Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of and Prospects for the Hierarchical Medical Policy in Beijing, China

Hierarchical medical policies are widely used worldwide to reduce healthcare costs, rationalize the use of healthcare resources, and improve accessibility and fairness of healthcare services. However, few case studies have evaluated the effects and prospects of such policies. Medical reform efforts in China have distinct goals and characteristics. Therefore, we investigated the effects of a hierarchical medical policy in Beijing and assessed the future potential of the policy to yield insights for other countries, especially developing countries. Different methods were used to analyze multidimensional data from official statistics, a questionnaire survey of 595 healthcare workers from 8 representative public hospitals in Beijing, a questionnaire survey of 536 patients, and 8 semi-structured interview records. The hierarchical medical policy had strong positive effects on improving access to healthcare services, balancing the workload of healthcare workers in various levels of public hospitals, and improving the management of public hospitals. The remaining obstacles include severe job stress among healthcare workers, the high cost of some healthcare services, and the need for improvement in the development level and service capacity of primary hospitals. This study provides useful policy recommendations regarding the implementation and extension of the hierarchical medical policy, including the need for governments to improve the hospital assessment system and for hospitals to actively participate in developing medical partnerships.
Analysis of paracardial adipose tissues using deep learning segmentation in CT calcium score images

Epicardial (EAT) and paracardial (PAT) adipose tissues (inside and outside the pericardial sac, respectively) are thought to be associated with major adverse cardiovascular events (MACE). Our long-term goal is to include PAT and EAT in a comprehensive survival analysis of MACE. Here we developed an automated method for segmenting PAT in computed tomography calcium score (CTCS) scans. Analysts identified the top and bottom heart slices by anatomical evidence, and segmented PAT in a slice-by-slice basis. Our proposed PAT segmentation approach (DeepPAT) used preprocessing steps and a multi-class automated semantic segmentation (DeepLab-v3plus) network. Preprocessing steps incorporated filtering to reduce noise, window-leveling to draw attention to sac, and morphological operations to close gaps within mask volumes. DeepPAT was trained/tested on (30/22) CTCS scans from the University Hospitals of Cleveland. The output mask voxels were classified as either enclosed sac, PAT, or background. PAT region is further thresholded with standard fat HU range [-190, -30]. The DeepPAT showed excellent segmentation compared to ground truth (manual) with an average Dice score (82.5%±3.93) and correlation of (R=99.23%, P<<0.001). PAT volume difference was (4.08%±7.78) while the PAT mean HU value changed (2.65%±4.72). The EAT and PAT volumes had a noticeable correlation R=82.9% (P<<0.001). Volumes for MACE/no-MACE (5/17 patients) subgroups showed significance for PAT (P= 0.023), while EAT had better significance (P=0.004). Mean HU values showed less significance in both PAT (p=0.81) and EAT (p=0.18). Our research results offer valuable insights that can be utilized for cardiovascular risk assessment studies.
Social Media Sentiment about COVID-19 Vaccination Predicts Vaccine Acceptance among Peruvian Social Media Users the Next Day

Drawing upon theories of risk and decision making, we present a theoretical framework for how the emotional attributes of social media content influence risk behaviors. We apply our framework to understanding how COVID-19 vaccination Twitter posts influence acceptance of the vaccine in Peru, the country with the highest relative number of COVID-19 excess deaths. By employing computational methods, topic modeling, and vector autoregressive time series analysis, we show that the prominence of expressed emotions about COVID-19 vaccination in social media content is associated with the daily percentage of Peruvian social media survey respondents who are vaccine-accepting over 231 days. Our findings show that net (positive) sentiment and trust emotions expressed in tweets about COVID-19 are positively associated with vaccine acceptance among survey respondents one day after the post occurs. This study demonstrates that the emotional attributes of social media content, besides veracity or informational attributes, may influence vaccine acceptance for better or worse based on its valence.
PERSEPSI LANSIA TERHADAP VAKSINASI COVID-19 DI KELURAHAN PASIE NAN TIGO KECAMATAN KOTO TANGAH KOTA PADANG

Realisasi vaksinasi untuk warga lanjut usia di Sumatera Barat masih rendah. Berdasarkan data dari Dinas Kesehatan Sumbar hingga November 2021, realisasi vaksinasi lansia baru mencapai 20,88 persen dari target 488.575 orang untuk tahap I dan untuk vaksinasi tahap II yaitu 7,6 persen. Persepsi yang salah, pengetahuan yang kurang, serta informasi yang kurang menjadi penyebab kurangnya kepatuhan lansia dalam mengikuti program vaksinasi COVID-19. Tujuan penelitian ini adalah untuk mengeksplorasi persepsi lansia di RW 14 Kelurahan Pasie Nan Tigo terhadap vaksinasi COVID-19. Jenis penelitian ini adalah penelitian kualitatif dengan pendekatan studi fenomenologi dengan metode wawancara mendalam. Pemilihan partisipan yang digunakan yaitu metode purposive sampling. Jumlah partisipan dalam penelitian ini sebanyak 4 orang lansia di RW 14 Kelurahan Pasie Nan Tigo. Hasil penelitiannya didapatkan 3 (tiga) tema yaitu keterbatasan pengetahuan lansia tentang vaksinasi COVID-19, ketidaksiapan lansia dalam mengikuti program vaksinasi, dan kurangnya dukungan keluarga. Diharapkan dengan adanya penelitian ini, pelayanan yang diberikan oleh puskesmas lubuk buaya lebih baik lagi terutama dalam memberikan edukasi atau pendidikan kesehatan kepada masyarakat terutama lansia terkait vaksinasi COVID-19
Millimeter-Wave Wideband ±45° Dual-Polarized Phased Array Antenna Based on Compact Wideband Widebeam Dipole Element Antenna

To meet the requirements of a millimeter-wave (mmWave) communication system prototype complying with 5G (24.25–29.5 GHz) and B5G/6G (30–33 GHz) standards, this letter presents a compact wideband widebeam ±45° dual-polarized dipole element antenna to form a wideband phased array antenna (PAA) covering the entire 24–33 GHz (∼31.6%) band. First, by placing two orthogonal coupling feeding baluns over a dual-polarized dipole to excite the dipole's two pairs of orthogonal arms and employing four parasitic patches, a ±45° dual-polarized dipole element antenna is developed, showing a compact size (0.34λ0 × 0.34λ0 at 24 GHz), wide −14 dB impedance bandwidth (24–33 GHz, 31.6%), wide 3 dB beamwidth (>100°), high polarization isolation (>25 dB), and high cross polarization discrimination (XPD) (>25 dB) within the −14 dB impedance bandwidth. Then, based on the element antenna, a 4 × 4-element ±45° dual-polarized PAA is designed, fabricated using the low temperature co-fired ceramic (LTCC) process, and measured. The measurements show that, within the entire 24–33 GHz band, the broadside scanning gain of the PAA is up to 14 dBi, and the 3 dB gain variation scanning range is >±41° with a peak up to ±60°.
John von Neumann between Physics and Economics: A methodological note

A methodological discussion is proposed, aiming at illustrating an analogy between game theory in particular (and mathematical economics in general) and quantum mechanics. This analogy relies on the equivalence of the two fundamental operators employed in the two fields, namely, the expected value in economics and the density matrix in quantum physics. I conjecture that this coincidence can be traced back to the contributions of von Neumann in both disciplines.
Ultrasensitive Plasmonic Detection of Molecules with Graphene

Graphene plasmons can couple with vibrations in both extended and local systems, for example, phonons in polar crystals and molecular vibrations in polymers. These interactions are characterized by plasmon-induced transparency features within the plasmon infrared absorption profile. Detection enhancement made possible by graphene-based plasmon-induced transparency has been demonstrated in both polymer and protein films and has shown to offer superior detection capabilities compared to conventional metal dipole plasmonic sensors. Here, we demonstrate the detection of molecular vibrations in minute, residual molecular quantities of solid- and gas-phase molecules down to 50 zeptomol/μm2 using graphene plasmonic sensing platforms. Plasmon-induced transparency enhancement is shown to be sensitive to both the specific molecular coordination of the measured vibrations and to the distribution of modes within the measured vibrational bands. This work could lead to the development of functionalization-free, chemica.
Innovative Metrics for Reporting and Comparing the Glycan Structural Profile in Biotherapeutics

Glycosylation is a critical quality attribute in biotherapeutics, impacting properties such as protein stability, solubility, clearance rate, efficacy, immunogenicity, and safety. Due to the heterogenic and complex nature of protein glycosylation, comprehensive characterization is demanding. Moreover, the lack of standardized metrics for evaluating and comparing glycosylation profiles hinders comparability studies and the establishment of manufacturing control strategies. To address both challenges, we propose a standardized approach based on novel metrics for a comprehensive glycosylation fingerprint which greatly facilitates the reporting and objective comparison of glycosylation profiles. The analytical workflow is based on a liquid chromatography–mass spectrometry-based multi-attribute method. Based on the analytical data, a matrix of glycosylation-related quality attributes, both at site-specific and whole molecule level, are computed, which provide metrics for a comprehensive product glycosylation fingerprint. Two case studies illustrate the applicability of the proposed indices as a standardized and versatile approach for reporting all dimensions of the glycosylation profile. The proposed approach further facilitates the assessments of risks associated with changes in the glycosylation profile that may affect efficacy, clearance, and immunogenicity.
Impact of Meteorological Conditions on PM2.5 Concentration in Delhi

Air pollution has been a widespread concern in recent years. It is an alarming issue due to the adverse effects of impurities, particularly on human health. The presence of the influence of the meteorological factors on the concentration of pollutants becomes the major subject of interest, as the determination of the correlation would help to explore the dynamics of the concentration of air pollutants. In this work, the existence of cross-correlation between pollutant PM2.5 and four meteorological factors, including temperature, humidity, pressure, and wind speed has been unraveled for Delhi using Multifractal cross-correlation detrended fluctuation analysis (MF-X-DFA) method. The daily data of the air pollutant PM2.5 and four meteorological factors have been obtained from the Central Pollution Control Board (CPCB) for the years 2015 to 2019. The exploration shows that the cross-correlation between PM2.5 and all the four factors are persistent and long-range correlated also confirming multifractality. Meanwhile, the strength of the multifractal spectrum of wind speed is found to be strongest thus the effect of wind speed on PM2.5 concentration is obvious to be most pronounced. Hence it becomes evident from Hurst exponent values and multifractal spectrum that not only wind speed rather temperature, humidity, and wind speed combined can bring a massive change in concentration of PM2.5.
Constraining modes and rates of horizontal deformation along east Qinling fault system from rotated river basins

The planform rotation of river basins has been used as a marker of crustal strain and been used to assess the style and rates of on‐fault deformation. We use the geometry of river basins to evaluate horizontal deformation associated with the South China–North China relative block motion in the east Qinling mountains. The long‐time average slip rates of the Luonan fault and Shangdan fault are constrained as 0.31 mm/year and 0.3–0.6 mm/year, respectively. According to the latest GPS, we believe that a minor portion of the crustal strain of relative block motion between North China and South China was partitioned into the east Qinling strike‐slip fault system, leaving a major portion of deformation to be accommodated by southern North China (SNC). We conclude that the eastward extrusion of South China cannot explain the present deformation of the entire eastern China, and more attention should be paid into the SNC.
Reading Elementary Principles: Gibbs and the origin of statistical mechanics

Josiah Willard Gibbs (1839–1903) is famous for his contributions to statistical mechanics (fig. 1). In 1902, he published Elementary Principles in Statistical Mechanics, in which he systematically developed the ensemble theory of statistical mechanics [1]. The importance of this work is illustrated by the fact that Landau and Lifshitz’s Courses of Theoretical Physics regarded Gibbs’ method as fundamental [2]. Albert Einstein (1879–1955)—who independently developed his own version of statistical mechanics from 1902 to 1904, having no knowledge of Gibbs’ work—remarked in 1910 “Had I been familiar with Gibbs’ book at that time, I would not have published those papers at all, but would have limited myself to the discussion of just a few points” [3, p. 176]. Gibbs’ theory was a well-developed infrastructure that later physicists could employ to solve concrete problems. Despite of its importance, however, it has rarely been examined by historians of science, probably because of its abstractness and difficulty.1 In fact, there are considerable differences between Gibbs’ and today’s theories of statistical mechanics. To see the differences, let us study the nuances and contexts of Gibbs’ book. Gibbs began his scientific career as a researcher in thermodynamics. In 1876 and 1878, he published a long article in two parts that presented a theoretical formulation of thermodynamics based on equilibrium criteria expressed in energetic and entropic variations of thermal systems. This article provided details regarding Helmholtz free energy, Gibbs free energy, and enthalpy, thereby explaining a broad range of phenomena in equilibrium such as critical phenomena, osmotic pressure, and chemical cells [5]. It is interesting to compare the contents of this paper with Planck’s thermodynamic investigations that
Research on optimal route planning and delivery strategy of multiple robots using HCA algorithm in a restaurant

As science and technology advance quickly,, many machines are gradually replacing labor, such as intelligent catering robots with some advanced functions (automatic meal delivery, voice output, and power detection functions etc.) can gradually replace waiters to serve customers. I This essay investigates the issue of multi-robot collaborative delivery in a restaurant setting. The paper analyzes the optimal delivery path from the perspectives of restaurant environment, robot morphology, algorithm selection and the comparison of road planning. And in order to be more realistic, experiments were conducted by changing some obstacles in the restaurant environment to find the optimal delivery strategy for robots. From this article, it shows that multi-robots work in restaurants can solve the artificially shortages, reduce labor costs, improve the service efficiency and quality of restaurants and bring more benefits to restaurants.
An Easy-To-Update Pulse-Like Ground Motion Identification Method Based on Siamese Convolutional Neural Networks

ABSTRACT A pulse-like ground motion identification method is proposed based on the Siamese Convolutional Neural Networks (SCNNs). The wavelet coefficient graphs of pulse-like ground motions are used as the input data, and the features extracted by the SCNNs are used for the identification. Based on the time-domain features, pulse-like and non-pulse-like ground motions are classified into several classes. The results indicated that all the identified pulse-like ground motions have similar pulse features to the pre-selected training data. The principal advantage of the method is that the misclassification problem can be minimized by an updating procedure proposed by this paper.
Performance Analysis of Efficiently trusted AODV serving Security in MANET under Blackhole Attack Using Genetic Algorithm

The mobile nodes or systems in mobile ad hoc networks wirelessly transmit binary data. The topology of the network is dynamic. Therefore, because of the network's wireless nature, sensitive data is vulnerable to uninvited external attackers, sometimes known as data theft or loss by an attacking or malicious node For the network to operate more efficiently and to preserve safe connectivity, these hostile nodes must be identified. A trust based routing protocol is proposed here with genetic algorithm to identify the attack in MANET using AODV protocol. The performance analysis is made using NS2 simulator with AODV under attack and with proposed trusted algorithm(ETSAODV) using GA under blackhole attack. In terms of network lifetime and characteristics like throughput and packet delivery ratio in simulation, it maximises the network's performance.
Review of Quantitative Applications of the Concept of the Water Planetary Boundary at Different Spatial Scales

The water planetary boundary (PB) quantifies a safe operating space for human water consumption and is understood as a control‐variable set at a safe distance from a selected threshold (or dangerous level) based on precautionary principles. The water PB is useful for guiding sustainable development, and various multiscale quantitative assessments of water PB have been conducted. To improve our understanding and guide future applications, we conduct a comprehensive review of all studies published since the concept's introduction. We identify a total of 288 relevant papers in the literature and perform a systematic review and meta‐analysis of 28 papers providing 488 data records at various spatial scales. The analyses mainly involve the relevant quantification indicators, quantification methods, comparisons of the water PB with the current state of water consumption at different scales, and the identification of associated problems. Finally, we propose 10 outlooks for important future research. This review indicates that the theoretical water‐PB framework, as an early‐stage research area, has gradually developed, despite the few, imperfect available methods. To address the limitations of previous studies, we propose two improvement frameworks for guiding future research: the further improvement of traditional popular approaches to quantifying the multiscale water PB within a consistent scientific framework and an improved framework for quantifying the water PB at various scales to obtain better‐fitting results for different research purposes and study areas. Based on this review, we point out some important issues that have received little attention, including the quantification of safe distances and the linkages between multiscale water PBs.
Covariance Regression Analysis

ABSTRACT This article introduces covariance regression analysis for a p-dimensional response vector. The proposed method explores the regression relationship between the p-dimensional covariance matrix and auxiliary information. We study three types of estimators: maximum likelihood, ordinary least squares, and feasible generalized least squares estimators. Then, we demonstrate that these regression estimators are consistent and asymptotically normal. Furthermore, we obtain the high dimensional and large sample properties of the corresponding covariance matrix estimators. Simulation experiments are presented to demonstrate the performance of both regression and covariance matrix estimates. An example is analyzed from the Chinese stock market to illustrate the usefulness of the proposed covariance regression model. Supplementary materials for this article are available online.
FRET Based Biosensor: Principle Applications Recent Advances and Challenges

Förster resonance energy transfer (FRET)-based biosensors are being fabricated for specific detection of biomolecules or changes in the microenvironment. FRET is a non-radiative transfer of energy from an excited donor fluorophore molecule to a nearby acceptor fluorophore molecule. In a FRET-based biosensor, the donor and acceptor molecules are typically fluorescent proteins or fluorescent nanomaterials such as quantum dots (QDs) or small molecules that are engineered to be in close proximity to each other. When the biomolecule of interest is present, it can cause a change in the distance between the donor and acceptor, leading to a change in the efficiency of FRET and a corresponding change in the fluorescence intensity of the acceptor. This change in fluorescence can be used to detect and quantify the biomolecule of interest. FRET-based biosensors have a wide range of applications, including in the fields of biochemistry, cell biology, and drug discovery. This review article provides a substantial approach on the FRET-based biosensor, principle, applications such as point-of-need diagnosis, wearable, single molecular FRET (smFRET), hard water, ions, pH, tissue-based sensors, immunosensors, and aptasensor. Recent advances such as artificial intelligence (AI) and Internet of Things (IoT) are used for this type of sensor and challenges.
Development and Characterization of an Edible Zein/Shellac Composite Film Loaded with Curcumin

The development of functional edible films is promising for the food industry, and improving the water barrier of edible films has been a research challenge in recent years. In this study, curcumin (Cur) was added to zein (Z) and shellac (S) to prepare an edible composite film with a strong water barrier and antioxidant properties. The addition of curcumin significantly reduced the water vapor permeability (WVP), water solubility (WS), and elongation at break (EB), and it clearly improved the tensile strength (TS), water contact angle (WCA), and optical properties of the composite film. The ZS–Cur films were characterized by SEM, FT-IR, XRD, DSC, and TGA; the results indicated that hydrogen bonds were formed among the curcumin, zein, and shellac, which changed the microstructure and improved the thermal stability of the film. A test of curcumin release behavior showed controlled release of curcumin from the film matrix. ZS–Cur films displayed remarkable pH responsiveness, strong antioxidant properties, and inhibitory effects on E. coli. Therefore, the insoluble active food packaging prepared in this study provides a new strategy for the development of functional edible films and also provides a possibility for the application of edible films to extend the shelf life of fresh food.
Machine Learning for Physical Layer Security: Limitations, Challenges and Recommendation

The properties and features of wireless channels have recently attracted the attention of researchers since they include valuable and powerful parameters for security services. This has paved the way for a new security paradigm, Physical Layer Security (PLS). To further improve the performance and security of such technology, it is recently being combined with machine learning algorithms to provide authentication, confidentiality and intrusion detection. Motivated by the novel advancements in this field, we present a brief overview of the different machine learning techniques and algorithms that offer PLS-based security services. These techniques are discussed in details to shed the light on the existing methods in the literature. We also propose several recommendations for enhancing the performance and efficiency of the presented schemes.