Miracle-dz/UniFAR-FTUs huggingface dataset:
Field-free switching of VG-SOT-pMTJ device through the interplay of SOT, exchange bias, and VCMA effects

Field-free magnetization switching via the interplay of spin orbit torque (SOT), exchange bias field (HEX), and voltage controlled magnetic anisotropy (VCMA) is crucial for the development of scalable, high speed, and energy-efficient spintronic memories. This has been experimentally demonstrated by the rapid evolution of the voltage gated-spin orbit torque-magnetic random access memory (VG-SOT-MRAM) cell, in which perpendicular spin current is fed along with the in-plane HEX and VCMA assistance for cell programming. Here, we have examined the writing properties of a three terminal voltage gated-spin orbit torque-perpendicularly magnetized magnetic tunnel junction (VG-SOT-pMTJ) device structure (IrMn/CoFeB/MgO/CoFeB) in-depth through simulation. We observed that SOT critical switching current (I_SOT) decreases either by increasing the VCMA voltage or FL thickness. Even SOT field-like torque can accelerate the switching process and modulate the critical switching current. As the VCMA voltage rises, I_SOT falls by nearly 60%. In our experimental setup, VCMA/SOT optimal pulse width and amplitude for better write delay are 1 ns and 0.3 V, respectively. Furthermore, the impacts of free layer thickness, pMTJ radius, HEX, and noise are analyzed. Finally, we demonstrate the dependency of material parameters on temperature and VCMA voltage.
Monitoring Autonomous Mowers Operative Parameters on Low-Maintenance Warm-Season Turfgrass

Robotic solutions and technological advances for turf management demonstrated excellent results in terms of quality, energy, and time consumption. Two battery-powered autonomous mowers (2 WD and 4 WD) with random patterns were evaluated according to different trampling levels (control, low, medium, high) on a typical warm season turfgrass at the DAFE, University of Pisa, Italy. Data on the percentage of area mowed, the distance traveled, the number of passages, and the number of intersections were collected through RTK devices and processed by a custom-built software (1.8.0.0). The main quality parameters of the turfgrass were also analyzed by visual and instrumental assessments. Soil penetration resistance was measured through a digital penetrometer. The efficiency significantly decreased as the trampling level increased (from 0.29 to 0.11). The over-trampled areas were mainly detected by the edges (on average for the medium level: 18 passages for the edges vs. 14 in the central area). The trampling activity caused a reduction in turf height (from about 2.2 cm to about 1.5 cm). The energy consumption was low and varied from 0.0047 to 0.048 kWh per cutting session. Results from this trial demonstrated suitable quality for a residential turf of the Mediterranean area (NDVI values from 0.5 to 0.6), despite the over-trampling activity. Soil penetration data were low due to the reduced weight of the machines, but slightly higher for the 4 WD model (at 5 cm of depth, about 802 kPa vs. 670 kPa).
Montelukast and Telmisartan as Inhibitors of SARS-CoV-2 Omicron Variant

Earlier studies with montelukast (M) and telmisartan (T) have revealed their potential antiviral properties against SARS-CoV-2 wild-type (WT) but have not assessed their efficacy against emerging Variants of Concern (VOCs) such as Omicron. Our research fills this gap by investigating these drugs’ impact on VOCs, a topic that current scientific literature has largely overlooked. We employed computational methodologies, including molecular mechanics and machine learning tools, to identify drugs that could potentially disrupt the SARS-CoV-2 spike RBD-ACE2 protein interaction. This led to the identification of two FDA-approved small molecule drugs, M and T, conventionally used for treating asthma and hypertension, respectively. Our study presents an additional potential use for these drugs as antivirals. Our results show that both M and T can inhibit not only the WT SARS-CoV-2 but also, in the case of M, the Omicron variant, without reaching cytotoxic concentrations. This novel finding fills an existing gap in the literature and introduces the possibility of repurposing these drugs for SARS-CoV-2 VOCs, an essential step in responding to the evolving global pandemic.
Chosen Features of Maple for Mathematical Modeling in Education and Practice

This paper deals with chosen features of the last versions of Maple system (Release 14 and 15) for teaching mathematical modeling online and its applications in scientific disciplines, especially in the area of economical/financial modeling; students learn mathematical modeling as an important interactive support for understanding and presenting solved real problems. In this paper is presented chosen basic ideas on process of mathematical modeling which is demonstrated in examples of several computational models in practice with the support of the system Maple.
Nanodrugs for the Treatment of Ischemic Stroke: A Systematic Review

Ischemic stroke, a significant neurovascular disorder, currently lacks effective restorative medication. However, recently developed nanomedicines bring renewed promise for alleviating ischemia’s effects and facilitating the healing of neurological and physical functions. The aim of this systematic review was to evaluate the efficacy of nanotherapies in animal models of stroke and their potential impact on future stroke therapies. We also assessed the scientific quality of current research focused on nanoparticle-based treatments for ischemic stroke in animal models. We summarized the effectiveness of nanotherapies in these models, considering multiple factors such as their anti-inflammatory, antioxidant, and angiogenetic properties, as well as their safety and biodistribution. We conclude that the application of nanomedicines may reduce infarct size and improve neurological function post-stroke without causing significant organ toxicity.
Risk Scoring Systems for Preterm Birth and Their Performance: A Systematic Review

Introduction: Nowadays, the risk stratification of preterm birth (PTB) and its prediction remain a challenge. Many risk factors associated with PTB have been identified, and risk scoring systems (RSSs) have been developed to face this challenge. The objectives of this systematic review were to identify RSSs for PTB, the variables they consist of, and their performance. Materials and methods: Two databases were searched, and two authors independently performed the screening and eligibility phases. Records studying an RSS, based on specified variables, with an evaluation of the predictive value for PTB, were considered eligible. Reference lists of eligible studies and review articles were also searched. Data from the included studies were extracted. Results: A total of 56 studies were included in this review. The most frequently incorporated variables in the RSS included in this review were maternal age, weight, history of smoking, history of previous PTB, and cervical length. The performance measures varied widely among the studies, with sensitivity ranging between 4.2% and 92.0% and area under the curve (AUC) between 0.59 and 0.95. Conclusions: Despite the recent technological and scientifical evolution with a better understanding of variables related to PTB and the definition of new ultrasonographic parameters and biomarkers associated with PTB, the RSS’s ability to predict PTB remains poor in most situations, thus compromising the integration of a single RSS in clinical practice. The development of new RSSs, the identification of new variables associated with PTB, and the elaboration of a large reference dataset might be a step forward to tackle the problem of PTB.
LVRF: A Latent Variable Based Approach for Exploring Geographic Datasets

Geographic datasets are usually accompanied by spatial non-stationarity – a phenomenon that the relationship between features varies across space. Naturally, nonstationarity can be interpreted as the underlying rule that decides how data are generated and alters over space. Therefore, traditional machine learning algorithms are not suitable for handling non-stationary geographic datasets, as they only render a single global model. To solve this problem, researchers often adopt the multiple-local-model approach, which uses different models to account for different sub-regions of space. This approach has been proven efficient but not optimal, as it is inherently difficult to decide the size of subregions. Additionally, the fact that local models are only trained on a subset of data also limits their potential. This paper proposes an entirely different strategy that interprets nonstationarity as a lack of data and addresses it by introducing latent variables to the original dataset. Backpropagation is then used to find the best values for these latent variables. Experiments show that this method is at least as efficient as multiple-local-model-based approaches and has even greater potential.
Continuous Time H-Infinity Filter with Asymptotic Convergence

In this paper H-infinity, a posteriori filter (HIPF) is converted to a continuous time H-infinity (HI) filter. Then, an observer is presented which uses the gain and the state error Gramian from the continuous time HI filter (CTHF). Asymptotic stability result of the observer’s error dynamics is derived using the Lyapunov energy functional.
Axiomatic foundations of a unifying concept of the core of games in effectiveness form

We provide an axiomatic characterization of the core of games in effectiveness form. We point out that the core, whenever it applies to appropriate classes of these games, coincides with a wide variety of prominent stability concepts in social choice and game theory, such as the Condorcet winner, the Nash equilibrium, the pairwise stability, and the stable matchings, among others. Our characterization of the core invokes the axioms of non-emptiness, coalitional unanimity, and Maskin monotonicity together with a principle of independence of irrelevant states, and uses in its proof a holdover property echoing the conventional ancestor property. Taking special cases of this general characterization of the core, we derive new characterizations of the previously mentioned stability concepts.
The association between COVID-19 preventive strategies, virtual reality exercise, use of fitness apps, physical, and psychological health: testing a structural equation moderation model

Background Directly or indirectly, individual psychosocial characteristics, motivation, and health consciousness factors help to maintain physical and psychological health through maintaining physical activity. Objective In the current study, we investigated how fitness apps moderate the links among COVID-19 preventive strategies, virtual reality exercise, physical health, and psychological health in Chinese society. Method A nationwide online survey across China was conducted under a snowball sampling design from February to June 2022. A total of 3,000 questionnaires were distributed across China via online platforms. A total of 2,795 complete detailed replies were included in the final analysis. Structural equation modeling techniques were employed to analyze the collected data through Smart-PLS 3.0. Results It has been statically proved that all the scales used in this inquiry to determine the mean scores, standard deviation, excess kurtosis, and skewness values were reliable and produced satisfactory results. The overall results (H1: β = 0.385, t = 15.699, p = 0.000; H2: β = 0.159, t = 7.405, p = 0.000; H3: β = 0.122, t = 5.435, p = 0.000; H4: β = 0.143, t = 6.493, p = 0.000; H5: β = 0.157, t = 6.444, p = 0.000; H6: β = 0.184, t = 9.071, p = 0.000; H7: β = 0.192, t = 9.319, p = 0.000; H8: β = 0.235, t = 11.899, p = 0.000; H9: β = −0.114, t = 4.872, p = 0.000; H10: β = 0.042, t = 2.872, p = 0.004; H11: β = 0.041, t = 2.699, p = 0.007) supported our hypothetical model and explained that using fitness apps and virtual reality exercise benefits physical and psychological health. Conclusion The fitness app’s primary purpose during and after the pandemic is to motivate users to keep up with their regular at-home workouts. Exercise and active living are helpful in the prevention of risk factors associated with physical inactivity.
Absolute rotation detection by Coriolis force measurement using optomechanics

In this article, we present an application of the optomechanical cavities for absolute rotation detection. Two optomechanical cavities, one in each arm, are placed in a Michelson interferometer. The interferometer is placed on a rotating table and is moved with a uniform velocity of y ¯ ˙ with respect to the rotating table. The Coriolis force acting on the interferometer changes the length of the optomechanical cavity in one arm, while the length of the optomechanical cavity in the other arm is not changed. The phase shift corresponding to the change in the optomechanical cavity length is measured at the interferometer output to estimate the angular velocity of the absolute rotation. An analytic expression for the minimum detectable rotation rate corresponding to the standard quantum limit of measurable Coriolis force in the interferometer is derived. Squeezing technique is discussed to improve the rotation detection sensitivity by a factor of γ m / ω m at 0 K temperature, where γ m and ω m are the damping rate and angular frequency of the mechanical oscillator. The temperature dependence of the rotation detection sensitivity is studied.
Achieving Energy-Efficient Massive URLLC Over Cell-Free Massive MIMO

Achieving energy-efficient massive ultrareliable and low-latency communications (E2-mURLLC) is a promising application prospect for sixth-generation (6G) mobile communication networks. However, there are some insurmountable obstacles, such as a large number of potential users, complex and diverse small-scale and shadow fading, and stringent energy efficiency (EE), reliability, and latency requirements. Considering the above obstacles, we propose a cell-free massive multiple-input–multiple-output (MIMO) architecture based on the $\kappa $ - $\mu $ shadowed fading model, and maximum-ratio combining (MRC) multiuser detection with simple path-loss decoding (S-PLD) to achieve the simultaneous optimization of EE, latency, and reliability. Furthermore, the finite blocklength information theory is used to uncover the relationship among EE, reliability, latency, and achievable data rate when the packet size is small. Simulation results show that compared with the massive MIMO architecture, using our architecture with MRC multiuser detection and S-PLD can support a threefold increase in the number of access users, reduce transmit power by 90%, achieve a nearly 100 times reliability enhancement, and shorten transmission latency by 23.3%. Consequently, a cell-free massive MIMO system with MRC multiuser detection and S-PLD, as a considerable significant potential to facilitate the advancement from URLLC to E2-mURLLC, is promising to support some time-sensitive applications with massive access, such as unmanned aerial vehicles, the Industrial Internet of Things and vehicle-to-vehicle communications.
IDENTIFICATION OF CRYPTOSPORIDIUM SP. IN SUMATRAN ORANGUTAN AND BORNEAN ORANGUTAN AT NORTH SUMATERA WILDLIFE PARK

Cryptosporidium sp. is a zoonotic intestinal protozoa in orangutans which is transmitted through contaminated water (waterborne disease). This study aims to determine Cryptosporidium sp. which infects the sumatran orangutan (Pongo abelii) and the bornean orangutan (Pongo pygmaeus) in North Sumatera Wildlife Park. The samples used were 3 orangutan fecal samples from different locations, two bornean orangutans in Medan Wildlife Park and one sumatran orangutan in Pematang Siantar Animal Park. Samples were examined using the floatation method and the modified Ziehl-Neelsen method. The results showed that from 3 samples of orangutan feces (sumatran and bornean orangutan), 2 positive tails from bornean orangutans were found containing Cryptosporidium oocysts, namely the C. parvum species. In this study, it can be concluded that the orangutans in Medan Wildlife Park, the bornean orangutan were infected with cryptosporidiosis.
Unusual energy state evolution in Ce-based metallic glass under high pressure

Metallic Glasses (MGs) are always aging toward the lower energy state, which leads to higher density, modulus, and hardness. We find that high pressure (HP) could lead to similar densification and hardening while the energy is increased. The comparison between two processes under HP and ambient pressure shows that densification happens in denser regions in MGs under HP, while it happens in looser regions under ambient pressure, which leads to the opposite energy changes in the two conditions. This result breaks the common wisdom about the relationship between the free volume and enthalpy and displays different structural and energy evolutions in MGs.
Pseudotoric structures: Lagrangian submanifolds and Lagrangian fibrations

This survey presents a generalization of the notion of a toric structure on a compact symplectic manifold: the notion of a pseudotoric structure. The language of these new structures appears to be a convenient and natural tool for describing many non-standard Lagrangian submanifolds and cycles (Chekanov's exotic tori, Mironov's cycles in certain particular cases, and others) as well as for constructing Lagrangian fibrations (for example, special fibrations in the sense of Auroux on Fano varieties). Known properties of pseudotoric structures and constructions based on these properties are discussed, as well as open problems whose solution may be of importance in symplectic geometry and mathematical physics. Bibliography: 28 titles.
A Ketogenic Diet in Combination with Gemcitabine Mitigates Pancreatic Cancer-Associated Cachexia in Male and Female KPC Mice

Cancer-associated cachexia (CAC) is a critical contributor to pancreatic ductal adenocarcinoma (PDAC) mortality. Thus, there is an urgent need for new strategies to mitigate PDAC-associated cachexia; and the exploration of dietary interventions is a critical component. We previously observed that a ketogenic diet (KD) combined with gemcitabine enhances overall survival in the autochthonous LSL-KrasG12D/+; LSL-Trp53 R172H/+; Pdx1-Cre (KPC) mouse model. In this study, we investigated the effect and cellular mechanisms of a KD in combination with gemcitabine on the maintenance of skeletal muscle mass in KPC mice. For this purpose, male and female pancreatic tumor-bearing KPC mice were allocated to a control diet (CD), a KD, a CD + gemcitabine (CG), or a KD + gemcitabine (KG) group. We observed that a KD or a KG-mitigated muscle strength declined over time and presented higher gastrocnemius weights compared CD-fed mice. Mechanistically, we observed sex-dependent effects of KG treatment, including the inhibition of autophagy, and increased phosphorylation levels of eIF2α in KG-treated KPC mice when compared to CG-treated mice. Our data suggest that a KG results in preservation of skeletal muscle mass. Additional research is warranted to explore whether this diet-treatment combination can be clinically effective in combating CAC in PDAC patients.
Depot-specific adaption of adipose tissue for different exercise approaches in high-fat diet/streptozocin-induced diabetic mice

Background: Adipose tissue pathology plays a crucial role in the pathogenesis of type 2 diabetes mellitus. Understanding the impact of exercise training on adipose tissue adaptation is of paramount importance in enhancing metabolic health. In this study, we aimed to investigate the effects of various exercise modalities on three distinct adipose tissue depots, namely, interscapular brown adipose tissue (iBAT), subcutaneous white adipose tissue (sWAT), and epididymal white adipose tissue (eWAT), in a murine model of diabetes. Methods: Male C57BL/6J mice received a 12-week high-fat diet and a single injection of streptozotocin, followed by an 8-week exercise intervention. The exercise intervention included swimming, resistance training, aerobic exercise, and high-intensity interval training (HIIT). Results: We found that exercise training reduced body weight and body fat percentage, diminished adipocyte size and increased the expression of mitochondria-related genes (PGC1, COX4, and COX8B) in three adipose tissue depots. The effects of exercise on inflammatory status include a reduction in crown-like structures and the expression of inflammatory factors, mainly in eWAT. Besides, exercise only induces the browning of sWAT, which may be related to the expression of the sympathetic marker tyrosine hydroxylase. Among the four forms of exercise, HIIT was the most effective in reducing body fat percentage, increasing muscle mass and reducing eWAT adipocyte size. The expression of oxidative phosphorylation and thermogenesis-related genes in sWAT and eWAT was highest in the HIIT group. Conclusion: When targeting adipose tissue to improve diabetes, HIIT may offer superior benefits and thus represents a more advantageous choice.
A Local-Global Feature Fusing Method for Point Clouds Semantic Segmentation

In recent years, the abundance of information in 3D data has made the semantic segmentation of 3D point clouds a topic of great interest. However, current methods often rely solely on the original three-dimensional coordinates of the point cloud as input geometric features, leading to poor generalization performance. Additionally, occlusion of the point cloud data can negatively impact segmentation accuracy when only local information is considered. To address these issues, this paper proposes a network named LGFF-Net. To fully utilize the original information of point clouds, we designed a Local Feature Aggregation (LFA) module that treats geometric and semantic information equally and preserves the original properties while cross-augmenting them. On the other hand, we proposed a simple and effective Global Feature Extraction (GFE) module to extract global features. Finally, we hierarchically fuse local and global features using a U-shaped segmentation structure. Compared to state-of-the-art networks, our method achieves competitive results on several benchmark datasets, including Semantic Topographic Point Labeling-Synthetic 3D, Toronto_3D, Stanford Large 3-D Indoor Space, and ScanNet. We also conduct multiple ablation experiments to validate the efficacy of LGFF-Net.
Steganography in binary image by checking data-carrying eligibility of boundary pixels

我们在场为没有介绍显著人工制品，把秘密数据嵌进一幅二进制图象的一个新奇计划。 不同于一些基于块的方法，建议计划由为嵌入资格在一份假散乱订单检查盖子图象的每个象素直接编码秘密的位进边界象素。 一套规则在盲目抽取保证带数据的象素的正确鉴定。 建议计划不产生孤立的点，并且能合并象矩阵编码进一步改进嵌入的表演那样的各种各样的编码方法。 多达四分之一个边界象素可以被用来带秘密数据，这被显示出。 试验性的结果显示方法能与相当大的数据能力完成好视觉质量。