Miracle-dz/UniFAR-FTUs huggingface dataset:
Power Spectrum Analysis of the Two-Degree Field QSO Sample Revisited

We revisit the power spectrum analysis of the complete sample of the Two-Degree field (2dF) QSO redshift (2QZ) survey, as a complementary test of the work by Outram et al. A power spectrum consistent with that of the 2QZ group is obtained. Differently from their approach, fitting of the power spectrum is investigated by incorporating the nonlinear effects, the geometric distortion, and the light-cone effect. It is shown that the QSO power spectrum is consistent with a Λ cold dark matter model with the matter density parameter Ωm = 0.2-0.5. Our constraint on the density parameter is rather weaker than that of the 2QZ group. We also show that the constraint slightly depends on equation-of-state parameter w of the dark energy. The constraint on w from the QSO power spectrum is demonstrated, although it is not very tight.
BL LAC CANDIDATES FOR TeV OBSERVATIONS

BL Lac objects are the most numerous class of extragalactic TeV-detected sources. One of the biggest difficulties in investigating their TeV emission is due to their limited number, since only 47 BL Lac objects are known to be TeV emitters. In this paper, we propose new criteria to select TeV BL Lac candidates based on infrared and X-ray observations. We apply our selection criteria to the BL Lac objects listed in the ROMA-BZCAT catalog, thereby identifying 41 potential TeV emitters. We then perform a search over a more extended sample combining the ROSAT bright source catalog and the WISE all-sky survey, revealing 54 additional candidates for TeV observations. Our investigation also led to a tentative classification of 16 unidentified X-ray sources as BL Lac candidates. This analysis provides new interesting BL Lac targets for future observations with ground-based Cherenkov telescopes.
Experimental investigations of soil fluidization by an upward water leak jet

ABSTRACT In this paper, a fluidized granular sand bed by a vertically upward water leak jet was studied experimentally. It was found that an increase in the size of sand particles decreases the height of the fluidized zone, and vice versa. By increasing the cover depth, the height and area of the fluidized and mobilized bed zones are reduced. Dimensions of the fluidized zone increase as the pressure increases. As the pressure inside the pipe increases 5-fold, the relative area of the fluidized zone increases approximately 3.5-fold, and the relative height increases 12-fold. By increasing ratio of the cover depth to mean particle size, the relative area and relative height of fluidization increases. New equations were obtained to determine the relative area and the relative height of the fluidized zone.
Evaluation of glueball masses from supergravity

In the framework of the conjectured duality relation between large {ital N} gauge theory and supergravity the spectra of masses in large {ital N} gauge theory can be determined by solving certain eigenvalue problems in supergravity. In this paper we study the eigenmass problem given by Witten as a possible approximation for masses in QCD without supersymmetry. We place a particular emphasis on the treatment of the horizon and related boundary conditions. We construct exact expressions for the analytic expansions of the wave functions both at the horizon and at infinity and show that requiring smoothness at the horizon and normalizability gives a well defined eigenvalue problem. We show, for example, that there are no smooth solutions with a vanishing derivative at the horizon. The mass eigenvalues up to m{sup 2}=1000 corresponding to smooth normalizable wave functions are presented. We comment on the relation of our work with the results found in a recent paper by C. Cs{acute a}ki {ital et al.}, hep-th/9806021, which addresses the same problem. {copyright} {ital 1998} {ital The American Physical Society}
Vocabulario emocional y casos de cyberbullying en alumnado universitario

El uso de las tecnologías ha propiciado nuevas formas de violencia, como es el caso del cyberbullying, haciendo necesarias nuevas estrategias emocionales para prevenirlo. En el presente artículo se pretende evaluar la presencia de bullying y cyberbullying en las titulaciones universitarias relacionadas con el ámbito educativo, haciendo énfasis en la incidencia de casos, las estrategias usadas y los sentimientos experimentados durante el abuso. Además, dada la importancia del vocabulario emocional en la gestión de emociones, se observarán diferencias entre estudiantes de grados educativos y otros ajenos a este ámbito, así como las posibles diferencias de género. Para responder a estas cuestiones contamos con la participación de 398 estudiantes universitarios españoles, clasificados según su pertenencia a titulaciones del ámbito educativo u otros grados, y en segundo lugar según el género, a los que se realizó la prueba de vocabulario, y 108 estudiantes de educación que respondieron el cuestionario de cyberbullying. Con respecto a la incidencia del cyberbullying, se advierte un mayor número de agresores hombres y una correlación existente entre ser agresor y víctima y entre ser víctima de bullying tradicional y cyberbullying, tanto telefónico como vía internet. Con respecto al vocabulario, los resultados muestran un mayor número de palabras emocionales expresadas por los estudiantes de grados educativos, tanto en el vocabulario emocional general como en las agrupaciones emocionales de miedo, alegría y felicidad.
Macromolecular Dynamics. An introductory lecture

This lecture has the following sections: Systems and States; Brownian Motion; Segmental Relaxation and the Glass Transition; Dynamics of a Free Chain; Entanglement and Reptation. Appendices cover: Linear response theory, relaxation, dissipation, fluctuation; Debye's theory of dielectric relaxation; Zimm's theory of chain dynamics in solution.
G-Quadruplex Linked DNA Guides Selective Transfection into Nucleolin-Overexpressing Cancer Cells

Gene therapy is a promising approach for treating tumors. Conventional approaches of DNA delivery depending on non-viral or viral vectors are unsatisfactory due to the concerns of biosafety and cell-targeting efficiency. The question how to deliver DNA into tumor cells efficiently and selectively is a major technological problem in tumor gene therapy. Here, we develop a vector-free gene transfer strategy to deliver genes effectively and selectively by taking advantage of targeting nucleolin. Nucleolin, a shuttle protein moving between cell membrane, cytoplasm and nuclei, is overexpressed in tumor cells. It has a natural ligand G-quadruplex (Gq). Gq-linked DNA (Gq-DNA) is likely to be internalized by ligand dependent uptake mechanisms independently of vectors after neutralizing negative charges of cell membrane by targeting nucleolin. This strategy is referred to as Gq-DNA transfection. Benefiting from its high affinity to nucleolin, Gq-DNA can be effectively delivered into nucleolin-positive tumor cells even nuclei. Gq-DNA transfection is characterized by low cytotoxicity, high efficiency, ease of synthesis, high stability in serum, direct access into nuclei, and specific nucleolin-positive tumor cell targeting.
Natural Populations from the Phytophthora palustris Complex Show a High Diversity and Abundance of ssRNA and dsRNA Viruses

We explored the virome of the “Phytophthora palustris complex”, a group of aquatic specialists geographically limited to Southeast and East Asia, the native origin of many destructive invasive forest Phytophthora spp. Based on high-throughput sequencing (RNAseq) of 112 isolates of “P. palustris” collected from rivers, mangroves, and ponds, and natural forests in subtropical and tropical areas in Indonesia, Taiwan, and Japan, 52 putative viruses were identified, which, to varying degrees, were phylogenetically related to the families Botybirnaviridae, Narnaviridae, Tombusviridae, and Totiviridae, and the order Bunyavirales. The prevalence of all viruses in their hosts was investigated and confirmed by RT-PCR. The rich virus composition, high abundance, and distribution discovered in our study indicate that viruses are naturally infecting taxa from the “P. palustris complex” in their natural niche, and that they are predominant members of the host cellular environment. Certain Indonesian localities are the viruses’ hotspots and particular “P. palustris” isolates show complex multiviral infections. This study defines the first bi-segmented bunya-like virus together with the first tombus-like and botybirna-like viruses in the genus Phytophthora and provides insights into the spread and evolution of RNA viruses in the natural populations of an oomycete species.
Signal classification using global dynamical models, Part II: SONAR data analysis

In Part I of this paper, we described a numerical method for nonlinear signal detection and classification which made use of techniques borrowed from dynamical systems theory. Here in Part II of the paper, we will describe an example of data analysis using this method, for data consisting of open ocean acoustic (SONAR) recordings of marine mammal transients, supplied from NUWC sources. The purpose here is two‐fold: first to give a more operational description of the technique and provide rules‐of‐thumb for parameter choices; and second to discuss some new issues raised by the analysis of non‐ideal (real‐world) data sets. The particular data set considered here is quite non‐stationary, relatively noisy, is not clearly localized in the background, and as such provides a difficult challenge for most detection/classification schemes.
D-brane anti-brane annihilation in an expanding universe

The time-varying density of D-branes and anti-D-branes in an expanding universe is calculated. The D-brane anti-brane annihilation rate is shown to be too small to compete with the expansion rate of a FRW type universe and the branes over-close the universe. This brane problem is analogous to the old monopole problem. Interestingly however, it is shown that small dimension D-branes annihilate more slowly than high dimension branes. Hence, an initially brany universe may be filled with only low dimension branes at late times. When combined with an appropriate late inflationary theory this leads to an attractive dynamical way to create a realistic braneworld scenario.
Income Distribution and the Quality of Life in Latin America: Patterns, Trends, and Policy Implications

Latin America, more than other regions of the capitalist world, has been characterized by persistently high concentration of income and wealth and by limited trickling-down of the material gains from output growth. This situation was an enduring characteristic of “modern economic growth” in Latin America during its era of crecimiento hacia afuera, from the mid-nineteenth century to the onset of the Great Depression of the 1930s. It has remained so, with some modification, during the subsequent half-century, despite industrialization, rapid urbanization, the spread of education, and other conquistas sociales in many of the countries, and despite the faster economic-growth rates since World War II. Indeed, a further rise of income concentration accompanying that postwar growth is statistically detectable in many of the countries. By combining pre-World War II data with plausible inference, one can also deduce a still longer-run rising-concentration trend from the mid-nineteenth century, with oscillations downward in periods of slow growth and upward during fast growth periods. The result in most countries has been a slow improvement at best for the lowest 60 percent of the population in the more measurable and less ethnocentric dimensions of that amorphous concept, the quality of life.
Effective disentanglement of measured system and measurement apparatus

We consider a multi-level system coupled to a bosonic measurement apparatus. We derive exact expressions for the time-dependent expectation values of a large class of physically relevant observables that depend on degrees of freedom of both sytems. We find that, for this class, though the two systems become entangled as a result of their interaction, they appear classically correlated for long enough times. The unique corresponding separable state is determined explicitly. To better understand the physical parameters that control the time scale of this effective disentanglement process, we study a one-dimensional measurement apparatus.
A Comprehensive Review of the Management of Acute Respiratory Distress Syndrome

Acute respiratory distress syndrome (ARDS) is an inflammatory process in the lungs that induces non-hydrostatic protein-rich pulmonary edema. ARDS occurs in roughly half of coronavirus disease 2019 (COVID-19) pneumonia patients, with most of them requiring intensive care. Oxygen saturation, partial pressure of the oxygen, and the fraction of the inspired oxygen are health indicators that may indicate a severe illness necessitating further investigation. As treatments have evolved, a typical pattern of ARDS has likewise evolved. In cases where mechanical ventilation is required, the use of low tidal volumes (<6 ml/kg ideal body weight) and airway pressures (plateau pressure <30 cmH2O) was recommended. For patients with moderate/severe ARDS (partial pressure to fractional inspired oxygen ratio <20), prone positioning was recommended for at least 16 hours per day. By contrast, high-frequency oscillation was not recommended. The use of inhaled vasodilators was recommended in patients with persistent hypoxemia despite invasive ventilation and prone position until extracorporeal membrane oxygenation (ECMO). The use of a conservative fluid management strategy was suggested for all patients. Mechanical ventilation with high positive end-expiratory pressure (PEEP) was suggested for patients with ARDS with a ratio of arterial oxygen partial pressure to fractional inspired oxygen (PF) ratios. ECMO was suggested as an adjunct to protective mechanical ventilation for patients with severe ARDS. In the absence of adequate evidence, research recommendations were made for corticosteroids and extracorporeal carbon dioxide removal. While decades of research have been conducted, treatment options for underlying pathologies remain limited, and mechanical ventilation, which removes carbon dioxide from the body, remains essential to achieving better clinical outcomes. This review aims to identify the best ARDS treatments that are currently available.
The diffuse molecular component in the nuclear bulge of the Milky Way

Context: The bulk of the Molecular gas in the Central Molecular Zone (CMZ) of the Galactic center region shows warm kinetic temperatures, ranging from $>20$ K in the coldest and densest regions (n$\sim 10^{4-5}$ cm$^{-3}$) up to more than 100 K for densities of about n$\sim 10^3$ cm$^{-3}$. Recently, a more diffuse, hotter ($n \sim 100$ cm$^{-3}$, $T\sim 250$ K) gas component was discovered through absorption observations of H$_3^+$. This component may be widespread in the Galactic center, and low density gas detectable in absorption may be present even outside the CMZ along sightlines crossing the extended bulge of the Galaxy. Aims: We aim to observe and characterize diffuse and low density gas using observations of 3-mm molecular transitions seen in absorption. Methods: Using the Atacama Large (sub)Millimeter Array (ALMA) we observed the absorption against the quasar J1744-312, which is located towards the Galactic bulge region at $(l,b)=(-2{^\circ}.13,-1{^\circ}.0)$, but outside the main molecular complexes. Results: ALMA observations in absorption against the J1744-312 quasar reveal a rich and complex chemistry in low density molecular and presumably diffuse clouds. We detected three velocity components, at $\sim $ 0, $-153$, and $-192$ km s$^{-1}$. The component at $\sim 0$ km s$^{-1}$ could represent gas in the Galactic disk while the velocity components at $-153$, and $-192$ km s$^{-1}$ likely originate from the Galactic bulge. We detected 12 molecules in the survey, but only 7 in the Galactic bulge gas.
A Nonsense Variant in the DMD Gene Causes X-Linked Muscular Dystrophy in the Maine Coon Cat

Simple Summary Muscular dystrophy (MD) in cats is a muscular disease that can have a fatal outcome. It is often caused by variants in the DMD gene and shows an X-linked recessive mode of inheritance. Therefore, females can carry such a variant without showing clinical signs of disease and can spread the variant to their offspring. These carriers can only be identified through DNA tests. Here, we identified the variant causing MD in two Maine coon cats. Maine coons can now be screened for this variant through a DNA test. Abstract (1) Feline dystrophin-deficient muscular dystrophy (ddMD) is a fatal disease characterized by progressive weakness and degeneration of skeletal muscles and is caused by variants in the DMD gene. To date, only two feline causal variants have been identified. This study reports two cases of male Maine coon siblings that presented with muscular hypertrophy, growth retardation, weight loss, and vomiting. (2) Both cats were clinically examined and histopathology and immunofluorescent staining of the affected muscle was performed. DMD mRNA was sequenced to identify putative causal variants. (3) Both cats showed a significant increase in serum creatine kinase activity. Electromyography and histopathological examination of the muscle samples revealed abnormalities consistent with a dystrophic phenotype. Immunohistochemical testing revealed the absence of dystrophin, confirming the diagnosis of dystrophin-deficient muscular dystrophy. mRNA sequencing revealed a nonsense variant in exon 11 of the feline DMD gene, NC_058386. 1 (XM_045050794.1): c.1180C > T (p.(Arg394*)), which results in the loss of the majority of the dystrophin protein. Perfect X-linked segregation of the variant was established in the pedigree. (4) ddMD was described for the first time in the Maine coon and the c.1180C>T variant was confirmed as the causal variant.
Design and Implementation of a Modular UUV Simulation Platform

The complex and time-varying marine environment puts forward demanding requirements for the structural design and algorithm development of unmanned underwater vehicles (UUVs). It is inevitable to repeatedly evaluate the feasibility of autonomy schemes to enhance the intelligence and security of the UUV before putting it into use. Considering the high cost of the UUV hardware platform and the high risk of underwater experiments, this study aims to evaluate and optimize autonomy schemes in the manner of software-in-loop (SIL) simulation efficiently. Therefore, a self-feedback development framework is proposed and a multi-interface, programmable modular simulation platform for UUV based on a robotic operating system (ROS) is designed. The platform integrates the 3D marine environment, UUV models, sensor plugins, motion control plugins in a modular manner, and reserves programming interfaces for users to test various algorithms. Subsequently, we demonstrate the simulation details with cases, such as single UUV path planning, task scheduling, and multi-UUV formation control, and construct underwater experiments to confirm the feasibility of the simulation platform. Finally, the extensibility of the simulation platform and the related performance analysis are discussed.
Understanding the neutron star population with the SKA

Thomas M. Tauris1,2, Victoria M. Kaspi∗3, Rene P. Breton4, Adam T. Deller5, Evan F. Keane6,7, Michael Kramer2, Duncan R. Lorimer8, Maura A. McLaughlin8, Andrea Possenti9, Paul S. Ray10, Ben W. Stappers11, Patrick Weltevrede11 1Argelander-Institute for Astronomy, University of Bonn, Germany; 2MPIfR, Germany; 3McGill University, Canada; 4University of Southampton, UK; 5ASTRON, The Netherlands; 6Swinburne University of Technology, Australia; 7ARC Centre of Excellence for All-Sky Astrophysics (CAASTRO); 8West Virginia University, USA; 9INAF-Osservatorio Astronomico di Cagliari, Italy; 10Naval Research Laboratory, USA; 11University of Manchester, UK E-mail: tauris@astro.uni-bonn.de vkaspi@physics.mcgill. ca
Dark energy from vacuum entanglement

We suggest that vacuum entanglement energy associated with the entanglement entropy of the universe is the origin of dark energy. The observed properties of dark energy can be explained by using the nature of entanglement energy without modification of gravity or exotic matter. From the number of degrees of freedom in the standard model, we obtain the equation of state parameter and for the holographic dark energy, which are consistent with current observational data at the 95% confidence level.
Cytarabine-Induced Bradycardia: A Case Report

Cardiotoxicity is damage to the heart muscle, which affects its function. Chemotherapy is known to cause cardiotoxicity along with many other medications and etiologies. Many chemotherapeutic cocktails are known to be associated with cardiotoxicities, such as taxane and cisplatin. Patients might have arrhythmias, severe bradycardia, cardiomyopathy, and even cardiac arrest, so precautions are taken when such medications are started. This report presents a patient who developed severe symptomatic bradycardia after receiving idarubicin and cytarabine and was managed conservatively, along with a literature review of this entity.
Smart Congestion Control in 5G/6G Networks Using Hybrid Deep Learning Techniques

With the mobility and ease of connection, wireless sensor networks have played a significant role in communication over the last few years, making them a significant data carrier across networks. Additional security, lower latency, and dependable standards and communication capability are required for future-generation systems such as millimeter-wave LANs, broadband wireless access schemes, and 5G/6G networks, among other things. Effectual congestion control is regarded as of the essential aspects of 5G/6G technology. It permits operators to run many network illustrations on a single organization while maintaining higher service quality. A sophisticated decision-making system for arriving network traffic is necessary to confirm load balancing, limit network slice letdown, and supply alternative slices in slice letdown or congestion. Because of the massive amount of data being generated, artificial intelligence (AI) and machine learning (ML) play a vital role in reconfiguring and improving a 5G/6G wireless network. In this research work, a hybrid deep learning method is being applied to forecast optimal congestion improvement in the wireless sensors of 5G/6G IoT networks. This proposed model is applied to a training dataset to govern the congestion in a 5G/6G network. The proposed approach provided promising results, with 0.933 accuracy, and 0.067 miss rate.