Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding Turbulence in Compressing Plasmas and Its Exploitation or Prevention

Unprecedented densities and temperatures are now achieved in compressions of plasma, by lasers and by pulsed power, in major experimental facilities. These compressions, carried out at the largest scale at the National Ignition Facility and at the Z Pulsed Power Facility, have important applications, including fusion, X-ray production, and materials research. Several experimental and simulation results suggest that the plasma in some of these compressions is turbulent. In fact, measurements suggest that in certain laboratory plasma compressions the turbulent energy is a dominant energy component. Similarly, turbulence is dominant in some compressing astrophysical plasmas, such as in molecular clouds. Turbulence need not be dominant to be important; even small quantities could greatly influence experiments that are sensitive to mixing of non-fuel into fuel, such as compressions seeking fusion ignition. Despite its important role in major settings, bulk plasma turbulence under compression is insufficiently understood to answer or even to pose some of the most fundamental questions about it. This thesis both identifies and answers key questions in compressing turbulent motion, while providing a description of the behavior of three-dimensional, isotropic, compressions of homogeneous turbulence with a plasma viscosity. This description includes a simple, but successful, new model for the turbulent energy of plasma undergoing compression. The unique features of compressing turbulence with a plasma viscosity are shown, including the sensitivity of the turbulence to plasma ionization, and a “sudden viscous dissipation” effect which rapidly converts plasma turbulent energy into thermal energy. This thesis then examines turbulence in both laboratory compression experiments and molecular clouds. It importantly shows: the possibility of exploiting turbulence to make fusion or X-ray production more efficient; conditions under which hot-spot turbulence can be prevented; and a lower bound on the growth of turbulence in molecular clouds. This bound raises questions about the level of dissipation in existing molecular cloud models. iii Finally, the observations originally motivating the thesis, Z-pinch measurements suggesting dominant turbulent energy, are reexamined by self-consistently accounting for the impact of the turbulence on the spectroscopic analysis. This is found to strengthen the evidence that the multiple observations describe a highly turbulent plasma state.
Using COVID-19 Vaccine Attitudes on Twitter to Improve Vaccine Uptake Forecast Models in the United States: Infodemiology Study of Tweets

Background Since the onset of the COVID-19 pandemic, there has been a global effort to develop vaccines that protect against COVID-19. Individuals who are fully vaccinated are far less likely to contract and therefore transmit the virus to others. Researchers have found that the internet and social media both play a role in shaping personal choices about vaccinations. Objective This study aims to determine whether supplementing COVID-19 vaccine uptake forecast models with the attitudes found in tweets improves over baseline models that only use historical vaccination data. Methods Daily COVID-19 vaccination data at the county level was collected for the January 2021 to May 2021 study period. Twitter’s streaming application programming interface was used to collect COVID-19 vaccine tweets during this same period. Several autoregressive integrated moving average models were executed to predict the vaccine uptake rate using only historical data (baseline autoregressive integrated moving average) and individual Twitter-derived features (autoregressive integrated moving average exogenous variable model). Results In this study, we found that supplementing baseline forecast models with both historical vaccination data and COVID-19 vaccine attitudes found in tweets reduced root mean square error by as much as 83%. Conclusions Developing a predictive tool for vaccination uptake in the United States will empower public health researchers and decisionmakers to design targeted vaccination campaigns in hopes of achieving the vaccination threshold required for the United States to reach widespread population protection.
Ultrametric properties of the attractor spaces for random iterated linear function systems

We investigate attractors of random iterated linear function systems as independent spaces embedded in the ordinary Euclidean space. The introduction on the set of attractor points of a metric that satisfies the strengthened triangle inequality makes this space ultrametric. Then inherent in ultrametric spaces the properties of disconnectedness and hierarchical self-similarity make it possible to define an attractor as a fractal. We note that a rigorous proof of these properties in the case of an ordinary Euclidean space is very difficult.
Functional Diversity of Novel Lectins with Unique Structural Features in Marine Animals

Due to their remarkable structural diversity, glycans play important roles as recognition molecules on cell surfaces of living organisms. Carbohydrates exist in numerous isomeric forms and can adopt diverse structures through various branching patterns. Despite their relatively small molecular weights, they exhibit extensive structural diversity. On the other hand, lectins, also known as carbohydrate-binding proteins, not only recognize and bind to the diverse structures of glycans but also induce various biological reactions based on structural differences. Initially discovered as hemagglutinins in plant seeds, lectins have been found to play significant roles in cell recognition processes in higher vertebrates. However, our understanding of lectins in marine animals, particularly marine invertebrates, remains limited. Recent studies have revealed that marine animals possess novel lectins with unique structures and glycan recognition mechanisms not observed in known lectins. Of particular interest is their role as pattern recognition molecules in the innate immune system, where they recognize the glycan structures of pathogens. Furthermore, lectins serve as toxins for self-defense against foreign enemies. Recent discoveries have identified various pore-forming proteins containing lectin domains in fish venoms and skins. These proteins utilize lectin domains to bind target cells, triggering oligomerization and pore formation in the cell membrane. These findings have spurred research into the new functions of lectins and lectin domains. In this review, we present recent findings on the diverse structures and functions of lectins in marine animals.
Measurement uncertainty in pulsar timing array experiments

Highly precise monitoring of arrival times of pulses from pulsars will allow for gravitational-wave detection in the nano-Hertz regime in the near future. Due to the complex nature of such pulsar-timing experiments and to the large number of effects that can affect these data (starting with magnetospheric effects at the pulsars themselves but extending across the entire signal path down to the final gravitational-wave detection algorithm), any treatment of the measurement uncertainties relevant to such a gravitational-wave detection has been lacking and incomplete so far. In this review, we provide an exhaustive description of the currently known influences on measurement precision in pulsar-timing experiments in general and in gravitational-wave detection through pulsar-timing specifically. While some of these effects remain poorly understood and largely unquantified at present, we discuss both analytic and observational quantifications where available.
CMB—A Geometric, Lorentz Invariant Model in Non-Expanding Lobachevskian Universe with a Black Body Spectral Distribution Function

In the present paper, based on Lobachevskian (hyperbolic) static geometry, we present (as an alternative to the existing Big Bang model of CMB) a geometric model of CMB in a Lobachevskian static universe as a homogeneous space of horospheres. It is shown that from the point of view of physics, a horosphere is an electromagnetic wavefront in Lobachevskian space. The presented model of CMB is an Lorentz invariant object, possesses observable properties of isotropy and homogeneity for all observers scattered across the Lobachevskian universe, and has a black body spectrum. The Lorentz invariance of CMB implies a mathematical equation for cosmological redshift for all z. The global picture of CMB, described solely in terms of the Lorentz group—SL(2C), is an infinite union of double sided quotient spaces (double fibration of the Lorentz group) taken over all parabolic stabilizers P⊂SL(2C). The local picture of CMB (as seen by us from Earth) is a Grassmannian space of an infinite union all horospheres containing origin o∈L3, equivalent to a projective plane RP2. The space of electromagnetic wavefronts has a natural identification with the boundary at infinity (an absolute) of Lobachevskian universe. In this way, it is possible to regard the CMB as a reference at infinity (an absolute reference) and consequently to define an absolute motion and absolute rest with respect to CMB, viewed as an infinitely remote reference.
Inborn Errors of Purine Salvage and Catabolism

Cellular purine nucleotides derive mainly from de novo synthesis or nucleic acid turnover and, only marginally, from dietary intake. They are subjected to catabolism, eventually forming uric acid in humans, while bases and nucleosides may be converted back to nucleotides through the salvage pathways. Inborn errors of the purine salvage pathway and catabolism have been described by several researchers and are usually referred to as rare diseases. Since purine compounds play a fundamental role, it is not surprising that their dysmetabolism is accompanied by devastating symptoms. Nevertheless, some of these manifestations are unexpected and, so far, have no explanation or therapy. Herein, we describe several known inborn errors of purine metabolism, highlighting their unexplained pathological aspects. Our intent is to offer new points of view on this topic and suggest diagnostic tools that may possibly indicate to clinicians that the inborn errors of purine metabolism may not be very rare diseases after all.
Indonesian Honey Consumers' Behavior and Sensory Preference for Commercial Trigona Honey

Consumption of honey has increased in recent years. This included trigona honey as a new market that is developing. This research was conducted to (1) identify the consumption patterns for Indonesian honey, and (2) identify the sensory attributes of honey considered ideal by consumers which influence consumer acceptance and satisfaction. There were 2 stages of activity in this study, including a consumption online survey by 225 respondents and a sensory testing of honey samples using the CATA (check-all-that-apply) method involving 64 untrained panelists. Data analysis was carried out using SPSS and XLSTAT 2022 software. There were 4 honey samples used in this study: 2 Apis bee honey samples and 2 trigona honey samples. The study showed that the consumption pattern of Indonesian honey consumers is influenced by the consumers’ age and income. Health benefits, brand awareness, and taste of honey were the important factors in consumer behavior. Apis bee honeys were perceived as the ideal honey by consumers as they were very familiar with the taste. The sweet aroma, sweet aftertaste, caramel flavor, and viscous attributes of Apis bee honey were the attributes that the consumers like. The floral flavor and fruity aroma found in trigona honey were appealing. However, the strong sour aroma, taste, and aftertaste found in trigona honeys decrease the Indonesian consumers liking.
A Systematic Review of Key Factors of Effective Collaborative Governance of Social-Ecological Systems

Abstract Sustainable resource management requires governance systems that facilitate effective collaboration among a variety of stakeholder interests, across jurisdictional scales and resource sectors. Yet, there is not widespread scholarly agreement on the key ingredients that need to be present to facilitate the effective collaborative governance of natural resources. To address this scholarly gap, we conducted a systematic literature review which revealed 17 publications that compiled essential lists of key factors for effective collaboration. From these studies across multiple disciplines, we identified 22 common factors associated with effective collaborative natural resource management, including near unanimous acceptance of the importance of nested governance structures and conflict resolution mechanisms. These 22 factors, along with additional contextual and outcome-oriented factors, could begin to form a core set of factors to comparatively test large numbers of case studies on collaborative governance of social-ecological systems around the world.
Review of theoretical literature: The relationship between credit risk management and bank profitability

Today, commercial banks are the largest financial institutions in our country. Credit risk is one of the biggest risks of these banks due to the nature of their activities. Through effective credit risk management, banks not only support the sustainability and profitability of their business, but also contribute to systemic stability and an efficient distribution of capital in the economy. This paper will focus on the theoretical analysis of the relationship between some indicators of credit risk management and indicators of bank profitability, as well as the evidence of the stability over time of this relationship.
Model study of seismic waves from explosions in rectangular cavities

Abstract The patterns of radiation of P and S waves generated by firing a charge in a rectangular hole, about 2 × 5 mm, in a thin sheet have been determined. Plexiglas and aluminum have been used as the model materials. It is shown that Knopoff and Gilbert9s theory for bilateral cracking along a plane in an infinite medium and Heelan9s theory for radiation from a cylinder give the same radiation patterns if the plane of observation is normal to the plane of the crack in the first case and includes the axis of the cylinder in the second, when the axis of cylinder is oriented in the direction of the crack. The observed radiation patterns agree satisfactorily with the predictions of these theories.
WATER LEVEL MONITORING SYSTEM IN WATER UTILITY COMPANY OPEN CHANNELS BASED ON INTERNET OF THINGS

Monitoring the water level in the open channels of the regional water utility company needs to be carried out to ensure the availability of raw water to be processed. This research focuses on making a prototype of a water level monitoring system in an open channel utilizing the WSN (Wireless Sensor Network) component as an application of the IoT (Internet of Things) concept. Monitoring the water level in the open channel is carried out using the infrared sensor GP2Y0A02KF0Y. The real-time measurement results are then sent using XBee wireless communication, then processed by the Raspberry Pi to be saved to a database and displayed on the website. The measurement data can be presented on the website in graphs and tables. The GP2Y0A02YK0F sensor has a measurement error of 1.02% with a correlation coefficient of 0.9998. The average delay in sending data to the website is 1 second. The monitoring system can work well when measuring the water level in an open channel. The advantages of this research are that the instrument used has a high level of accuracy at an affordable price, uses low power, is easy to operate, and can store and present real-time data
LiDAR Point Cloud Data Combined Structural Analysis Based on Strong Form Meshless Method Using Essential Boundary Condition Capturing

This study proposes a novel hybrid simulation technique for analyzing structural deformation and stress using light detection and ranging (LiDAR)-scanned point cloud data (PCD) and polynomial regression processing. The method estimates the edge and corner points of the deformed structure from the PCD. It transforms into a Dirichlet boundary condition for the numerical simulation using the particle difference method (PDM), which utilizes nodes only based on the strong formulation, and it is advantageous for handling essential boundaries and nodal rearrangement, including node generation and deletion between analysis steps. Unlike previous studies, which relied on digital images with attached targets, this research uses PCD acquired through LiDAR scanning during the loading process without any target. Essential boundary condition implementation naturally builds a boundary value problem for the PDM simulation. The developed hybrid simulation technique was validated through an elastic beam problem and a three-point bending test on a rubber beam. The results were compared with those of ANSYS analysis, showing that the technique accurately approximates the deformed edge shape leading to accurate stress calculations. The accuracy improved when using a linear strain model and increasing the number of PDM model nodes. Additionally, the error that occurred during PCD processing and edge point extraction was affected by the order of polynomial regression equation. The simulation technique offers advantages in cases where linking numerical analysis with digital images is challenging and when direct mechanical gauge measurement is difficult. In addition, it has potential applications in structural health monitoring and smart construction involving machine leading techniques.
Effects of proton beam irradiation on seed germination and growth of soybean (Glycine max L. Merr.)

The present study aimed to evaluate the morphological effects of proton beam irradiation on the seed germination, seedling survival, and plant growth of soybean. Seeds of three Korean elite cultivars (Kwangankong, Daepungkong, and Pungsannamulkong) were irradiated with a 57-MeV proton beam in the range of 50 - 400 Gy. The germination rates of all the varieties increased to > 95%; however, the survival rates were significantly reduced. At doses of > 300 Gy irradiation, the Daepungkong, Kwangankong, and Pungsannamulkong cultivars exhibited 39, 75, and 71% survival rates, respectively. In addition, plant height and the fresh weight of shoots and roots were significantly decreased by doses of > 100 Gy irradiation, as were the dry weights of the shoots and roots. However, SPAD values increased with increasing doses of irradiation. Abnormal plants with atypically branched stems, modified leaves, and chlorophyll mutations were observed. Based on the survival rate, plant growth inhibition, and mutation frequency, it appears that the optimum dosage of proton beam irradiation for soybean mutation breeding is between 250 and 300 Gy.
NATURAL REGENERATION IN MIXED PLANTING FOR ECOLOGICAL RESTORATION IN THE COASTAL PLAIN OF PARANÁ STATE, BRAZIL

Pastures occupy approximately 20% of the Brazilian territory and a significant part of these areas are degraded and have legal environmental liabilities. Ecological restoration is necessary to remedy this liability. The objective of the present study was to determine the effectiveness of a forest restoration planting in an area previously used as buffalo pasture, through floristic and phytosociological parameters of natural regeneration. The study area was densely populated by invasive exotic grasses (Urochloa spp.) until 2006, when, after eliminating the grasses, six native tree species were planted at 2.5 × 1.6 m spacing. A total of 73 terrestrial plant species were found, the most important being Alchornea glandulosa Poepp. & Endl. - heliophilous, which showed high abundance in all strata. The restoration methodology employed was effective in triggering natural succession in the study area, resulting, after 12 years, in floristic and structural parameters consistent with the initial stage of development of the alluvial Dense Ombrophylous Forest. It is inferred that the well-preserved landscape in the region has been determinant in providing the propagules and dispersers that made the observed species richness possible, while the planting tends to have contributed with the control of grasses and with the recovery of the forest environment, facilitating the arrival and development of these propagules. Evidence of soil degradation by use as pasture was observed, and in former buffalo bathing areas neither restoration planting nor natural regeneration developed.
INNOVATIVE TECHNIQUE FOR RESTORATION OF OPTICAL COHERENCE TOMOGRAPHY IMAGES AND COMPARISON WITH BM3D.

The automated processing of Optical Coherence tomography images has main difficulty of presence of noise which varies over the entire image. We first segment the OCT image into two regions, one containing different layers of eye and the other which contains only noise. The similar rows which contain only noise are considered to model the noise and then we find the local threshold value in adaptive manner. We were formulating a novel algorithm for OCT image restoration which uses a threshold derived from mean and variance of discrete wavelet coefficients in different sub bands of noisy image (segment of OCT image containing only noise). The found threshold will be different for the two segments of the image and all their sub bands. Thus this algorithm won't smooth the entire image and preserves the edge information and removes the noise. We compared our results with one of the most efficient technique BM3D.
Comparison of the Effectiveness of Spirituality Therapy and Mindfulness-Based Training in Promoting Resilience of Multiple Sclerosis Patients

Background: Chronic diseases such as multiple sclerosis (MS) can lead to hopelessness, negative emotions and thoughts, and reduced quality of life. The present study aimed to compare the effectiveness of spirituality therapy and mindfulness-based training in increasing the resilience of MS patients. Methods: The present study was a quasi-experimental study adopting a pre-test, post-test, and follow-up design with a control group. The statistical population of this study included all patients referring to the MS Association of Tehran in 2018. Using a convenience sampling method, 60 patients were selected and randomly divided into three groups. Data were collected using the Connor‐Davidson Resilience Scale (CD‐RISC) and analyzed adopting repeated measure analysis of variance. Data were analyzed by SPSS 22 software. Results: The results of repeated measure analysis of variance showed that spirituality and mindfulness-based interventions exerted effect on resilience (P≥0.008). Comparing the results also revealed that spirituality therapy had more powerful effect on resilience (P≥0.001). Conclusion: It was concluded that spirituality therapy and mindfulness-based training were both effective in promoting resilience in MS patients; however, spirituality therapy was found to be more effective in increasing the MS patients’ resilience.