Miracle-dz/UniFAR-FTUs huggingface dataset:
Brain Activities Show There Is Nothing Like a Real Friend in Contrast to Influencers and Other Celebrities

Especially for young people, influencers and other celebrities followed on social media evoke affective closeness that in their young minds seems real even though it is fake. Such fake friendships are potentially problematic because of their felt reality on the consumer side while lacking any inversely felt true closeness. The question arises if the unilateral friendship of a social media user is equal or at least similar to real reciprocal friendship. Instead of asking social media users for explicit responses (conscious deliberation), the present exploratory study aimed to answer this question with the help of brain imaging technology. Thirty young participants were first invited to provide individual lists including (i) twenty names of their most followed and loved influencers or other celebrities (fake friend names), (ii) twenty names of loved real friends and relatives (real friend names) as well as (iii) twenty names they do not feel any closeness to (no friend names). They then came to the Freud CanBeLab (Cognitive and Affective Neuroscience and Behavior Lab) where they were shown their selected names in a random sequence (two rounds), while their brain activities were recorded via electroencephalography (EEG) and later calculated into event-related potentials (ERPs). We found short (ca. 100 ms) left frontal brain activity starting at around 250 ms post-stimulus to process real friend and no friend names similarly, while both ERPs differed from those elicited by fake friend names. This is followed by a longer effect (ca. 400 ms), where left and right frontal and temporoparietal ERPs also differed between fake and real friend names, but at this later processing stage, no friend names elicited similar brain activities to fake friend names in those regions. In general, real friend names elicited the most negative going brain potentials (interpreted as highest brain activation levels). These exploratory findings represent objective empirical evidence that the human brain clearly distinguishes between influencers or other celebrities and close people out of real life even though subjective feelings of closeness and trust can be similar. In summary, brain imaging shows there is nothing like a real friend. The findings of this study might be seen as a starting point for future studies using ERPs to investigate social media impact and topics such as fake friendship.
Dynamic and Static Nature of XH-∗-π and YX-∗-π (X = F, Cl, Br, and I; Y = X and F) in the Distorted π-System of Corannulene Elucidated with QTAIM Dual Functional Analysis

The dynamic and static nature of the XH-∗-π and YX-∗-π (X = F, Cl, Br, and I; Y = X and F) interactions in the distorted π-system of corannulene (π(C20H10)) is elucidated with a QTAIM dual functional analysis (QTAIM-DFA), where asterisks emphasize the presence of bond critical points (BCPs) on the interactions. The static and dynamic nature originates from the data of the fully optimized and perturbed structures, respectively, in QTAIM-DFA. On the convex side, H in F–H-∗-π(C20H10) and each X in Y–X-∗-π(C20H10) join to C of the central five-membered ring in π(C20H10) through a bond path (BP), while each H in X–H-∗-π(C20H10) does so to the midpoint of C=C in the central five-membered ring for X = Cl, Br, or I. On the concave side, each X in F–X-∗-π(C20H10) also joins to C of the central five-membered ring with a BP for X = H, Cl, Br, and I; however, the interactions in other adducts are more complex than those on the convex side. Both H and X in X–H-∗-π(C20H10) (X = Cl and Br) and both Fs in F–F-∗-π(C20H10) connect to the three C atoms in each central five-membered ring (with three BPs). Two, three, and five BPs were detected for the Cl–Cl, I–H, Br–Br, and I–I adducts, where some BPs do not stay on the central five-membered ring in π(C20H10). The interactions are predicted to have a vdW to CT-MC nature. The interactions on the concave side seem weaker than those on the convex side for X–H-∗-π(C20H10), whereas the inverse trend is observed for Y–X-∗-π(C20H10) as a whole. The nature of the interactions in the π(C20H10) adducts of the convex and concave sides is examined in more detail, employing the adducts with X–H and F–X placed on their molecular axis together with the π(C24H12) and π(C6H6) adducts.
Stock Prices Prediction Using Long Short Term Memory

In this study, we propose to use a Long Short Term Memory (LSTM) to forecast stock price and subsequently investigate the model’s defenses against epochs and batch size. Stock market is a trading and investing alternative. Predicting the stock price for the future is a very sensitive process. Knowing the future price, or the unborn price, is useful for investors and dealers so they can enter and exit the market at the appropriate time and price. New algorithms and machine learning fared reasonably well in this, despite the fact that there are numerous ways to estimate unborn or future prices. In this investigation, a new stock price forecasting framework and exercising model are provided. i.e. model for long-short-term memory (LSTM). The Root Mean Square Error (RMSE) for LSTM was assessed by altering the number of iterations, architectures, and different units used in the unseen layers in order to generate a more a reliable model that can be applied read future or unborn stock values. The computation results show that our proposed strategy can accurately predict future market trends by applying the LSTM with the right hyperactive parameter adjustment. It can be anticipated that this model can be used in real time stock market prediction.
Heat Conduction with Memory: a singular kernel problem

The existence and uniqueness of solution to an integro-differential problem arising in heat conduction with memory is here considered. Specifically, a singular kernel problem is analyzed in the case of a multi-dimensional rigid heat conductor. The choice to investigate a singular kernel material is suggested by applications to model a wider variety of materials and, in particular, new materials whose heat flux relaxation function may be superiorly unbounded at the initial time $t=0$. The present study represents a generalization to higher dimensions of a previous one concerning a $1$-dimensional problem in the framework of linear viscoelasticity with memory. Specifically, an existence theorem is here proved when initial homogeneous data are assumed. Indeed, the choice of homogeneous data is needed to obtain the a priori estimate in Section 2 on which the subsequent results, are based.
Online motion planning based on swept volume search with replanning using sequential quadratic programming

This paper describes a method for obtaining a mobile manipulator's motion sequence by indicating a goal-hand pose. The proposed method entails recording various robot motions as a large number of motion sequences and associated swept volumes (SVs) and then selecting the most appropriate SV for the current situation. In addition, the motion sequences can be altered while the robot is in motion, and the transition motion is generated using sequential quadratic programming, enabling the robot to avoid collisions with obstacles found after it has begun to move. The proposed method's performance is verified by simulation to confirm the appropriate amount of data and the method's superiority. GRAPHICAL ABSTRACT
On the Number of Self-Incompatibility Alleles Maintained in Equilibrium by a Given Mutation Rate in a Population of Given Size: A Reexamination

Some twenty years ago, Emerson [1, 2] found an extraordinary number of self-incompatibility alleles (at least 37, later stated by Lewis [7] to be 45) in Oenothera organensis, a species believed to be restricted to a few relatively moist canyons in the Organ Mountains of New Mexico within an area of 33 square miles above the 6000 foot line. On careful search, Emerson found 154 individuals in the four supposedly most favorable canyons. He states: "On the basis of this preliminary survey, it is estimated that the entire population of this species consists of less than one thousand and very likely less than five hundred".
The Economic Evaluation of Mastitis Control Strategies in Holstein-Friesian Dairy Herds

Simple Summary In order to capture the complexity and dynamics of bovine mastitis, which has multiple effects, such as milk losses, increased risk of culling, or a higher likelihood of reproductive failure, a simulation model was developed. The economic evaluation of the mastitis control was performed considering different interventions combining a basic control plan with either segregation or culling of chronically infected cows. Changes in transmission probability, milk price, and strategies efficacy were evaluated. Several economic parameters in the model could be adjusted to represent farm-specific situations. This is a flexible tool that may support the decision-making of producers and veterinarians. Abstract The economic evaluation of mastitis control is challenging. The objective of this study was to perform the economic evaluation of mastitis control, under different intervention scenarios, quantifying the total cost of mastitis caused by S. aureus in Holstein cows in Argentina. A model was set for a dairy herd of Holstein cows endemically infected with S. aureus. A basic mastitis control plan including proper milking procedures, milking machine test, dry cow therapy, and treatment for clinical mastitis, was compared against other more complex and costly interventions, such as segregation and culling of chronically infected cows. Sensitivity analysis was performed by modifying the intramammary infection transition probabilities, economic parameters, and efficacy of treatment strategies. The basic mastitis control plan showed a median total cost of USD88.6/cow per year, which was close to the infected cows culling scenarios outputs. However, the segregation scenario was the most efficient, in which the total cost was reduced by about 50%. Such cost was more sensitive to probabilities and efficacy than the economic parameters. The model is flexible and can be customized by producers and veterinarians according to different control and herd settings.
Far-field and near-field optical trapping

Optical trapping techniques have become an important and irreplaceable tool in many research disciplines for reaching non-invasively into the microscopic world and to manipulate, cut, assemble and transform micro-objects with nanometer precision and sub-micrometer resolution. Further advances in optical trapping techniques promise to bridge the gap and bring together the macroscopic world and experimental techniques and applications of microsystems in areas of physics, chemistry and biology. In order to understand the optical trapping process and to improve and tailor experimental techniques and applications in a variety of scientific disciplines, an accurate knowledge of trapping forces exerted on particles and their dependency on environmental and morphological factors is of crucial importance. Furthermore, the recent trend in novel laser trapping experiments sees the use of complex laser beams in trapping arrangements for achieving more controllable laser trapping techniques. Focusing of such beams with a high numerical aperture (NA) objective required for efficient trapping leads to a complicated amplitude, phase and polarisation distributions of an electromagnetic field in the focal region. Current optical trapping models based on ray optics theory and the Gaussian beam approximation are inadequate to deal with such a focal complexity. Novel applications of the laser trapping such as the particle-trapped
Solving the time capacitated arc routing problem under fuzzy and stochastic travel and service times

Stochastic, as well as fuzzy uncertainty, can be found in most real‐world systems. Considering both types of uncertainties simultaneously makes optimization problems incredibly challenging. In this paper we propose a fuzzy simheuristic to solve the Time Capacitated Arc Routing Problem (TCARP) when the nature of the travel time can either be deterministic, stochastic or fuzzy. The main goal is to find a solution (vehicle routes) that minimizes the total time spent in servicing the required arcs. However, due to uncertainty, other characteristics of the solution are also considered. In particular, we illustrate how reliability concepts can enrich the probabilistic information given to decision‐makers. In order to solve the aforementioned optimization problem, we extend the concept of simheuristic framework so it can also include fuzzy elements. Hence, both stochastic and fuzzy uncertainty are simultaneously incorporated into the CARP. In order to test our approach, classical CARP instances have been adapted and extended so that customers' demands become either stochastic or fuzzy. The experimental results show the effectiveness of the proposed approach when compared with more traditional ones. In particular, our fuzzy simheuristic is capable of generating new best‐known solutions for the stochastic versions of some instances belonging to the tegl, tcarp, val, and rural benchmarks.
Printed and Room Temperature Processed Nanoparticulate VO2 Thin Films Toward Memristive Device Applications

Vanadium dioxide (VO2) has received tremendous research interest in recent years for its versatile electronic application possibilities based on its reversible metal–insulator transition (MIT) behavior, which can be triggered by a large set of stimuli, such as current, electric field, or light. VO2 undergoes a phase transition from a semi-insulating monoclinic to metallic rutile phase at a low critical temperature of 68 °C, which is very close to room temperature, and compatible with any inexpensive flexible substrate. However, due to the existence of various vanadium oxide polymorphs, the synthesis of the pure monoclinic VO2 (M) phase is a challenge. In fact, the difficulty level increases further when it is to be solution-processed. However, synthesis protocol for phase-pure VO2 (M) following wet chemical routes is essential to obtain high throughput, cost-efficient, and substrate-independent fabrication routine for the large volume of devices. In this regard, in this study, we report a solution-based synthesis of ultrasmall VO2 (M) nanoparticles that are phase-pure and the small nanoparticles may easily be used to formulate inkjet printable VO2 nanoparticulate. The printed VO2 (M) films have been found to be homogeneous, crack-free and the memristor device thus fabricated has demonstrated temperature-dependent phase transition and a resistance change of more than three orders of magnitude around 68 °C; on the other hand, retention of the metallic and insulating state has also been demonstrated for 180 min.
Review On Design and Analysis of 3D Printed Parts Developed Through Fusion of Composite Materials

- This paper presents the development of a new composite material for use in injection molding machine. The material consists of iron powder filled in and to find out which type of composite material is best and to conduct tensile testing and fluctuation testing from a scientific point of view and to make a specimen and test it according to which type of composite material will give good 3D printing and find out the result and give a conclusion. FDM is one of the most widely used 3D printing technologies because of its reliability and simple process. FDM requires only a heating process to extrude the materials. Furthermore, FDM 3D printers have competitive prices when compared to other 3D printing machines. This is the primary reason why the FDM 3D printer is the most commercialized in the additive manufacturing industry today. Composites are becoming increasingly popular among business professionals as a way to provide high-quality materials for desired products, particularly in the aerospace and automotive industries, medical industries. Users can print lighter, stronger – sometimes even stronger than some metals – objects. The combination of two substances with different physical and chemical properties is called a compound. The most common materials for FDM 3D printing are Metal/Nylon, Metal/ABS and their various fusions. FDM printers can also print with other special materials with properties such as higher temperature, impact resistance, resistance and stiffness. In addition to commonly used materials, there are new and more effective materials that can be used in many combinations.
Estimation of Non-Stationary Noise Based on Robust Statistics in Speech Enhancement

We propose a novel method for noise power spectrum estimation in speech enhancement. This method called extended-DATE (E-DATE) extends the d -dimensional amplitude trimmed estimator (DATE), originally introduced for additive white gaussian noise estimation in [1], to the more challenging scenario of non-stationary noise. The key idea is that, in each frequency bin and within a sufficiently short time period, the noise instantaneous power spectrum can be considered as approximately constant and estimated as the variance of a complex gaussian noise process possibly observed in the presence of the signal of interest. The proposed method relies on the fact that the Short-Time Fourier Transform (STFT) of noisy speech signals is sparse in the sense that transformed speech signals can be represented by a relatively small number of coefficients with large amplitudes in the time-frequency domain. The E-DATE estimator is robust in that it does not require prior information about the signal probability distribution except for the weak-sparseness property. In comparison to other state-of-the-art methods, the E-DATE is found to require the smallest number of parameters (only two). The performance of the proposed estimator has been evaluated in combination with noise reduction and compared to alternative methods. This evaluation involves objective as well as pseudo-subjective criteria
Role of Estrogen Receptor β, G-Protein Coupled Estrogen Receptor and Estrogen-Related Receptors in Endometrial and Ovarian Cancer

Simple Summary Despite new therapeutic approaches, ovarian cancer is still the most lethal gynecological cancer that is mainly diagnosed in its advanced stages. Contrarily, endometrial cancer is often detected in its early stages. However, in the cases of recurrence or advanced disease, treatment options are still limited. Both the ovary and endometrium are affected by estrogens and their receptors. The well-known estrogen receptor α (ERα) mediates estrogen effects such as the activation of cell proliferation. In contrast, the functions of the later discovered ERs, ERβ and GPER1, and of estrogen-related receptors (ERRs), are less understood. Increasing evidence suggests them to be involved in tumor development, progression, and metastasis. This article provides a summary and update of the current findings on the role of these receptors in ovarian and endometrial cancer to show at which points further research is reasonable and might change the future of their treatment. Abstract Ovarian and endometrial cancers are affected by estrogens and their receptors. It has been long known that in different types of cancers, estrogens activate tumor cell proliferation via estrogen receptor α (ERα). In contrast, the role of ERs discovered later, including ERβ and G-protein-coupled ER (GPER1), in cancer is less well understood, but the current state of knowledge indicates them to have a considerable impact on both cancer development and progression. Moreover, estrogen related receptors (ERRs) have been reported to affect pathobiology of many tumor types. This article provides a summary and update of the current findings on the role of ERβ, GPER1, and ERRs in ovarian and endometrial cancer. For this purpose, original research articles on the role of ERβ, GPER1, and ERRs in ovarian and endometrial cancers listed in the PubMed database have been reviewed.
Assessment of Lumbosacral Nerve Roots in Patients with Type 2 Diabetic Peripheral Neuropathy Using Diffusion Tensor Imaging

Background: Diffusion tensor imaging (DTI) has found clinical applications in the evaluation of the central nervous system and has been extensively used to image peripheral neuropathy. However, few studies have focused on lumbosacral nerve root fiber damage in diabetic peripheral neuropathy (DPN). The aim of the study was to evaluate whether DTI of the lumbosacral nerve roots can be used to detect DPN. Methods: Thirty-two type 2 diabetic patients with DPN and thirty healthy controls (HCs) were investigated with a 3T MRI scanner. DTI with tractography of the L4, L5, and S1 nerve roots was performed. Anatomical fusion with the axial T2 sequences was used to provide correlating anatomical information. Mean fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values were measured from tractography images and compared between groups. Diagnostic value was assessed using receiver operating characteristic (ROC) analysis. The Pearson correlation coefficient was used to explore the correlation between DTI parameters and clinical data and the nerve conduction study (NCS) in the DPN group. Results: In the DPN group, FA was decreased (p < 0.001) and ADC was increased (p < 0.001) compared with the values of the HC group. FA displayed the best diagnostic accuracy, with an area under the ROC curve of 0.716. ADC was positively correlated with HbA1c level (r = 0.379, p = 0.024) in the DPN group. Conclusions: DTI of lumbosacral nerve roots demonstrates appreciable diagnostic accuracy in patients with DPN.
Modeling and Simulation of Fe-Doped GaN PCSS in High-Power Microwave

In this article, the characteristics of linear GaN photoconductive semiconductor switch (PCSS) in high-power microwaves are investigated by Silvaco TCAD (Technology Computer-Aided Design). By comparison of optical absorption efficiency among three types of PCSS structures, the optimized Fe-doped GaN PCSS is designed in a side-illuminated, vertical structure with a spot size of <inline-formula> <tex-math notation="LaTeX">$1\times $ </tex-math></inline-formula> 8 mm. The photocurrent of side-illuminated GaN vertical PCSS (vPCSS) begins to saturate at 1.65 mJ with the increase of applied optical energy. The average saturated switch resistance and electron concentration of vPCSS under a bias voltage of 5–20 kV are almost <inline-formula> <tex-math notation="LaTeX">$8.2 \pmb \Omega $ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$3.5\times 10^{{14}}$ </tex-math></inline-formula> cm<inline-formula> <tex-math notation="LaTeX">$^{-{3}}$ </tex-math></inline-formula>, respectively. As the device is in a saturated photocurrent state, the peak photocurrent is a linear function of bias voltage. As the device is in an unsaturated photocurrent state, improving the light energy is more effective than the withstand voltage of the device to increase photocurrent. Due to the short carrier lifetime, the GaN vPCSS has the response capacity to a 50-ps pulsewidth laser. Based on side-illuminated GaN vPCSS at the bias field 200 kV/cm, a narrowband microwave with adjustable frequency (3.3–5 GHz) could be generated. The maximum output power reaches up to 1.3 kW. Effects of anti-reflective (AR) and reflective coatings on optical absorption are investigated. The photocurrent of vPCSS with both AR and reflective coatings increases by 77.2% as compared with normal vPCSS.