Miracle-dz/UniFAR-FTUs huggingface dataset:
A unifying theory of jet screech

Abstract This paper describes the mechanism underpinning modal staging behaviour in screeching jets. An upstream-propagating subsonic guided-jet mode is shown to be active in all stages of screech. Axial variation of shock-cell spacing manifests in the spectral domain as a series of suboptimal peaks. It is demonstrated that the guided-jet mode may be energized by interactions of the Kelvin–Helmholtz wavepacket with not only the primary shock wavenumber peak, but also suboptimal peaks; interaction with suboptimals is shown to be responsible for closing the resonance loop in multiple stages of jet screech. A consideration of the full spectral representation of the shocks reconciles several of the classical models and results for jet screech that had heretofore been paradoxical. It is demonstrated that there are multiple standing waves present in the near field of screeching jets, corresponding to the superposition of the various waves active in these jets. Multimodal behaviour is explored for jets in a range of conditions, demonstrating that multiple peaks in the frequency spectra can be due to either changes in which peak of the shock spectra the Kelvin–Helmholtz wavepacket is interacting with, or a change in azimuthal mode, or both. The absence of modal staging in high-aspect-ratio non-axisymmetric jets is also explained in the context of the aforementioned mechanism. The paper closes with a new proposed theory for frequency selection in screeching jets, based on the observation that these triadic interactions appear to underpin selection of the guided-jet mode wavelength in all measured cases.
Using Fuzzy Clustering with Deep Learning Models for Detection of COVID-19 Disinformation

Since the beginning of 2020, the COVID-19 pandemic has killed millions of people around the world, leading to a worldwide panic that has fueled the rapid and widespread dissemination of COVID-19-related disinformation on social media. The phenomenon, described by the World Health Organization (WHO) as an "indodemic" presents a serious challenge to governments and public health authorities, but the spread of misinformation has made human detection less efficient than the rate of spread. While there have been many studies developing automated detection techniques for COVID-19 fake news, the results often refer to high accuracy but rarely to model detection time. This research uses fuzzy theory to extract features and uses multiple deep learning model frameworks to detect Chinese and English COVID-19 misinformation. With the reduction of text features, the detection time of the model is significantly reduced, and the model accuracy does not drop excessively. This study designs two different feature extraction methods based on fuzzy classification and compares the results with different deep learning models. BiLSTM was found to provide the best detection results for COVID-19 misinformation by directly using deep learning models, with 99% accuracy in English and 86% accuracy in Chinese. Applying fuzzy clustering to English COVID-19 fake news data features maintains 99% accuracy while reducing detection time by 10%. For Chinese misinformation, detection time is reduced by 15% at the cost of an 8% drop in accuracy.
Performance index improvement of a double-pipe cooler with MgO/water-ethylene glycol (50:50) nano-suspension

A series of tests was conducted to unlock the potential application of MgO/water-EG (ethylene glycol) nano ﬂ uids (NF) in a double-pipe heat exchanger (HEX). The overall heat transfer coef ﬁ cient (HTC), the inlet temperature of the working ﬂ uid, the ﬂ uid pressure drop (FPD), friction factor (FF) and the hydraulic performance index of the NF within the HEX were experimentally measured. Fouling of nanoparticles (NPs) within the Hex was also studied and modelled using asymptotic particulate fouling model. Results showed that MgO NPs can enhance the HTC by 39% at Re Z 10,500 and wt. % Z 0.3 in the turbulent regime. Also, the presence of MgO NPs augmented the FF and the FPD values. The former was enhanced 33.8%, while the latter was augmented by 37% both at wt. % Z 0.3 and at Reynolds number Z 10,500. Results also revealed that the formation of porous particulate fouling layer on the internal wall of the inner tube creates a fouling thermal resistance which changes asymp-totically with time. Overall, MgO/water-ethylene glycol shows a great potential to be used as a coolant within a HEX.
Incorporation of Data-Mined Knowledge into Black-Box SVM for Interpretability

The lack of interpretability often makes black-box models challenging to be applied in many practical domains. For this reason, the current work, from the black-box model input port, proposes to incorporate data-mined knowledge into the black-box soft-margin SVM model to enhance accuracy and interpretability. The concept and incorporation mechanism of data-mined knowledge are successively developed, based on which a partially interpretable soft-margin SVM (pTsm-SVM) optimization model is designed and then solved through reformulating the optimization problem as standard quadratic programming. An algorithm for mining linear positive (negative) class knowledge from general data sets is also proposed, which generates a linear two-dimensional discriminative rule with specificity (sensitivity) equal to 1 and the highest possible sensitivity (specificity) among all two-dimensional feature spaces. The knowledge-integrated pTsm-SVM works by achieving a good trade-off among the “large margin”, “high specificity”, and “high sensitivity”. Our experimental results on eight UCI datasets demonstrate the superiority of the proposed pTsm-SVM over the standard soft-margin SVM both in terms of accuracy and interpretability.
A Modified U-Net Architecture for Road Surfaces Cracks Detection

Cracks on road surfaces causes inconveniences to drivers and passengers and may cause mechanical failure or even accidents. Good Road condition plays an important role in quick transportation of goods and services from one place to another and acts as a catalyst for the economic development. Road surfaces need to be maintained in good condition to ensure the safety of road users. Road damage detection is important for Structural Health Monitoring (SHM). Traditional manual inspection is normally performed through human visualization which is time consuming, expensive, dangerous because of the passing vehicles, suffers from subjective judgment of the inspector and pose difficulties in keeping records for future road maintenance and repair. The rapid emergency and development of AI has stimulated many experts to automate the process of crack detection through computer vision (CV) technology, though most of these studies faces challenge on getting good detection accuracy. In this study a novel modified U-Net Architecture for image classification and segmentation is proposed to detect cracks on the road surfaces by using detection and classification of the road images to determine whether they represent cracks or not. Extensive experiments are conducted on three publicly available road crack datasets to evaluate the performance of our proposed model, The performance of the proposed Modified U-Net architecture was verified with respect to different performance metrics such as accuracy, precision, recall and f1 score. Qualitative and Quantitative comparisons experimental results of the proposed approach were also compared with existing state of the art U-Net architectures. It can be inferred from results that the proposed approach achieves superior performance in terms of detection accuracy.
Blockchain Stretching & Squeezing: Manipulating Time for Your Best Interest

We present a novel way for cryptocurrency miners to manipulate the effective interest-rate on loans or deposits they make on decentralized finance (DeFi) platforms by manipulating difficulty-adjustment algorithms (DAAs) and changing the block-rate. This presents a new class of strategic manipulations available to miners. These manipulations allow miners to stretch and squeeze the time between consecutive blocks. We analyze these manipulations both analytically and empirically, and show that a 25% miner can stretch the time between consecutive blocks by up to 54% in Ethereum and 33% in Bitcoin, and squeeze it by up to 9% in Ethereum. Ethereum is particularly vulnerable, and even relatively small miners can seriously affect the block-rate. An interesting application of these manipulations is to create an artificial interest-rate gap between loans taken from one DeFi platform which accrues interest according to block height (such as Compound [66]) and deposited in some other platform that does so according to elapsed time (like a bank, or other DeFi platforms such as Aave [99]). Hence, stretching and squeezing the block-rate can decrease the interest paid on DeFi loans relative to external financial platforms. The profit made from this interest-rate gap provides a large incentive for miners to deviate. For example, a 25% Ethereum miner using our manipulations can increase mining profits by up to 35%, even after taking potential losses into consideration, such as less block-rewards. Our analysis of these manipulations and their mitigations has broad implications with regards to commonly-used cryptocurrency mechanisms and paradigms, such as Ethereum's difficulty-adjustment algorithm and reward schemes, with Ethereum's handling of uncle blocks being particularly manipulable. Interestingly, Bitcoin's mechanism is more resistant Ethereum's, owing to its larger incentives and a more resilient DAA.
Quantitative contribution of the Grain for Green Program to vegetation greening and its spatiotemporal variation across the Chinese Loess Plateau

A distinct greening trend is evident in Asia, especially on the Loess Plateau (LP) of China, which is driven by climate change and large‐scale land‐use‐related ecological projects, especially the 'Grain for Green Program' (GFGP). However, the specific contributions of the GFGP to vegetation greening and the variation of this greening on a large spatiotemporal scale are not yet clear. We used long‐time‐series normalized difference vegetation index datasets and climate datasets based on the double mass curve method to quantify the contributions of ecological projects and climate change to the greening trend on the LP. We found that the interannual fluctuation of vegetation change was likely related to the interannual fluctuation of climate, especially precipitation. The increasing trend of vegetation change after 2005 indicated that the GFGP, as a type of external disturbance, began to improve vegetation growth. The GFGP failed initially to make a positive contribution in the first few years because of the drought conditions in 1999 and 2005. The increased precipitation played a critical role in enhancing the output of the GFGP on the LP after 2005. Then, the contribution of the GFGP increased quickly until 2013, after which it remained stable and reached average values of 58.8% ± 19.34% and 31.7% ± 24.3% in the representative areas that conducted the GFGP and in other regions with a lower implementation intensity of the GFGP, respectively. Our results highlight the contribution the GFGP has made to spatiotemporal variation due to the spatial heterogeneity of the projects, their intensity and the effect of forest stand age.
A Numerical Investigation of the Effect of Wave‐Induced Mixing on Tropical Cyclones Using a Coupled Ocean‐Atmosphere‐Wave Model

Ocean surface waves play a significant role in regulating the sea surface temperature and mixed layer depth, which are essential for accurate prediction of tropical cyclone (TC) intensity. The effects of wave breaking and wave orbital motion induced mixing on the TC intensity and size are investigated using a coupled ocean‐atmosphere‐wave model for both idealized and real TC cases. The results show that both wave breaking and wave orbital motion lead to greater sea surface temperature cooling and mixed layer deepening, resulting in decreases in TC intensity and size owing to the reduction of air‐sea heat fluxes. Wave orbital motion has a slightly greater effect than wave breaking on the TC intensity and size when the mixed layer is shallow, whereas it has a much greater effect when the mixed layer is deep. In addition, including wave orbital motion induced mixing in models can effectively reduce the error in simulated TC size.
Mortality management and climate action: A review and reference for using Terror Management Theory methods in interdisciplinary environmental research

Global climate change awareness is increasing, but efforts to convey information can trigger undesirable behaviors, including denial, skepticism, and increased resource consumption. It is therefore essential to more fully investigate social–psychological responses to climate information and messaging if we are to prompt, support, and sustain pro‐environmental behaviors. Yet consideration of these responses is typically absent from interdisciplinary environmental study designs. Of specific relevance is research using social psychology's Terror Management Theory (TMT) showing that people's efforts to repress mortality salience (MS) or awareness significantly influence their attitudes, beliefs, and behaviors. Research on MS's influence on climate change beliefs is progressing but, to date, a systematic scoping review of the literature has been unavailable. Here, we provide such a review. We propose that TMT insights and methods should be better integrated into research designs to guide climate communications and to generate the comprehensive cultural and behavioral changes needed to address societies' climate problems. We introduce a methodological framework for interdisciplinary researchers to incorporate TMT into their research designs and to help practitioners anticipate how their mortality‐laden messaging could trigger unintentional social‐psychological responses that degrade climate communication strategies.
The transition from dislocation creep to frictional failure in carbonate fault zones: 1 Schmid factor analysis of marbles within the Karakoram Fault Zone,

11 The onset of frictional failure and potentially seismogenic deformation in carbonate 12 rocks undergoing exhumation within fault zones depends on hardening processes that reduce 13 the efficiency of aseismic dislocation creep as temperature decreases. However, few techniques 14 are available for quantitative analysis of dislocation slip system activity and hardening in 15 natural tectonites. Electron backscatter diffraction maps of crystal orientations offer one such 16 approach via determination of Schmid factors, if the palaeostress conditions can be inferred 17 and the critical resolved shear stresses of slip systems are constrained. We analyse calcite 18 marbles deformed in simple shear within the Karakoram Fault Zone, NW India, to quantify 19 changes in slip system activity as the rocks cooled during exhumation. Microstructural 20 evidence demonstrates that between ~300°C and 200–250°C the dominant deformation 21 mechanisms transitioned from dislocation creep to twinning and frictional failure. However, 22
Original Article

Maryam Ashjaran 1, Mirzaagha Babazadeh1, Abolfazl Akbarzadeh 2,3, Soodabeh Davaran4, Roya Salehi 4 Background: Today, increasing attention is being paid to the application of biocompatible polymers as drug carriers with low cytotoxicity in drug delivery systems to enhance the therapeutic effects of anticancer agents. Materials and Methods: In this study, a biocompatible synthetic polymer (grafted on graphene oxide), composed of N-isopropylacrylamide and 1-vinyl2-pyrrolidone with L-lysine segments (Lys/PNIPAM-PVP/GO), was developed as a nano-vehicle for the drug. This platform was used for the delivery of fluorouracil (FU) to A549 human lung cancer cells. The superior characteristics of the platform included low-cost precursors, easy synthesis, and the presence of many functional groups for loading drugs. To determine and compare the cytotoxic effects of free FU and its formulated form on the A549 cells, MTT assay was performed; the results showed no significant toxicity difference between the two treated groups (free and formulated FU). For further evaluations, cellular uptake assays were performed via fluorescence microscopy and flow cytometry. Results: Both analyses revealed the low internalization of nano-vehicle into the A549 cells, with 4.31% and 8.75% cellular uptakes in the first two and four hours of treatment. Therefore, the low penetration rate reduced the toxicity of drug-loaded nano-vehicle. Conclusion: Finally, DAPI staining and Annexin V-FITC staining were performed as complementary techniques to determine cell apoptosis.
InfectionResistant to Depletion Early During Virus Cutting Edge: T Cells from Aged Mice Are

Aging is associated with decreased expansion of T cells upon stimulation. In young mice, infection induces a transient T cell depletion followed by the development of an Ag-specific T cell response that controls the infection. We found that T cells were depleted early after infection with E55 (cid:1) murine leukemia retrovirus in young, but not aged, mice. Adoptive transfer experiments showed donor T cells of young, but not aged, mice were depleted due to apoptosis in various tissues of young recipients. However, T cells of neither young nor aged donors were depleted in aged recipients. These results indicate that both environmental and intrinsic cellular properties limit depletion of T cells of aged mice and suggest a novel explanation for the decreased T cell response associated with aging. The Journal of Immunology, 2003, 171: 3353–3357.
Comparison of phenotypic characterization, productive and reproductive performance of pure black bengal and crossbred goat

The study was conducted between Pure Black Bengal (PBB) and crossbred (CBB) goat to compare the phenotypic features, morphometry, production and reproduction performance. A total number of 87 goats from which 26 PBB goats from Government Goat Development Sub center, Jhenidah and 61 CBB goats from Alamdanga Upazila and Jhenidah Sadar Upazila were collected for this study from November 2019 to January 2020. Prominent coat color was black in both PBB and CBB but in case of 55.74% CBB has long hair in its hind quarter but it was totally absent in PBB. The average value of morphometric measurements was compared between sex and age. The result indicated that, the height of wither and rump, length of horn, ear, head and scrotum were higher (p<0.05) in CBB (77.57, 75.03, 12.17, 23.16, 22.33 and 12.98cm, respectively) than PBB buck (58.93, 61.47, 10.97, 13.00, 17.78 and 9.86cm, respectively). The measurement between the does indicated that the horn length was higher (P<0.001) in PBB doe but ear length was higher (p<0.01) in CBB than PBB. In case of kids, height of wither, heart girth and ear length was higher (p<0.01) in CBB (36.9, 31.39 and12.7cm, respectively) than PBB (30.48, 24.77 and 7.8cm, respectively). The average milk production of PBB (390.44 ml/day) was significantly (p<0.01) lower than CBB (1045.01 ml/day) but the litter size was significantly (p<0.05) higher in PBB (2.30) than CBB (1.77). The age of puberty, age of first kidding and kidding interval were better (P<0.01) in PBB (205.30, 355.5 and 200.30 days, respectively) than CBB (275.92, 401.5and 273.77 days, respectively). The study revealed that the morphologic and morphometric characteristics were higher in CBB and quiet altered from PBB due to indiscriminate cross breeding and the reproductive performance were better in PBB in comparison with CBB. These data may help in identifying current status of Black Bengal goat and contribute to in situ conservation of the breed.
DENSITY ON THE

by REiNEKE's model, FUrthermore, the dependenee of individual DBH upon troe demsity was formu- lated frem a function of tree density. In cQnclusion, A normalint density function of DBH yielded a statistical basis to RiiiNEKE's model.
Universality in the Photophysics of pi-Conjugated Polymers and Single-Walled Carbon Nanotubes

We describe both pi-conjugated polymers and semiconducting single-walled carbon nanotubes because of the remarkable similarities in their behavior under photoexcitation. The common themes between these two seemingly different classes of materials are pi-conjugation, quasi one-dimensionality, and strong Coulomb interactions. Theoretical understanding of both systems requires going beyond traditional band theory. We present our current understanding of the electronic structures and excited state absorptions in both systems within a common theoretical model. Our aim is to give physical interpretations of experiments that have been performed and to give guidance to future experimental work.
Identifying Coping Mechanisms of Exam Anxiety as Innovative Technique to Prepare Malaysian Secondary School Students for Examination

The study aims to determine the level of exam anxiety and the coping mechanisms used by the students, and also the relationship between the two variables. This is due to the fact that highly suitable and effective exam anxiety coping mechanisms are believed to be able to help the students in overcoming their anxiety. The study used the survey method in order to find out the anxiety level and the coping mechanisms used by the students in handling exam anxiety. 324 Form Four students from a daily secondary school (152 male, 172 female) were selected as the study sample. The instruments utilized in the study were the questionnaires of Test Anxiety Inventory, also known as TAI Inventory, and Coping with Pre-Exam Anxiety and Uncertainty (COPEAU). The results indicated that the exam anxiety level of the students was moderate. Also, there is a significant difference level of exam anxiety and the coping mechanisms based on genders, in which the mean value for female students is much higher than that of male students. From the aspect of coping mechanisms, it was found that a large number of the secondary school students used the task-orientation and preparation and also seeking social support as the mechanisms in handling anxiety, while only a few of them used the avoidance mechanism. The implication of preparing the students prior to the examination was discuss.
MAXIMUM FLOW OF RIVERS OF THE UKRAINIAN CARPATHIANS (IN THE UPPER DNIESTER) IN THE CLIMATE CHANGE CONDITIONS

The complex nature of the flow of the Carpathian Mountains necessitates the identification of current trends in the changes in the maximum flow with different genesis (spring flood and rainwater floods). The studies were carried out over a period of the years (1961-2010) and various phases of water content. Statistically significant trends were identified by the Mann-Kendall test. It was found the statistically significant positive trends in air temperatures are generated during the summer season. The trend of maximum flow is offset in time from the calculated "winter" interval (1961-1981) to the calculated interval of "early snow melt flood" (1982-2010). Since 1989, a statistically significant increase in the maximum flow has been detected in the intervals of "late snow melt flood" and "spring floods". These shifts in time are due to changes in precipitation. The impact of rainfall on the generation of maximum flow is growing.