Miracle-dz/UniFAR-FTUs huggingface dataset:
Ordering the Zagreb Coindices of Connected Graphs 1

In this paper, we give a simple approach to order the first Zagreb indices of connected graphs and the second Zagreb coindices of trees and unicyclic graphs, respectively. As an application of our new method, we determine the first eight smallest and the first three largest (respectively, first eight smallest and first three largest, first seven smallest and first two largest) values of the first Zagreb coindices in the class of trees (respectively, unicyclic graphs, bicyclic graphs) on n vertices, and we also determine the first eleven (respectively, thirteen) smallest values of the second Zagreb coindices in the class of trees (respectively, unicyclic graphs) on n vertices. Furthermore, we also identify the smallest value of the first Zagreb coindices in the class of � �
A Real-World Study of Achievement Rate and Predictive Factors of Clinical and Deep Remission to Biologics in Patients with Severe Asthma

Background: Recent advances in biologics have provided new insights into the clinical course of asthma, including disease modification, clinical remission (CR), and deep remission (DR). However, the extent to which biologics achieve CR and DR in severe asthma patients is poorly understood. Methods: To assess the achievement rate and predictors of CR and DR using long-term biologics, we retrospectively evaluated 54 severe asthma patients recently started on biologics. “CR” denotes the achievement of all three criteria: (1) absence of asthma symptoms, (2) no asthma exacerbations, and (3) no use of oral corticosteroids. DR denoted CR plus (4) normalized pulmonary function and (5) suppressed type 2 inflammation. Results: CR and DR achievement rates were 68.5% and 31.5%, respectively. Compared with the non-deep remission group, the DR group had higher adult-onset asthma rates (94.1% vs. 70.3%, p = 0.078), shorter asthma duration (5 vs. 19 years, p = 0.006), and higher FEV1 (91.5% vs. 71.5%, p < 0.001). There were no significant differences in the Asthma Control Questionnaire scores, exacerbation frequency, or type 2 inflammation at baseline between groups. Asthma duration combined with FEV1 can stratify the achievement rates of CR and DR. Conclusions: the early introduction of biologics in severe asthma patients may help achieve CR and DR.
Intra Plant Body Signal Transmission Using Capacitive and Galvanic Coupling

Human Body Communication (HBC) technique uses human body as communication channel for transferring various physiological data. Like humans, plants are also composed of different types of tissues with highly specialized functions. For feasibility study of electrical signal transmission through plant body; two pair of electrodes viz. one pair for the transmitter and one pair for the receiver involving stem of full Mangifera Indica plant by using capacitive coupling has been setup. The signal transmission through the different parts of stem of different thickness has been analyzed in time domain at 100 kHz. Different channel lengths have been used for capacitive coupling and different electrode distance has been used for galvanic coupling under similar environmental conditions at room temperature. Effect of positioning the ground electrode in both longitudinal and transverse directions with respect to signal electrode in galvanic coupling has also been investigated and reported in this paper.
Does Downside Risk Matter more in Asset Pricing? Evidence from Indonesia

This study examines downside risk matters in asset pricing, particularly evidence from Indonesia. Using ten reference indexes for passive instruments and 674 companies listed on the Indonesia Stock Exchange between 2020-2021. The four measurements are the traditional families (beta and standard deviation/risk) and downside risk families (semi-deviation and downside beta). For those, we divide 674 stocks into quintiles (5 groups). Every quintile is investigated by four measurements using Fama-Macbeth regression. semi-deviation in those close to standard deviation. Standard deviation affects semi-deviation portfolios in quintiles 1 and 2 and portfolios sorted beta and downside beta in quintile 2. Beta does not affect all portfolios. Eighth, semi-deviation affects portfolios sorted semi-deviation in quintiles 1,2,3,and 5. Downside beta does not affect all portfolios.
Antibacterial and Photocatalytic Activities of LDH-Based Sorbents of Different Compositions

Layered double hydroxides (LDHs) play a fundamental role in the processes for the abatement of pollutants in water, with reference to heavy metal decontamination. The research on the topic is multiobjective target oriented, aiming at combining environmental remediation with the possibility of reusing a sorbent as many times as possible, turning it into a renewable resource. In this study, the antibacterial and catalytic properties of a ZnAl-SO4 LDH and its resulting product after being subjected to a Cr(VI) remediation process are compared. Both solid substrates have also been tested after undergoing a thermal annealing process. The sorbent (previously described and tested for remediation) has been investigated for its antibacterial activity in view of further surgery and drug delivery applications. Finally, its photocatalytic properties have been experimentally tested in the degradation of a model pollutant, i.e., Methyl Orange (MO), under solar-simulated light. Identifying the best recycling strategy for these materials requires an accurate knowledge of their physicochemical properties. The results show that both the antimicrobial activity and the photocatalytic performance may considerably improve after thermal annealing.
Simultaneous Inhibition of Thrombosis and Inflammation Is Beneficial in Treating Acute Myocardial Infarction

Myocardial ischemia reperfusion injury (IRI) in acute coronary syndromes is a condition in which ischemic/hypoxic injury to cells subtended by the occluded vessel continues despite successful resolution of the thrombotic obstruction. For decades, most efforts to attenuate IRI have focused on interdicting singular molecular targets or pathways, but none have successfully transitioned to clinical use. In this work, we investigate a nanoparticle-based therapeutic strategy for profound but local thrombin inhibition that may simultaneously mitigate both thrombosis and inflammatory signaling pathways to limit myocardial IRI. Perfluorocarbon nanoparticles (PFC NP) were covalently coupled with an irreversible thrombin inhibitor, PPACK (Phe[D]-Pro-Arg-Chloromethylketone), and delivered intravenously to animals in a single dose prior to ischemia reperfusion injury. Fluorescent microscopy of tissue sections and 19F magnetic resonance images of whole hearts ex vivo demonstrated abundant delivery of PFC NP to the area at risk. Echocardiography at 24 h after reperfusion demonstrated preserved ventricular structure and improved function. Treatment reduced thrombin deposition, suppressed endothelial activation, inhibited inflammasome signaling pathways, and limited microvascular injury and vascular pruning in infarct border zones. Accordingly, thrombin inhibition with an extraordinarily potent but locally acting agent suggested a critical role for thrombin and a promising therapeutic strategy in cardiac IRI.
An All-Optical 2-Bit Adder Composed of Fabry-Perot Devices

This work models an all-optical 2-bit adder comprised of Fabry-Perot devices. Each device is composed of 2 silver mirrors on either side of a cavity made of a nonlinear Kerr material. These devices are optically bistable and suitable for fast logic operations on the order of picoseconds. We propose to use an amplifying buffer between devices to adjust the transmitted signal's amplitude to the desired value, and to provide control for logic operations. We use the method of finite-difference time-domain (FDTD) in one-dimensional (1D) space to demonstrate the feasibility of the proposed idea.
Determinants of High Breastfeeding Self-Efficacy among Nursing Mothers in Najran, Saudi Arabia

Many factors have been found to correlate with satisfactory Exclusive Breastfeeding (EBF) practices. The relationships between EBF practices and associated factors are complex and multidimensional; Breastfeeding Self-Efficacy (BSE) is the most important psychological factor that may help the mother to overcome any expected barriers. This study investigates the determinants of high breastfeeding self-efficacy among Saudi nursing mothers. Methods: This is a descriptive cross-sectional study investigating the determinant of BSE among 1577 nursing mothers in primary health centers in Najran City, Saudi Arabia. The study uses a cluster random sampling technique. Data collection was performed from June 2022 to January 2023 using a self-reported questionnaire that encompasses the Breastfeeding Self-Efficacy Scale—Short Form (BSES-SF), Gender Friendly Breastfeeding Knowledge Scale (GFBKS), Iowa Infant Feeding Attitude Scale (IIFAS), and a basic data questionnaire to assess women’s demographic factors and obstetric history. Results: The mean score for all BSES-SF items was between 3.23–3.41, the highest mean score was in mothers who felt comfortable breastfeeding with family members present (3.41 ± 1.06), and the lowest mean was in mothers who could breastfeed their baby without using formula as a supplement (3.23 ± 0.94). The overall BSE score was high among 67% of the study participants. Binary logistic regression showed that being a housewife, being highly educated, having breastfeeding experience, and being multiparous are positive predictors for high BSE (p ≤ 0.001). In addition, having adequate breastfeeding knowledge and positive breastfeeding attitudes were positively associated with higher BSE (p = 0.000). Conclusion: BSE can be predicted by modifiable predictors such as mothers’ education, working status, parity, breastfeeding experience, adequate breastfeeding knowledge, and positive attitudes toward breastfeeding. If such predictors are considered during breastfeeding-related educational interventions, it could lead to more effective and sustainable effects in community awareness regarding breastfeeding.
PERBANDINGAN METODE DATA MINING UNTUK MEMPREDIKSI PRESTASI AKADEMIK SISWA

Pada dunia Pendidikan biasanya institusi mengalokasikan beasiswa dalam bentuk apresisasi untuk siswa-siswa yang berprestasi. Namun banyak masalah yang sering muncul, yaitu kurang terpatnya penyaluran beasiswa terhadap siswa. Metode pengumpulan data yang digunakan untuk memperoleh data-data yang dibutuhkan dalam penelitian ini adalah menggunakan kuesionar dan studi Pustaka. Dari data yang sudah dikumpulkan, mendapat data sebesar 102 record siswa yang sudah mengisi kuesioner tersebut. Pengujian pertama menggunakan metode naÃ¯ve bayes dan memiliki hasil accuracy 58.62%. Kedua menggunakan metode decision tree dan memiliki hasil accuracy 65.52%. Ketiga menggunakan metode random forest dan memiliki hasil accuracy 51.72%. Berdasarkan dari hasil uji yang telah dilakukan menggunakan aplikasi RapidMiner menggunakan 3 metode, hasil penelitian yang didapat menunjukan bahwa metode terbaik dari penelitian prediksi prestasi akademik siswa adalah metode Decision Tree dengan tingkat akurasi 65.52%.
Effects of a water hammer and cavitation on jet formation in a test tube

We investigate the motion of a gas–liquid interface in a test tube induced by a large acceleration via impulsive force. We conduct simple experiments in which the tube partially filled with a liquid falls under gravity and hits a rigid floor. A curved gas–liquid interface inside the tube reverses and eventually forms a so-called focused jet. In our experiments, there arises either vibration of the interface or an increment in the velocity of the liquid jet, accompanied by the onset of cavitation in the liquid column. These phenomena cannot be explained by a considering pressure impulse in a classical potential flow analysis, which does not account for finite speeds of sound or phase changes. Here we model such water-hammer events as a result of the one-dimensional propagation of a pressure wave and its interaction with boundaries through acoustic impedance mismatching. The method of characteristics is applied to describe pressure-wave interactions and the subsequent cavitation. The model proposed is found to be able to capture the time-dependent characteristics of the liquid jet.
Species listing and diversity of myxomycetes from Mt. Makulot and Napayong Island in Taal Lake, Batangas, Philippines

The rich vegetation of volcanic forest offers a unique habitat to explore myxomycetes (slime molds). In this study, the occurrence and diversity of myxomycetes in forest areas of Taal Volcano Crater Rim (Mt. Makulot) and Napayong Island in Taal Lake are reported. Decayed aerial and ground leaf litter, twigs, and woody vines collected from the study areas were used to prepare 1,110 moist-chamber cultures. A total of 35 species belonging to 14 genera were collected. These slime molds were identified as species of Arcyria, Ceratiomyxa, Clastoderma, Collaria, Comatricha, Cribraria, Diachea, Diderma, Didymium, Hemitrichia, Lamproderma, Perichaena, Physarum and Stemonitis. Five species were unique to Mt. Makulot while seven species were exclusively recorded in Napayong Island. Napayong Island also had a higher species diversity as compared to Mt. Makulot. In terms of substrate types, highest species diversity was recorded in ground litter collected in Napayong Island. This study is the first listing of species of myxomycetes in Napayong Island, a small island within a lake within an island.
Energy Theft Detection in Smart Grids via Explainable Attention Maps

Electricity theft is a widespread issue that has a negative impact on both electricity users and utility businesses. Smart meters record energy usage at hourly or daily frequency, creating time series which can help in fraud spotting. This study utilizes a daily consumption dataset given by State Grid Corporation of China to detect electricity fraud with mediocre class imbalance. Most of the existing studies either try to maximize the models detection quality with complex neural network architectures by sacrificing interpretability or try to extract handcrafted meaningful predictors while losing accuracy. In this work the authors proposed a method capable of providing high explainability while still preserving competitive detection quality of 0.896 ROC-AUC and 0.972 MAP@100. The key contribution of this paper is reformulating the original classification problem into time series segmentation problem with the help of attention maps. New labeling is acquired by averaging decision paths from random forest models. The authors also investigate different pitfalls during validation which can lead to overly optimistic estimates of models quality.
An Exact and Grid-free Numerical Scheme for the Hybrid Two Phase Traffic Flow Model Based on the Lighthill-Whitham-Richards Model with Bounded Acceleration

An Exact and Grid-free Numerical Scheme for the Hybrid Two Phase Traffic Flow Model Based on the Lighthill-Whitham-Richards Model with Bounded Acceleration Shanwen Qiu In this article, we propose a new grid-free and exact solution method for computing solutions associated with an hybrid traffic flow model based on the LighthillWhitham-Richards (LWR) partial differential equation. In this hybrid flow model, the vehicles satisfy the LWR equation whenever possible, and have a fixed acceleration otherwise. We first present a grid-free solution method for the LWR equation based on the minimization of component functions. We then show that this solution method can be extended to compute the solutions to the hybrid model by proper modification of the component functions, for any concave fundamental diagram. We derive these functions analytically for the specific case of a triangular fundamental diagram. We also show that the proposed computational method can handle fixed or moving bottlenecks.
Patient-Specific 3D Printed Soft Models for Liver Surgical Planning and Hands-On Training

Background: Pre-surgical simulation-based training with three-dimensional (3D) models has been intensively developed in complex surgeries in recent years. This is also the case in liver surgery, although with fewer reported examples. The simulation-based training with 3D models represents an alternative to current surgical simulation methods based on animal or ex vivo models or virtual reality (VR), showing reported advantages, which makes the development of realistic 3D-printed models an option. This work presents an innovative, low-cost approach for producing patient-specific 3D anatomical models for hands-on simulation and training. Methods: The article reports three paediatric cases presenting complex liver tumours that were transferred to a major paediatric referral centre for treatment: hepatoblastoma, hepatic hamartoma and biliary tract rhabdomyosarcoma. The complete process of the additively manufactured liver tumour simulators is described, and the different steps for the correct development of each case are explained: (1) medical image acquisition; (2) segmentation; (3) 3D printing; (4) quality control/validation; and (5) cost. A digital workflow for liver cancer surgical planning is proposed. Results: Three hepatic surgeries were planned, with 3D simulators built using 3D printing and silicone moulding techniques. The 3D physical models showed highly accurate replications of the actual condition. Additionally, they proved to be more cost-effective in comparison with other models. Conclusions: It is demonstrated that it is possible to manufacture accurate and cost-effective 3D-printed soft surgical planning simulators for treating liver cancer. The 3D models allowed for proper pre-surgical planning and simulation training in the three cases reported, making it a valuable aid for surgeons.
Fuzzy extension of n-persons games based on Choquet integral

Based on Choquet integral,a fuzzy extension method of n-persons game is proposed,which is different from classical multilinear extension and Cornet extension.For n-person games,any coalition can be represented by using its characteristic vectors.By means of Choquet integral,n-person games are extended from classical coalition to fuzzy coalition.Some properties of the fuzzy extension are discussed.The relation between the fuzzy extension and Shapley value is investigated.
Anxiety Prediction Based on Finger Pulse Wave Signal and Convolutional Neural Network

One of the key elements of Traditional Chinese Medicine (TCM) is the pulse wave diagnosis technique, and the pulse wave signal contains a variety of physiological information. A deep learning model was used in this study to train and predict 500 pieces of pulse wave data from adult males during the novel coronavirus epidemic, and it was able to do so with a prediction accuracy of over 70%.
A Simulation Study of n-ZnO/Perovskite/p-Cu2SnS3 Based Self-Powered Photodetector: Design and optimisation

ABSTRACT Perovskite has been widely used in the field of optoelectronics owing to its superb optoelectronic properties. The simplest fabrication along with low-temperature handling of perovskite-based planner structures (p-i-n or n-i-p) has drawn their potential impact in organic–inorganic lead halide optoelectronic devices. The poor conductivity, stability, and high processing cost of absorber materials hinder the optical performance of the device. The sandwiching of the perovskite as absorber materials between two inorganic materials working as electron transport layer (ETL) and hole transport layer (HTL) may be a possible solution. An active absorber perovskite (CH3NH3PbI3) assisted by two n-ZnO and p-CTS materials working as an ETL and HTL, respectively, has been used to maximize the overall performance of the proposed device. The resultant optimized device shows the maximum responsivity of ∼0.35 (A/W) for a broad visible spectrum (300–900 nm), while the EQE (%) reported in the range of 25–80%.
Mechanical model and numerical simulation of the formation of karst collapse columns in the Huainan coalfield of Northern China

Karst collapse columns (KCCs) are channels where groundwater and gas gather, and they pose a great threat to mining safety. In this study, a mechanical model and criterion for the roof collapse of KCCs were established, and simulations were performed to analyze the formation mechanism of KCCs in the Huainan coalfield of Northern China. The results showed that the roof collapse and upward development of KCCs were facilitated by increasing the cave radius of the KCC basement and decreasing the groundwater pressure, single-layer thickness of the roof strata, lateral pressure coefficient of the rock mass, and cohesion and internal friction angle between fractures. The KCC formation process in the Huainan coalfield could be divided into four stages: (I) early collapse, (II) middle-early rapid collapse, (III) middle-late slow collapse, and (IV) late filling compaction. The simulation results were generally consistent with actual KCCs observed in the Huainan coalfield, which verified the theoretical analysis. The results of this study provide an important reference for the formation mechanism and evolution of KCCs in Northern China.
MODELS FOR $pi$$sup +$--$sup 16$O SCATTERING AT 270 MeV.

Predictions of the Kisslinger and "local" optical models are compared to ${\ensuremath{\pi}}^{+}\ensuremath{-}^{16}\mathrm{O}$ elastic differential cross sections at 270-MeV lab kinetic energy. With no adjusted parameters, the local potential gives a remarkably good fit to the data.
Does peacekeeping by civilians work? Reducing armed violence without armed force

Abstract Since the 1990s, United Nations (UN) peacekeepers have been engaged in multidimensional activities in conflict-affected countries. The existing literature, however, focuses predominantly on the effectiveness of military and police peacekeepers involving the threat of force, and does not shed light on the effectiveness of civilian peacekeepers despite the latter's crucial role in rebuilding local livelihoods and restoring state institutions. Civilian participation in peacekeeping increases both the benefits of peaceful life and the costs of combat. Further, civilian activities, by strengthening the rule of law and political accountability mechanism, contribute to encouraging both the rebels and government to disengage from further violence. Using the original dataset of financial resources for UN peacekeeping operations in the world, from 1988 to 2019, I test hypotheses regarding the impact of civilian expenditures on battle-related deaths. Regression analysis shows that spending on the civilian component in UN peacekeeping reduces battle-related deaths on the government side inflicted by insurgents.
Wind Turbines Analysis and Analytics of Power Generation by using Long Short Term Memory

In this paper, the study of the behavior of wind turbines and its power generation in Germany that an important source for renewable energy is investigated. This work develops a deep learning recurrent neural model that depends on time series modeling to predict the power generation of wind turbines (WT) in every ten mins in a daily basis, and seasonal behavior. The proposed model uses previous historical power data from the turbines and the dependency of short-term points and long-term behavior that common in time series with its probabilistic behavior. However, WT power generation depends on wind speed, torque, gearbox state, temperature that are highly correlated to power generated and WT state in generation, but time series modeling uses the historical previous power generated only to forecast the future behavior that behaves in a pattern similar to the previous corresponding time frame. The comprehensive analysis is implemented to evaluate the suggested model with previous data and then forecast the power generated in the last months of the year.