Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on endogenous internet public opinion dissemination in Chinese universities based on SNIDR model

During an emergency, the negative Internet public opinion in colleges and universities, especially the negative endogenous public opinion, will have a serious impact on the reputation of colleges and universities. It is of great significance to find out the negative influencing factors of endogenous public opinion and explore the mechanism of public opinion dissemination for resolving the crisis of public opinion in universities. The existing research does not distinguish the endogenous Internet public opinion in colleges and universities from the general Internet public opinion in colleges and universities, and the SIR model adopted fails to fully reflect the difference between students and other dissemination subjects of endogenous public opinion in campus. In addition, various research methods and models currently used focus on the static expression of dissemination results, and the explanation of results is insufficient. The reason is that they do not well express the dynamic interaction mechanism between influencing factors and the dynamic conversion rate between roles. In this study, based on the improved infectious disease model and system dynamics theory, AnyLogic software is used to simulate the improved SNIDR model of infectious disease, to analyze the sensitivity of school supervision, school intervention, school response time and information transparency and to study the dynamic conversion rate between different roles. The SNIDR model effectively simulates the process of endogenous public opinion dissemination in colleges and universities after emergencies. The results show that, what has the greatest impact on the dissemination of public opinion is the school’s supervision and intervention efforts, which can suppress the dissemination from the source. Information transparency is an auxiliary variable and cannot function independently. During the dissemination period, the timelier the school responds, the faster the spreaders will drop to zero, and the better it will be to control the secondary dissemination of public opinion.
Replacement, Reduction, and Refinement of Animal Experiments in Anticancer Drug Development: The Contribution of 3D In Vitro Cancer Models in the Drug Efficacy Assessment

In the last decades three-dimensional (3D) in vitro cancer models have been proposed as a bridge between bidimensional (2D) cell cultures and in vivo animal models, the gold standards in the preclinical assessment of anticancer drug efficacy. 3D in vitro cancer models can be generated through a multitude of techniques, from both immortalized cancer cell lines and primary patient-derived tumor tissue. Among them, spheroids and organoids represent the most versatile and promising models, as they faithfully recapitulate the complexity and heterogeneity of human cancers. Although their recent applications include drug screening programs and personalized medicine, 3D in vitro cancer models have not yet been established as preclinical tools for studying anticancer drug efficacy and supporting preclinical-to-clinical translation, which remains mainly based on animal experimentation. In this review, we describe the state-of-the-art of 3D in vitro cancer models for the efficacy evaluation of anticancer agents, focusing on their potential contribution to replace, reduce and refine animal experimentations, highlighting their strength and weakness, and discussing possible perspectives to overcome current challenges.
On the Number of Parity Sets in a Graph

The graphs considered in this paper are finite and have no loops or multiple edges. If G is such a graph, we denote its vertex set by VG and its edge set by EG. If X and Y are disjoint subsets of VG, we define δ (X, Y) to be the set of edges of G that join a vertex in X to one in Y.
High-speed digital color fringe projection technique for three-dimensional facial measurements

Digital fringe projection techniques have been widely studied in industrial applications because of the advantages of high accuracy, fast acquisition and non-contact operation. In this study, a single-shot high-speed digital color fringe projection technique is proposed to measure three-dimensional (3-D) facial features. The light source used in the measurement system is structured light with color fringe patterns. A projector with digital light processing is used as light source to project color structured light onto face. The distorted fringe pattern image is captured by the 3-CCD color camera and encoded into red, green and blue channels. The phase-shifting algorithm and quality guided path unwrapping algorithm are used to calculate absolute phase map. The detecting angle of the color camera is adjusted by using a motorized stage. Finally, a complete 3-D facial feature is obtained by our technique. We have successfully achieved simultaneous 3-D phase acquisition, reconstruction and exhibition at a speed of 0.5 s. The experimental results may provide a novel, high accuracy and real-time 3-D shape measurement for facial recognition system.
Sub-micron channels fabricated by direct electron beam lithography on SU8 for optofluidic bacterial analysis

Microfluidic structures in poly(dimethylsiloxane) (PDMS) are usually fabricated by optically patterning a resist and subsequently transferring this pattern to PDMS. Such microsystems suffer from reduced resolution, which in turn inhibit the manipulation of sub-micron scale entities such as bacteria, as well as their optical properties (e.g. long period gratings and radiation losses). In this paper we discuss how electron beam lithography (EBL) can be employed in prototyping SU8 moulds and nanostructures for poly(dimethylsiloxane) (PDMS) based microfluidics and optofluidics. In comparison to conventional optical methods, direct patterning of SU8 with an electron beam enabled both sub- and few micron scale structures with reduced complexity and duration. We will also discuss how to synthesize optofluidic circuits with this method and discuss our preliminary results on how such sub-micron scale structures can be employed in the optofluidic analysis of bacteria.
Successful Treatment of Infertility in a Patient with Probable 17 Hydroxylase Deficiency and Particularities of Association with Adrenal Autoimmunity—A Case Report and Review of the Literature

Congenital adrenal hyperplasia (CAH) due to 17-hydroxylase deficiency (17OHD) is a rare disease accounting for less than 1% of cases of CAH. In female patients, fertility is severely affected mainly due to constantly increased progesterone affecting endometrium receptivity and implantation. The optimal treatment for infertility in these patients is not clearly established, with only a few recent case reports of successful pregnancies available in the literature. Hereby, we present the case of an infertile female patient with 17OHD who obtained pregnancy through an in vitro fertilization (IVF) freeze-all strategy and particularities of association with adrenal autoimmunity. A 32-year-old infertile female patient was referred for infertility evaluation and treatment. She had normal sex development and menstrual history with oligomenorrhea alternating with normal menstrual cycles. During the evaluation, a reduced ovarian reserve and obstruction of the left fallopian tube were identified, and IVF treatment was recommended. During a controlled ovarian stimulation for IVF, increased values of serum progesterone were observed; thus, all the embryos were frozen and additional tests were performed. Increased values of 17-hydroxyprogesteron, 11-deoxycorticosteron, and adrenocorticotropic hormones in association with low basal and stimulated serum cortisol, testosterone, androstenedione, and dehydroepiandrosterone sulfate were found, supporting the presence of 17OHD. She started treatment with oral hydrocortisone given at 20 mg/day but, because follicular phase serum progesterone remained high, hydrocortisone was replaced by an oral dexamethasone treatment of 0.5 mg/day, followed by the normalization of serum progesterone. A thawed blastocyst was transferred after preparation with oral estradiol at 6 mg/day and intravaginal progesterone at 600 mg/day under continuous suppression of endogenous progesterone production with a gonadotropin-releasing hormone agonist and oral dexamethasone. The patient became pregnant and delivered two healthy girls at term. One year after delivery, the presence of 21-hydroxylase antibodies was detected, which might explain the particularities of adrenal steroids in our patient. Our case report demonstrates that a patient with 17OHD can become pregnant through IVF and the transfer of thawed embryos in a subsequent cycle under continuous suppression of adrenal and ovarian progesterone production.
Velocity rays for heterogeneous anisotropic media: Theory and implementation

The surface of equal two-way time referred to as the isochron is a fundamental concept in seismic imaging. The shape of an isochron depends on the source and receiver locations, on the wave type, and on the parameters constituting the seismic velocity model. A perturbation of a parameter of the velocity model forces the isochron points to move along trajectories called velocity rays, with the selected model parameter as the variable along the rays. Based on earlier work describing first-order approximations to velocity rays, I develop a general theory for velocity rays valid for 3D heterogeneous and anisotropic velocity models. By this theory, velocity rays can be obtained in a way similar to the way conventional rays are computed by numeric integration of a system of ordinary differential equations (ODEs). The process is organized with ODE solvers on two levels, where the upper level is model independent. The lower level includes conventional one-way kinematic and dynamic tracing of source and receiver rays, as well as calculation of ray perturbation quantities. Accurate velocity rays are expected to be useful for perturbation of reflectors mapped from the time domain to the depth domain, for remigration of seismic images in the depth domain, and for velocity model updating.
Postpartum Depression and Health: Role of Perceived Social Support among Pakistani Women

Postpartum depression (PPD) can predispose to physical and mental health problems in Pakistani women. However, PPD is associated with health and perceived social support, yet their causal relationship is unclear. Therefore, this study intended to evaluate the association of PPD with insomnia, mental health, and physical health. The convenience sampling technique was used to collect data from 320 (52.8%) young and middle-aged postpartum women, at the outpatient departments of obstetrics and gynecology of the Government Maula Bakhsh Hospital, District Head Quarter in Sargodha, Pakistan. The Edinburgh Postnatal Depression Scale, Pittsburgh Sleep Quality Index, Warwick–Edinburgh Mental Well-being Scale, patient health questionnaire, and Multidimensional Scale of Perceived Social Support were used to measure study variables. The results revealed a significant positive relationship between PPD and physical health (r = 0.45, p = 0.001), negative relationships with insomnia (r = −0.24, p < 0.001), and perceived social support (r = −0.38, p = 0.001). Results further confirmed that perceived social support played a moderating role (β = 0.97, p = 0.01) in the relationship between PPD and mental health among Pakistani women. This study concluded that perceived social support has an important role in PPD and the health of Pakistani women. The study also concluded that poor health is a risk indicator for the identification of aid in the early stages of postpartum among Pakistani women.
Stacking order and driving forces in the layered charge density wave phase of 1T-MX2 (M = Nb, Ta and X = S, Se)

The group-V transition metal dichalcogenides (TMD) have attracted a lot of research due to their unique structures and rich physical properties. In these materials, charge density waves (CDW) are still the subject worthy of in-depth research despite being a popular issue. Based on first principles, the stacking effect of the T- MX2 (M = Nb, Ta and X = S, Se) CDW phase are comprehensively explored, with the interplay of correlation effect and magnetic order. Without correlation effect, T- MX2 with one specific stacking order (AA_AC_AA) is most structurally stable and leads to a natural band insulator due to interlayer dimerization. In contrast, same materials with the other stacking orders (AA_AB_AA, AA, AB, AC) are metallic phase. In the presence of correlation effect, whether the systems are insulators or metal highly depends on the magnetic order. AA_AC_AA stacking T- MX2 with antiferromagnetic order end up with band insulator. T- MX2 with AA, AB, AC stacking are metal even in the presence of correlation effect, but with magnetic order, they become Mott insulator. The complication is that AA_AB_AA stacking is located at the intersection of the band insulator and Mott insulator. From this article, we can see T-MX2 with different stacking structure with/without correlation effect and magnetic order show different phases. We outline a rich landscape and systematically explain the causes of the insulating characteristic of the CDW phase and emphasizes the critical role of correlation effect and magnetic order, extending the underlying mechanism of metal-insulation transitions that previously relied only on Mott localization as a driving force.
Localization lengths over metal to band insulator transitions

Density functional and quantum Monte Carlo methods are used to examine the behaviour of the many-electron localization length near band insulator-to-metal transitions in various one- and two-dimensional model systems. The many-electron localization length is infinite in metals and finite in insulators, and is normally assumed to diverge as an insulator-to-metal transition is approached from the insulating side. Our results show that this is not the case: the band insulator-to-metal transition is normally first order and not associated with a diverging length scale. We also identify examples where the localization length diverges but the system is insulating on both sides of the divergence. The usefulness of the localization length as an indicator of the approach of an insulator-to-metal transition is therefore limited. A comparison of our quantum Monte Carlo and density functional results allows us to draw some general conclusions about the effect of correlation on localization.
A Comparative Analysis of Biodegradation and Bioconversion of Lentinula edodes and Other Exotic Mushrooms

Mushrooms are capable of bioconverting organic residues into food. Understanding the relationship between high-quality yields and substrate biomass from these residues is critical for mushroom farms when choosing new strains. The objective of this exploratory study was, therefore, to analyze whether exotic mushrooms, namely, Pleurotus eryngii, Flammulina velutipes, and Agrocybe aegerita, could biologically convert the substrate into edible mushrooms as effectively as Lentinula edodes (baseline). Five experiments were carried out. Biological efficiency, biodegradability coefficient, mass balance and chemical characterization of the substrate were evaluated. Strategically hydrating the sawdust enabled L. edodes to achieve the greatest biodegradability and biological efficiency of 0.5 and 94.2 kg dt−1, respectively. The values for L. edodes on wheat straw without hydration were 0.2 and 68.8 kg dt−1, respectively. From 1000 kg of fresh substrate, P. eryngii produced 150.1 kg of edible mushrooms, making it technically competitive with L. edodes on wheat straw (195.9 kg). Hence, P. eryngii was the most reliable option for scaling among the exotic mushrooms. The analytical insights from our study provide further knowledge to advance the field’s prominence in high-throughput mushroom-producing systems, particularly for exotic mushrooms.
Effect of boric acid in powder mixed EDM of Ti-6al-4V ELI

ABSTRACT Ti-6Al-4 V ELI is an advanced titanium alloy used in different sectors. Being a hard-to-machine material, it is crucial to explore the machinability of Ti-6Al-4 V ELI. Boric acid powder mixed with deionized water is utilized as a dielectric to machine Ti-6Al-4 V ELI in electrical discharge machining (EDM). The effect of powder concentration (PC), current, and pulse-on time on material removal rate (MRR), tool wear rate (TWR), surface roughness (SR), and specific energy consumption (SEC) is evaluated. X-ray diffraction (XRD) analysis revealed the formation of TiO2, TiB, and Al2O3-like hard compounds over the surface. Scanning electron microscope (SEM) test indicates that there are more craters and globules on the surface machined in 5 g/l PC compared to that of 15 g/l PC. The overall evaluation criteria are designed to maximize the MRR and minimize the TWR, SR, and SEC by optimizing the variable parameters.
Structural characterization and electron-energy-loss spectroscopic study of pulsed laser deposited LiNbO3 films on a-sapphire

Highly c- and a-oriented LiNbO3 films were deposited on a-sapphire substrates by pulsed laser deposition. The film microstructure and crystal orientation were studied by transmission electron microscopy, and the mechanism forming the different film orientations was interpreted in terms of the adatom energy and oxygen pressures. The electron-energy-loss functions derived from the electron-energy-loss spectra exhibit characteristic energy-loss peaks at about 7.0, 11.0, and 14.0eV. These peaks correspond to electron transitions from the maximum density of the states in the valence band of O 2p to the split conduction band. The dielectric functions of the LiNbO3 films were also derived from the energy-loss function.
Improved HHT based on MM-EMD and its application

The traditional HHT(Hilbert-Huang transformation) method supposes that a signal is composed of instinct mode functions(IMFs) and an ordinary trend term.Considering this limitation and the characteristics of hydraulic pressure signals,an improved HHT method based on MM-EMD(mathematical morphology and empirical mode decomposition) was proposed and employed to analyze pressure signals.The basic idea of this method was that if a signal contains a component not beloging to instinct mode functions and ordinary trend term,the morphological filter is used to separate this component from the original signal,and the rest signal is analyzed with EMD and HSA(Hilbert spectral analysis). The results of simulation and the measured signals showed that compared with the traditional method,the new one can have a better analysis effect.
SPR Biosensor Based High-Throughput Screening of Low Molecular Weight Compounds for Interaction with Candida krusei CYP51

The opportunistic fungus Candida krusei is the causative agent of nosocomial infections characterized by high mortality and development of resistance to drugs of the azole class. Therefore, develjoment of non-azole antifungal agents against resistant fungal strains is extremly important. Lanosterol 14-alpha demethylase (CYP51) is a well-known antifungal target. The optical SPR biosensor is a universal tool for screening studies in search of new drug prototypes. This paper presents the methodological aspects of high-hroughput SPR based screening of a library of low molecular weight compounds of natural origin for their interaction with C. krusei CYP51. It has been shown that when performing high-throughput screening, a researcher should pay special attention to the degree of a sensorgram curvature in the association phase. The described approaches to the analysis of high throughput screening data can be useful for researchers working with SPR biosensors from various manufacturers.
An Image Registration Method Combing Feature Constraint with Multilevel Strategy

A novel method combing feature constraint with multilevel strategy to improve simultaneously the registration accuracy and speed is proposed for non-parametric image registrations. To images between which the local difference is large, integrating feature constraint constructed with local structure information of images into objective function of image registration improves the registration accuracy. When applying feature constraint under multilevel strategy, parameter searching is prevented from entrapped into local extremum by using the optimization result on coarser levels as the starting points on finer levels; meanwhile traditional optimization methods without demanding intelligent optimization algorithms which consume more time can find the accurate registration parameter on finer levels, so registration speed is improved. Experimental results indicate that this method can finish fast and accurate registration for images between which there exists large local difference.
Performance enhancement for GPS positioning using constrained Kalman filtering

Over the past decades Kalman filtering (KF) algorithms have been extensively investigated and applied in the area of kinematic positioning. In the application of KF in kinematic precise point positioning (PPP), it is often the case where some known functional or theoretical relations exist among the unknown state parameters, which can be and should be made use of to enhance the performance of kinematic PPP, especially in an urban and forest environment. The central task of this paper is to effectively blend the commonly used GNSS data and internal/external additional constrained information to generate an optimal PPP solution. This paper first investigates the basic algorithm of constrained Kalman filtering. Then two types of PPP model with speed constraints and trajectory constraints, respectively, are proposed. Further validation tests based on a variety of situations show that the positioning performances (positioning accuracy, reliability and continuity) from the constrained Kalman filter are significantly superior to those from the conventional Kalman filter, particularly under extremely poor observation conditions.
Power‐Law‐Based Synthetic Minority Oversampling Technique on Imbalanced Serum Surface‐Enhanced Raman Spectroscopy Data for Cancer Screening

Surface‐enhanced Raman spectroscopy (SERS) has shown highly promising for existing cancer screening. However, previous “proof‐of‐concept” studies ignored the natural imbalance of cancer types in the population, leading the model to be biased toward learning more features in majority class during the learning process at the expense of ignoring minority class. Herein, a power‐law‐based synthetic minority oversampling technique (PL‐SMOTE) method is proposed to guide the resampling of multiclass serum SERS data by analyzing the long‐tailed (power‐law) distribution of cancer prevalence in the population. The proposed PL‐SMOTE method balances the number of minorities to resample and the number of overlaps between classes by introducing modulating factor. Modeling on resampled datasets synthesized by PL‐SMOTE verifies the effectiveness of proposed PL‐SMOTE method. After further fine‐tuning, the parameters of the deep neural network model and PL‐SMOTE method, an optimal cancer screening model with an optimal macroaveraged Recall score of 97.24% and an optimal macroaveraged F2‐Score of 97.38% is obtained. A new method for multiclass imbalanced resampling is provided, which has significant improvement on model performance in terms of SERS cancer screening. The method also inspires in other multiclass imbalanced scenario, such as biological medicine, abnormal detection, and disaster prediction.