing bone union. We evaluated the results obtained with various methods based solely on conventional radiographs in the same group of patients and compared them with results obtained using a method that is a combination of CT and conventional radiography, which we considered the most precise and a reference method. We operated on a total of 170 disc spaces in a group of 104 patients. Fusion was evaluated at 12 months after surgery with five different and popular classifications based on conventional radiographs and then compared with the reference method. Statistical analyses of test accuracy produced the following classification of fusion assessment methods with regard to the degree of consistency with the reference method, in descending order: (1) bone bridging is visible on the anterior and/or posterior edge of the operated disc space on a lateral radiograph; (2) change in the value of Cobb’s angle for a motion segment on flexion vs. extension radiographs (threshold for fusion vs. pseudoarthrosis is 2°); (3) change in the interspinous distance between process tips on flexion vs. extension radiographs (threshold of 2 mm); (4) change in the value of Cobb’s angle of a motion segment (threshold of 4°); (5) change in the interspinous distance between process bases on flexion vs. extension radiographs (threshold of 2 mm). When bone union is evaluated on the basis on radiographs, without CT evidence, we suggest using the “bone bridging” criterion as the most reliable commonly used approach to assessing bone union.
Exploring the Effects of the COVID-19 Pandemic on Mental Health and Well-Being of Migrant Populations in Europe: An Equity-Focused Scoping Review

The pandemic is aggravating health inequalities, particularly mental health inequalities, while revealing the social determinants of these inequalities, including migration as a social determinant that mediates the interaction of social, economic, cultural, institutional, and structural factors with health indicators. Therefore, it is of most relevance to identify the multiple interconnected factors that influence the mental health and well-being of migrant populations. A scoping review was developed to map the research performed in this area and to identify any gaps in knowledge, following the PRISMA extension for scoping reviews. MEDLINE, Scopus, and WHO Global Health research databases on COVID-19 were searched from January 2020 to October 2021. The review followed the inclusion criteria Population/Concept/Context (PCC): Population-Adult International migrants (including refugees, asylum seekers, and undocumented migrants); Concept-determinants of (and factors influencing) mental health and well-being; Context-COVID-19 anywhere in the world. Of the sixty-five selected studies, eleven were from European countries and were the focus of this review with special attention to health inequalities experienced by migrants in Europe. The results cover a diversity of themes related to the effects of COVID-19 on the mental health of migrants (country-level environmental factors, social determinants of mental health, mental health indicators and outcomes), responses (such as solidarity and resilience), populations, and study methods. The evidence found can inform recommendations and interventions focused on health promotion and mitigation of the inequalities accentuated by the pandemic.
Isolation of Phenolic Compounds from Raspberry Based on Molecular Imprinting Techniques and Investigation of Their Anti-Alzheimer’s Disease Properties

Alzheimer’s disease is the most common neurodegenerative disease, characterized by memory loss and cognitive dysfunction. Raspberry fruits contain polyphenols which have antioxidant and anti-inflammatory properties. In this study, we used molecular imprinting technology to efficiently isolate phenolic components from the raspberry ethyl acetate extracts. Six phenolic components (ellagic acid, tiliroside, kaempferol-3-o-rutoside, gallic acid, ferulic acid and vanillic acid) were identified by UPLC-Q-TOF-MS analysis. Molecular docking was used to predict the anti-inflammatory effects and anti-Alzheimer’s potential of these isolated compounds, which showed a good binding ability to diseases and related proteins. However, the binding energy and docking fraction of ellagic acid, tiliroside, and kaempferol-3-o-rutoside were better than those of gallic acid, ferulic acid and vanillic acid. Additionally, by studying the effects of these six phenolic components on the LPS-induced secretion of inflammatory mediators in murine microglial (BV2) cells, it was further demonstrated that they were all capable of inhibiting the secretion of NO, IL-6, TNF-α, and IL-1β to a certain extent. However, ellagic acid, tiliroside, and kaempferol-3-o-rutoside have better inhibitory effects compared to others. The results obtained suggest that the phenolic components extracted from ethyl acetate extracts of raspberry by molecularly imprinted polymers have the potential to inhibit the progression of Alzheimer’s disease.
The Tetrahydrofuran Motif in Marine Lipids and Terpenes

Heterocycles are particularly common moieties within marine natural products. Specifically, tetrahydrofuranyl rings are present in a variety of compounds which present complex structures and interesting biological activities. Focusing on terpenoids, a high number of tetrahydrofuran-containing metabolites have been isolated during the last decades. They show promising biological activities, making them potential leads for novel antibiotics, antikinetoplastid drugs, amoebicidal substances, or anticancer drugs. Thus, they have attracted the attention of the synthetics community and numerous approaches to their total syntheses have appeared. Here, we offer the reader an overview of marine-derived terpenoids and related compounds, their isolation, structure determination, and a special focus on their total syntheses and biological profiles.
Earthwork Volume Calculation, 3D Model Generation, and Comparative Evaluation Using Vertical and High-Oblique Images Acquired by Unmanned Aerial Vehicles

In civil engineering and building construction, the earthwork volume calculation is one of the most important factors in the design and construction stages; therefore, an accurate calculation is necessary. Moreover, because managing earthworks is highly important, in this study, a three-dimensional (3D) model for earthwork calculation and management was performed using an unmanned aerial vehicle (UAV) and an RGB camera. Vertical and high-oblique images (45°, 60°, and 75°) were acquired at 50 and 100 m heights for accurate earthwork calculations and a 3D model, and data were generated by dividing the images into eight cases. Cases 1–4 were images acquired from a height of 50 m, and cases 5–8 were images acquired from a height of 100 m. (case 1: 90°, case 2: 90° + 45°, case 3: 90° + 60°, case 4: 90° + 75°, case 5: 90°, case 6: 90° + 45°, case 7: 90° + 60°, case 8: 90° + 75°). Three evaluations were performed on the data. First, the accuracy was evaluated through checkpoints for the orthophoto; second, the earthwork volumes calculated via a global positioning system and UAV were compared; finally, the 3D model was evaluated. Case 2, which showed the lowest root mean square error in the orthophoto accuracy evaluation, was the most accurate. Case 2 was the most accurate in the earthwork volume evaluation and 3D model compared to other cases. Through this study, the best results were obtained when using a vertical image and a high-oblique image of 40 to 50° when generating a 3D model for earthwork volume calculation and management. In addition, if the UAV is not affected by obstacles, it is better to shoot at about 50 m or less than to shoot the UAV height too high.
In silico study of inhibitory capacity of sacubitril/valsartan toward neprilysin and angiotensin receptor

Heart failure (HF) is a life-threatening condition that occurs when the heart cannot pump enough blood and oxygen to meet the body's needs. It affects mostly the elderly, commonly from the male population, especially those with obesity, diabetes, or some other chronic condition. It can be treated with different medications, and promising results were shown by a relatively new medicament called Entresto. Results obtained from molecular docking and molecular dynamics simulations to examine the inhibitory capacity of Entresto are presented in this study. Parameters obtained by the molecular docking simulations show that both parts of Entresto (sacubitril (SAC) and valsartan (VAL)) interact with targeted proteins, and inhibit their physiological function. Simulations of molecular dynamics revealed some interesting inhibitory patterns. SAC was discovered to produce structural alterations in neprilysin by binding to it, reducing neprilysin's physiological activity. In addition to blocking the active site, SAC binding causes the enzyme's structure to become less compact over time, causing changes in its biochemical characteristics and preventing the enzyme from performing its biological function. Similar to SAC, VAL also causes deviations in the structure of angiotensin receptors. The angiotensin receptor GPCR (G-protein-coupled receptors) is immersed in the lipid bilayer, and changes in the tertiary structure are only visible through RMSD and RMSF, not by examining Rg. In this regard, MD simulations validated the results of molecular docking simulations, demonstrating that both SAC and VAL had inhibitory potential towards the neprilysin and angiotensin receptors, respectively.
On the Bright Side of Correlation Information Transmission

We consider a situation in which a decision maker solicits information from two partially informed experts with uncertain biases. Experts’ private information about an underlying state might be conditionally correlated across them. We show that although correlation tightens the conditions on preferences for a truth-telling equilibrium, in the presence of uncertainty, a high level of correlation may discipline the strongly biased expert and may foster the informational content of the experts’ advice under high uncertainty about correlation. In contrast to what may be expected, it may be optimal for the decision maker to consult two experts with correlated information than consulting two experts with independent information. This result suggests that getting independent opinions may not always be helpful for decision-making.
Google Earth Engine for Informal Settlement Mapping: A Random Forest Classification Using Spectral and Textural Information

Accurate and reliable informal settlement maps are fundamental decision-making tools for planning, and for expediting informed management of cities. However, extraction of spatial information for informal settlements has remained a mammoth task due to the spatial heterogeneity of urban landscape components, requiring complex analytical processes. To date, the use of Google Earth Engine platform (GEE), with cloud computing prowess, provides unique opportunities to map informal settlements with precision and enhanced accuracy. This paper leverages cloud-based computing techniques within GEE to integrate spectral and textural features for accurate extraction of the location and spatial extent of informal settlements in Durban, South Africa. The paper aims to investigate the potential and advantages of GEE’s innovative image processing techniques to precisely depict morphologically varied informal settlements. Seven data input models derived from Sentinel 2A bands, band-derived texture metrics, and spectral indices were investigated through a random forest supervised protocol. The main objective was to explore the value of different data input combinations in accurately mapping informal settlements. The results revealed that the classification based on spectral bands + textural information yielded the highest informal settlement identification accuracy (94% F-score). The addition of spectral indices decreased mapping accuracy. Our results confirm that the highest spatial accuracy is achieved with the ‘textural features’ model, which yielded the lowest root-mean-square log error (0.51) and mean absolute percent error (0.36). Our approach highlights the capability of GEE’s complex integrative data processing capabilities in extracting morphological variations of informal settlements in rugged and heterogeneous urban landscapes, with reliable accuracy.
Cold Start to Improve Market Thickness on Online Advertising Platforms: Data-Driven Algorithms and Field Experiments

Cold start describes a commonly recognized challenge for online advertising platforms: with limited data, the machine learning system cannot accurately estimate the click-through rates (CTR) of new ads and, in turn, cannot efficiently price these new ads or match them with platform users. Traditional cold start algorithms often focus on improving the learning rates of CTR for new ads to improve short-term revenue, but unsuccessful cold start can prompt advertisers to leave the platform, decreasing the thickness of the ad marketplace. To address these issues, we build a data-driven optimization model that captures the essential trade-off between short-term revenue and long-term market thickness on the platform. Based on duality theory and bandit algorithms, we develop the shadow bidding with learning (SBL) algorithms with a provable regret upper bound of [Formula: see text], where K is the number of ads and d captures the error magnitude of the underlying machine learning oracle for predicting CTR. Our proposed algorithms can be implemented in a real online advertising system with minimal adjustments. To demonstrate this practicality, we have collaborated with a large-scale video-sharing platform, conducting a novel, two-sided randomized field experiment to examine the effectiveness of our SBL algorithm. Our results show that the algorithm increased the cold start success rate by 61.62% while compromising short-term revenue by only 0.717%. Our algorithm has also boosted the platform’s overall market thickness by 3.13% and its long-term advertising revenue by (at least) 5.35%. Our study bridges the gap between the theory of bandit algorithms and the practice of cold start in online advertising, highlighting the value of well-designed cold start algorithms for online advertising platforms. This paper was accepted by Gabriel Weintraub, revenue management and market analytics.
Superhydrophobic and oleophobic coatings from flower‐like zinc oxide and fluorinated epoxy with good comprehensive property

Nowadays, most superhydrophobic surfaces will lose their superhydrophobic performance once they encounter oil, and adhesive strength of superhydrophobic coating is low. Therefore, the superhydrophobic coating with good oleophobicity and high adhesive strength is popular with people. A superhydrophobic and oleophobic coating is characteristic of antifouling and self‐cleaning, due to the appearance of special structures, such as overhang and re‐entrant. In this work, flower‐like zinc oxide (ZnO) particles free of fluorine and fluorine‐containing epoxy were used to establish the coating with a similar re‐entrant structure. Flower‐like ZnO particles were prepared by a chemical precipitation method, and the water contact angle of flower‐like ZnO is up to 149 ± 1°. For the coating, flower‐like ZnO particles were almost covered by fluorine‐containing epoxy synthesized through click reaction so that the adhesive strength between the coating and the matrix is high, superior to some coatings in the references. The surfaces made of flower‐like ZnO and fluorinated epoxy possess superhydrophobic and oleophobic properties. The contact angle of the coating for water, diiodomethane, glycerol, and glycol is 154 ± 0.7°, 138 ± 0.6°, 156 ± 0.7°, and 150 ± 0.7°, respectively. After withstanding 70 cycles under the pressure of 1 kPa, the coating is still superhydrophobic. Also, the coating possesses a good self‐cleaning and anti‐icing property.
Moduli of formal A-modules under change of A

We develop methods for computing the restriction map from the cohomology of the automorphism group of a height $dn$ formal group law (i.e., the height $dn$ Morava stabilizer group) to the cohomology of the automorphism group of an $A$-height $n$ formal $A$-module, where $A$ is the ring of integers in a degree $d$ field extension of $\mathbb{Q}_p$. We then compute this map for the quadratic extensions of $\mathbb{Q}_p$ and the height $2$ Morava stabilizer group at primes $p>3$. We show that the these automorphism groups of formal modules are closed subgroups of the Morava stabilizer groups, and we use local class field theory to identify the automorphism group of an $A$-height $1$-formal $A$-module with the ramified part of the abelianization of the absolute Galois group of $K$, yielding an action of $Gal(K^{ab}/K^{nr})$ on the Lubin-Tate/Morava $E$-theory spectrum $E_2$ for each quadratic extension $K/\mathbb{Q}_p$. Finally, we run the associated descent spectral sequence to compute the $V(1)$-homotopy groups of the homotopy fixed-points of this action; one consequence is that, for each element in the $K(2)$-local homotopy groups of the Smith-Toda complex $V(1)$, either that element or its dual is detected in the Galois cohomology of the abelian closure of some quadratic extension of $\mathbb{Q}_p$.
Effect of Changes in Veterinary Feed Directive Regulations on Violative Antibiotic Residues in the Tissue of Food Animals from the Inspector-Generated Sampling in the United States

The presence of antibiotic residues in the tissue of food animals is a growing concern due to the adverse health effects that they can cause in humans, such as antibiotic resistance bacteria. An inspector-generated sampling (IGS) dataset from the United States National Residue Surveillance Program, collected between 2014 and 2019, was analyzed to investigate the association of changes in the veterinary feed directive (VFD) regulations on the detection of violative penicillin, tetracycline, sulfonamide, desfuroylceftiofur, tilmicosin, and florfenicol, residues in the tissue of food animals. Multivariable logistic regression models were used for analysis. While the animal production class was significantly associated with residue violations for tetracycline, having a sample collection date after the implementation of change in VFD regulations was not. However, the odds of detecting violative sulfonamide and penicillin residues in the tissue of food animals following the implementation of the change in VFD regulations were 36% and 24% lower than those collected before the implementation of the change in VFD regulations period, respectively, irrespective of animal production class. Violative desfuroylceftiofur, tilmicosin, and florfenicol residues in the tissue of food animals were not significantly associated with the implementation of changes in the VFD regulations. Further investigation of the factors that influence the presence of violative antibiotic residues in the tissue of food animals following the change in VFD regulations would lend clarity to this critical issue.