Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatiotemporal information preservation in turbulent vapor plumes

Monitoring of airborne chemicals is essential for public safety and environmental applications, but the complex nature of stochastic airflow limits the accuracy of data acquired from chemical sensors, including the identity, concentration, and location of a chemical source. Here, we explore the limits on information retrieval in a turbulent environment using temporally modulated vapor plumes. By exploiting the physical and statistical properties of turbulent flow, we demonstrate higher classification rates (≥20 Hz) at lower chemical error rates (≤0.1%) than prior reports. Physical constraints on vapor sensing are explored, including finite spatial sampling, large path distances (≥3 m), dilute concentrations (≤1 ppb), dynamic wind velocities (V = 0–5 m/s), cross winds, and occluded airflows. Our results highlight the fact that as turbulence increases, smaller structures can be embedded in an air flow, which increases measurement variance, but also makes each plume more quickly and accurately identifiable. For a given wind velocity, there exists a modulation rate which optimizes the rate of preserved information. This raises interesting possibilities for the identification of optimally preserved patterns in a turbulent environment.Monitoring of airborne chemicals is essential for public safety and environmental applications, but the complex nature of stochastic airflow limits the accuracy of data acquired from chemical sensors, including the identity, concentration, and location of a chemical source. Here, we explore the limits on information retrieval in a turbulent environment using temporally modulated vapor plumes. By exploiting the physical and statistical properties of turbulent flow, we demonstrate higher classification rates (≥20 Hz) at lower chemical error rates (≤0.1%) than prior reports. Physical constraints on vapor sensing are explored, including finite spatial sampling, large path distances (≥3 m), dilute concentrations (≤1 ppb), dynamic wind velocities (V = 0–5 m/s), cross winds, and occluded airflows. Our results highlight the fact that as turbulence increases, smaller structures can be embedded in an air flow, which increases measurement variance, but also makes each plume more quickly and accurately identifiable.
SciFi - A large Scintillating Fibre Tracker for LHCb

The LHCb detector will be upgraded during the Long Shutdown 2 (LS2) of the LHC in order to cope with higher instantaneous luminosities and to read out the data at 40MHz using a trigger-less read-out system. All front-end electronics will be replaced and several sub-detectors must be redesigned to cope with higher occupancy. The current tracking detectors downstream of the LHCb dipole magnet will be replaced by the Scintillating Fibre (SciFi) Tracker. Concept, design and operational parameters are driven by the challenging LHC environment including significant ionising and neutron radiation levels. Over a total active surface of 360m2 the SciFi Tracker will use scintillating fibres (O 0.25 mm) read out by Silicon Photomultipliers (SiPMs). State-of-the-art multi-channel SiPM arrays are being developed to read out the fibres and a custom ASIC will be used to digitise the signals from the SiPMs. The project is now at the transition from R&D to series production. We will present the evolution of the design and the latest lab and test beam results.
Novel angular-independent higher order band-stop frequency selective surface for X-band applications

A higher order miniaturised band-stop frequency selective surface (FSS) with angular stability performance for X-band applications is presented in this study. The miniaturisation has been achieved by incurving the arms of conventional cross dipole shape inside. The unit cell size of FSS is diminished up to 75% compared to cross dipole FSS operating at the same resonant frequencies. Moreover, the presented FSS is designed to exhibit stable angular performance for incident angles up to about 60° for TE- and TM-polarised waves. The maximum relative frequency deviation is 1.28% with respect to different angles of incidence. Although the designed FSS consists of two layers, higher order and sharp roll-off filter characteristics have been obtained. The simulation of the proposed FSS is performed with the CST MWS. To verify the simulation results, the presented FSS is measured and a good match between the experimental and simulation results are obtained.
Cosmic ray physics with TeV muons in large volume detectors

Large volume detectors such as IceCube, designed for the detection of astrophysical neutrinos register cosmic ray-induced atmospheric muon bundles at a rate of several thousand events per second. Due to the large amount of surrounding material, the effective energy threshold for muons reaching the detector typically lies at approximately one TeV. Through careful evaluation of event profiles it is possible to address cosmic ray and particle physics issues in an unprecedented energy region. Results from the analysis of one year of IceCube data are presented and their implications discussed.
Object tracking by transitive learning using perspective transformation with asymptotic stability

Abstract. Object tracking is a core subject in computer vision and has significant meaning in both theory and practice. We propose a tracking method in which a robust discriminative classifier is built based on both object and context information. In this method, we consider multiple frames of local invariant features on and around the object and construct the object template and context template. To overcome the limitation of the invariant representations, we also design a nonparametric learning algorithm using transitive matching perspective transformation. This learning algorithm can keep adding object appearance and can avoid improper updating when occlusions appear. We also analyze the asymptotic stability of our method and prove its drift-free capability in long-term tracking. Extensive experiments using challenging publicly available video sequences that cover most of the critical conditions in tracking demonstrate the enhanced strength and robustness of our method.
Crossover Designs: Testing, Estimation, and Sample Size

This book introduces commonly-used and well-established statistical tests and estimators in epidemiology that can easily be applied to hypothesis testing and estimation of the relative treatment effect for various types of data scale in crossover designs. Models with distribution-free random effects are assumed and hence most approaches considered here are semi-parametric. The book provides clinicians and biostatisticians with the exact test procedures and exact interval estimators, which are applicable even when the number of patients in a crossover trial is small. Systematic discussion on sample size determination is also included, which will be a valuable resource for researchers involved in crossover trial design.
Retail Therapy: A Qualitative Investigation of Therapeutic Role of Shopping in Negative Affect

This paper focuses on producing a holistic understanding of Retail Therapy and systematically reviewing the existing literature in the field of retail therapy and negative affect. Previously, there was a dearth of direct investigation on retail therapy. This paper synthesizes the different sources of knowledge on retail therapy published between 1988 to 2022 and provides an integrative and comprehensive understanding of the therapeutic role of shopping in emotional regulation. The study used only secondary data collected from different scientific journals, books, and, websites. The finding of the paper is consistent with previous studies on retail therapy that, shopping is therapeutic but not always. It has a healing power but also can make a person addicted to compulsive buying.
MODELING THE EVOLUTION OF AN AGGRESSIVE TOTALITARIAN REGIME: A GEOMETRIC APPROACH

The article is devoted to the methodology of modelling the evolution of an aggressive totalitarian regime. The methodology is grounded on the macroeconomic functions and their geometric reflection. Several models are built and analyzed in the article, such as the socio-political, military-economic and socio-economic evolution of totalitarian society; evolution of labour potential; goods’ net exports and production capacity of the country with a variable level of nationalization of the economy; changing economic potential during the war between a large totalitarian country and a small democracy country. The nowadays totalitarian regime (similar to the previous one) is based on the nationalization of the economy and the manipulation of information. The nationalization isn’t total now, but the means of manipulation have improved significantly. The authors suggested that the reduction of repression in a totalitarian country is not a sign of its liberalization. The economic growth leads to the impoverishment of the population, and economic crises – to its disqualification in quasi-market circumstances. Together they strengthen the regime's social base. High prices for low-tech goods increase the level of nationalization of the economy and, consequently, reduce the country's productive potential. Specialization in low-tech exports puts it in a "trap of nationalization", where the positive trade balance becomes impossible to even with lower levels of government regulation. Deteriorating global conditions for trade in low-tech goods create a situation of uncertainty when the level of nationalization can both fall and rise. The excess of maximum allowable losses over the minimum possible losses of a large totalitarian country becomes the "trigger" for open aggression. The fundamental asymmetry like the losses for the military-and-economic potential of a large totalitarian country and a small democratic country is the peculiarity of the clash between them.
Permeability prediction using machine learning, exponential, multiplicative, and hybrid models

Abstract The authors present a unified methodology for permeability prediction with nonlinear multiplicative, exponential, and hybrid multiplicative-exponential nonlinear models. Due to logarithmic transform of these models they may be used for prediction with both linear regression and various machine learning methods. It was demonstrated that enhancement of prediction accuracy is achieved with new two-level adjustable committee machines. The new prediction methodology was tested on data from sandstone and carbonate reservoirs with similar pattern of improvement of prediction accuracy due to using nonlinear prediction models and two-level committee machines.
Genomic epidemiology of dengue in Shantou, China, 2019

Objectives Dengue has been endemic in Southeast Asian countries for decades. There are few reports tracing the dynamics of dengue in real time. In this study, we generated hundreds of pathogen genomes to understand the genomic epidemiology of an outbreak in a hyper-endemic area of dengue. Methods We leveraged whole-genome short-read sequencing (PE150) to generate genomes of the dengue virus and investigated the genomic epidemiology of a dengue virus transmission in a mesoscale outbreak in Shantou, China, in 2019. Results The outbreak was sustained from July to December 2019. The total accumulated number of laboratory-confirmed cases was 944. No gender bias or fatalities were recorded. Cambodia and Singapore were the main sources of imported dengue cases (74.07%, n = 20). A total of 284 dengue virus strains were isolated, including 259 DENV-1, 24 DENV-2, and 1 DENV-3 isolates. We generated the entire genome of 252 DENV isolates (229 DENV-1, 22 DENV-2, and 1 DENV-3), which represented 26.7% of the total cases. Combined epidemiological and phylogenetic analyses indicated multiple independent introductions. The internal transmission evaluations and transmission network reconstruction supported the inference of phylodynamic analysis, with high Bayes factor support in BSSVS analysis. Two expansion founders and transmission chains were detected in CCH and LG of Shantou. Conclusions We observed the instant effects of genomic epidemiology in monitoring the dynamics of DENV and highlighted its prospects for real-time tracing of outbreaks of other novel agents in the future.
Somatic Embryogenesis in Conifers: One Clade to Rule Them All?

Somatic embryogenesis (SE) in conifers is usually characterized as a multi-step process starting with the development of proembryogenic cell masses and followed by histodifferentiation, somatic embryo development, maturation, desiccation, and plant regeneration. Our current understanding of conifers’ SE is mainly derived from studies using Pinaceae species as a model. However, the evolutionary relationships between conifers are not clear. Some hypotheses consider conifers as a paraphyletic group and Gnetales as a closely related clade. In this review, we used an integrated approach in order to cover the advances in knowledge on SE in conifers and Gnetales, discussing the state-of-the-art and shedding light on similarities and current bottlenecks. With this approach, we expect to be able to better understand the integration of these clades within current studies on SE. Finally, the points discussed raise an intriguing question: are non-Pinaceae conifers less prone to expressing embryogenic competence and generating somatic embryos as compared to Pinaceae species? The development of fundamental studies focused on this morphogenetic route in the coming years could be the key to finding a higher number of points in common between these species, allowing the success of the SE of one species to positively affect the success of another.
Wavelet Based Analysis of ECG Signal for the Detection of Myocardial Infarction Using SVM Classifier

This paper introduce a new technique for automatic and accurate detection of heart attack which is also known as Myocardial Infarction. The ECG signals may be corrupted with different types of noises. So an efficient noise removal technique is inevitable. In this paper, we use a denoising technique using wavelet transform which aims to estimate the signal of interest from the composite signal. Features are extracted using polynomial fitting algorithm and classification of ECG beats is done by using an SVM (support vector machine) classifier. The proposed algorithm is capable for automatic detection of heart attack and also improves the classification quality.
Theory of SHG in a medium with combined nonlinear response

Second-harmonic generation (SHG) is used in many practical applications such as substance diagnostics and imaging of various processes as well as for frequency conversion. It is well known that frequency doubling may also be used for the generation of a tripled frequency wave due to mixing of optical radiation at basic frequency with optical radiation at doubled frequency. In this case, the relationship between phases of interacting waves with basic frequency and doubled frequency plays an important role. Therefore, the solution of the corresponding problem for wave phase evolutions is an important issue. In this paper, we provide such a solution for the SHG of high-intensity femtosecond pulses, taking into account the influence of a cubic nonlinear response on frequency doubling by using an original approach together with the long pulse duration approximation and plane wave approximation. The main feature of our approach is the absence of using the basic wave energy non-depletion approximation and using the problem invariants. It should be stressed that the frequency conversion process under consideration possesses a multi-stability property: there are two modes of SHG at certain values of intensity at basic frequency. We derive the wave intensity and phase evolution for both interacting waves for each of the modes. The derived formulas are verified by computer simulation based on using corresponding nonlinear Schrodinger equations. It is very important that we demonstrate the robustness of the derived formulas for the inhomogeneous shape of the pulse. They can be applied to computing of pulse shapes and beam profiles, even if reverse energy conversion occurs. As an example, we consider SHG for an incident Gaussian pulse with basic frequency.
Disparities in Smokefree and Vapefree Home Rules and Smokefree Policy Attitudes Based on Housing Type and Cigarette Smoking Status, United States, 2019

This study examined variations in cigarette smoking status, home smoking and vaping rules, and attitudes toward smoking rules among U.S. adults. We analyzed data from the 2019 U.S. Census Bureau’s Current Population Survey Supplements (n = 40,296 adults) and calculated weighted prevalence estimates of adult cigarette smoking based on housing type. In 2019, multi-unit housing (MUH) residents who currently smoked were predominantly residents of privately rented housing (66.9%), followed by privately owned (17.6%) and public housing (15.5%). MUH residents who currently smoked had the highest proportions of allowing smoking (26.7%) or vaping (29.1%) anywhere inside their homes and were least likely to support rules allowing smoking inside all MUH apartments or living areas. In the adjusted models, MUH residents with a current smoking status were 92% less likely to have a complete smoking ban. More than one in four MUH residents with a current smoking status allowed all smoking inside the home and supported allowing smoking inside all MUH apartment or living areas, reinforcing how MUH residents may be at higher risk of experiencing secondhand smoke or aerosol exposure, or incursions within their places of residence. Our results can inform the development, implementation, and sustainment of strategies to reduce exposures from tobacco and nicotine products in all living environments.
A Comparative and Collaborative Study of the Hydrodynamics of Two Swimming Modes Applicable to Dolphins

This paper presents a hydrodynamics study that examines the comparison and collaboration of two swimming modes relevant to the universality of dolphins. This study utilizes a three-dimensional virtual swimmer model resembling a dolphin, which comprises a body and/or caudal fin (BCF) module, as well as a medium and/or paired fin (MPF) module, each equipped with predetermined kinematics. The manipulation of the dolphin to simulate various swimming modes is achieved through the application of overlapping grids in conjunction with the parallel hole cutting technique. The findings demonstrate that the swimming velocity and thrust attained through the single BCF mode consistently surpass those achieved through the single MPF mode and collaborative mode. Interestingly, the involvement of the MPF mode does not necessarily contribute to performance enhancement. Nevertheless, it is encouraging to note that adjusting the phase difference between the two modes can partially mitigate the limitations associated with the MPF mode. To further investigate the potential advantages of dual-mode collaboration, we conducted experiments by increasing the MPF frequency while keeping the BCF frequency constant, thus introducing the concept of frequency ratio (β). In comparison to the single BCF mode, the collaborative mode with a high β exhibits superior swimming velocity and thrust. Although its efficiency experiences a slight decrease, it tends to stabilize. The corresponding flow structure indirectly verifies the favorable impact of collaboration.
Cross-Sectional Analysis of Colombian University Students’ Perceptions of Mental Health during the COVID-19 Pandemic: Repercussions on Academic Achievement

Background: During the COVID-19 pandemic, the increase in academic activities at home negatively impacted mental health, due to significant levels of stress, anxiety, and depression. We investigated the association of depression and anxiety with university students’ academic performance during the COVID-19 lockdown in Bucaramanga, Colombia. Materials and Methods: A cross-sectional study was conducted through an online survey during the lockdown, through the use of the Hospital Anxiety and Depression Scale (HADS) and the grade-point average. Results: 1090 females, out of 1957 students, with mean age 22.2 ± 5.3 years, participated in the study. The prevalence of low academic performance was higher in men (4.7% p = 0.014). As for mental health, 2.5% of the students were classified as “definite cases” of anxiety and 8.2% were diagnosed with depression. Women with a low academic performance had a greater percentage of being “definite cases” (3.8%) of anxiety as compared to men (1.1%). Regarding depression, in men, 12.2% of those with low academic performance were “definite cases” (6.9% p < 0.05); in females with low academic performance, 10.1% were “definite cases” of depression, according to the Poisson regression analysis. The probability of low performance was 100% higher for women identified as “doubtful cases” of depression (PR = 2.0; 95% CI: 1.10–5.18, p = 0.03). Conclusions: A positive association between the severity of anxiety/depression and lower grades, especially in women, was found. Mental health should be a special concern when considering university students, in order to improve their academic performance.
Does Robot Assisted Laparoscopy (RAL) Have an Advantage in Preservation of Ovarian Reserve in Endometriosis Surgery? Comparison of Single-Port Access (SPA) RAL and SPA Laparoscopy

The purpose of this study was to compare single-port access (SPA) laparoscopy and SPA robot assisted laparoscopy (RAL) for endometriosis with respect to ovarian reserve preservation and surgical outcomes. Clinical factors affecting any reduction in ovarian function after surgery were also evaluated. Patients with endometriosis who underwent SPA laparoscopy (n = 87) or RAL (n = 78) were retrospectively reviewed. Patients’ baseline characteristics, including the severity of endometriosis and surgical outcomes including surgical complexity, were collected. To assess the preservation of ovarian reserve after surgery, serum anti-Müllerian hormone (AMH) levels before surgery, at two weeks, and at three months after surgery were collected. Age, ovarian cyst size, location of cyst, complexity of surgery, and the severity of endometriosis were associated with the reduction in AMH levels after surgery. The severity of endometriosis was higher in the RAL group than in the SPA group. There were no significant differences in other clinical baseline characteristics, including preoperative AMH levels. For surgical outcomes, radical surgery was more frequently performed in the RAL group. In univariate and multivariate linear regression analyses, age, ovarian cyst size, location of cyst, complexity of surgery, and the severity of endometriosis were associated with the reduction in AMH levels after surgery. Incorporating surgical approaches and risk factors for postoperative ovarian function decrease, RAL was more beneficial than SPA laparoscopy for the preservation of ovarian reserve in patients with mild endometriosis (stage I/II) (postoperative 3 month AMH reduction rate (%), SPA laparoscopy vs. RAL, 33.51 ± 19.98 vs. 23.58 ± 14.98, p = 0.04) and in patients who underwent non-complex surgery (postoperative 3 month AMH reduction rate (%), SPA laparoscopy vs. RAL, 37.89 ± 22.37 vs. 22.37 ± 17.49, p = 0.022). SPA RAL may have advantages over SPA laparoscopy in ovarian function preservation, especially in patients with mild endometriosis and patients who have undergone a non-complex surgery.