Miracle-dz/UniFAR-FTUs huggingface dataset:
Metaverse and Students Engagement – Instructors' Perspective

The paper explores how metaverse helps in engaging students in virtual education in higher education institutions (HEIs). It also tries to analyze the drivers and challenges for acceptance of Metaverse in online education. The research involved in-depth-interviews of 15 respondents who were instructors in institutions in reputed cities in the USA. Teacher who had taught virtually for at least 5 years were selected through purposive sampling for this study. Interpretative Phenomenological Analysis (IPA) technique was applied for detailed analysis of the responses received from teachers. The research reveals that Metaverse could be used as an attractive immersive platform in virtual education. However, the instructors need to apply it constructively, aligning it with the course they teach and the pedagogy they apply. The research will be useful to HEIs and instructors who can design customized metaverse platforms to suit their online courses. The research will guide global companies operating in the metaverse domain to improvise their designs for a potential online education sector. The research will enhance the quality of virtual education and reduce dropout rate of students. It will make online education sector more inclusive, engaging and thereby lucrative for students. The study is original and novel in the area of online education sector. The study will be useful to policy makers in the higher education sector and government institutions in understanding the potential use of Metaverse in online education.
ANALYSIS OF NESTING MATERIALS FROM A GREAT BASIN FERRU-GINOUS HAWK NEST

A newly constructed Ferruginous Hawk (Buteo regalis ) nest was dismantled to determine the species origin, length, diameter and weight of each of the sticks of which it was constructed. Sagebrush (Artemesia tridentata) and juniper (Juniperus osteosperma ) sticks composed 75.58% and 23.26% of the total. No significant deviation existed be-tween sagebrush percent composition of the nest and that of vegetation surrounding the nest. The mean size of juniper sticks in the nest differed significantly from those on the ground in the vicinity of the nest. A possible explanation for the inclusion of rubbish in Ferruginous Hawk nests is offered.
Film antitranspirant application to enhance spring drought tolerance of oilseed rape (Brassica napus L.)

Oilseed rape (OSR) is an important crop worldwide and drought occurring during reproduction is the main limitation on yield. Following the recent problems in breeding new drought tolerant OSR varieties, there is potential for agronomic exploitation of film antitranspirant (AT) application to avoid yield losses. The main objectives of this study were i) to evaluate whether AT application during OSR r eproductive stages may sustain yield under drought; ii) to elucidate the physiological mechanisms behind the potential AT- induced yield mitigation; iii) to explore the apparent physiological inconsistency between the old and the new work on AT. In four glasshouse experiments and two field experiments drought conditions were applied at different phenological stages and OSR plants were sprayed with different AT chemicals. Three experiments were carried out on OSR seedlings in growth chambers under different atmospheric CO 2 concentration, drought conditions and sprayed or not with AT. The data showed physiological amelioration and yield loss mitigation from application of 1% v/v (glasshouse) and 1 L ha -1 (field) of a commercially -available AT (Vapor Gard) jus t prior to flowering (GS 6.0) on droughted OSR . The AT application under drought triggered complex physiological mechanisms, collectively leading to a sustained photosynthetic rate, reductions in ABA concentration, improved leaf water status and therefore sustaining pod and, to a greater extent, seed production. In addition, the data show that increasing the atmospheric CO 2 concentration does not have an ameliorative effect on OSR seedling’s drought tolerance. On the contrary, the experiments showed that in recent years the increased atmospheric CO 2 concentration may have counteracted the source- limiting effect of AT following increasing substrate available at the site of carboxylation, therefore leading to higher potential efficiency of AT chemicals under w ater -limited conditions. To conclude, AT may deserve further investigation as a potential and flexible management tool to counteract drought damage to OSR yield.
Estimation of near‐surface air temperature lapse rates over continental Spain and its mountain areas

Although the mean environmental lapse rate (MELR) value (a linear decrease of −6.5 °C/km) is the most widely used, near‐surface (i.e., non‐free atmosphere) air temperature lapse rates (NSLRs; measured at ~1.5 m height) are variable in space and time because of their dependence on topography and meteorological conditions. In this study we conducted the first analysis of the spatial and temporal variability of NSLRs for continental Spain and their relationship to synoptic atmospheric circulation (circulation weather types [CWTs]), focusing on major mountain areas including the Pyrenees, Cantabrian, Central, Baetic, and Iberian ranges.
A CAT-based early intervention for Borderline Personality Disorder: A Pilot Study

Objectives: Clinical interventions for borderline personality disorder (BPD) traditionally focused on established and chronic forms of the disorder. Increasing evidence indicates the reliability, validity, and clinical importance of the diagnosis of BPD in adolescence. This underscores a more developmental perspective to the disorder and sets the stage for prevention and early intervention. However, much is still unclear about the clinical practice of early intervention. This study aims to (a) explore a sample within an early intervention program, (b) explore how the different treatment modalities within this program were used, and (c) provide a preliminary test of general difficulties and psychosocial functioning change within young people participating in early intervention. Design: The current paper describes a pilot study of the program ‘Helping Young People Early’ (HYPE) in the Netherlands. HYPE is an early intervention program for BPD in youth based on cognitive analytic therapy (CAT), developed in Melbourne, Australia. Methods: For the current pilot study, data were used from 22 adolescents (M age = 17.3, SD age = 2.3). Subjects were offered HYPE treatment, comprising time-limited individual CAT, CAT-informed family therapy
An empirical parameterization of the subgrid-scale distribution of water vapor in the UTLS for atmospheric general circulation models

Temperature and water vapor are known to ﬂuctuate on multiple scales. In this study 27 years of airborne measurements of temperature and relative humidity from IAGOS (In-service Aircraft for a Global Observing System) are used to parameterize the distribution of water vapor in the upper troposphere and lower stratosphere (UTLS). The parameterization is designed to simulate water vapor ﬂuctuations within gridboxes of atmospheric general circulation models (AGCMs) with typical size of a few tens to a few hundreds kilometers. The distributions currently used in such models are often not supported by observations at high altitude. More sophisticated distributions are key to represent ice supersaturation, a physical phenomenon that plays a major role in the formation of natural cirrus and contrail cirrus. Here the observed distributions are ﬁtted with a beta law whose parameters are adjusted from the gridbox mean variables. More speciﬁcally the standard deviation and skewness of the distributions are expressed as empirical functions of the average temperature and speciﬁc humidity, two typical prognostic variables of AGCMs. Thus, the distribution of water vapor is fully parameterized for a use in these models. The new parameterization simulates the observed distributions with a determination coeﬃcient always greater than 0.917, with a mean value of 0.997. Moreover, the ice supersaturation fraction in a model gridbox is well simulated with a determination coeﬃcient of 0.983. The parameterization is robust to a selection of various geographical subsets of data and to gridbox sizes varying between 25 to 300 km.
The Influence Of Services, Tax Sanctions, Participation Strategies, And The Role Of Religion On Regional Taxpayer Compliance

This research investigates the factors that influence taxpayer compliance in an economic context, focusing on aspects of tax services, tax sanctions, government strategy, and religion. Through factor analysis and structural equation modeling, this research reveals five main findings: 1) Tax officer service quality has a positive and significant influence on taxpayer compliance, including aspects such as ease of payment and availability of information. 2) Tax sanctions have a positive effect on tax compliance, in line with deterrence theory and social behavior. 3) Government participation strategies may not be effective in increasing tax compliance but are still relevant as part of broader efforts. 4) Religion has a positive influence on tax compliance, supported by various theories such as social and moral values. 5) Structural equation models are used to describe the relationship between these variables and show the influence of each on tax compliance. These findings provide new insights into how governments can improve tax compliance through various approaches, and emphasize the importance of quality services and appropriate application of sanctions.
DE LA FACULTÉ DES SCIENCES Mathématiques

– We investigate wave breaking criteria for the Dullin-Gottwald-Holm equation and the two-component Dullin-Gottwald-Holm system. We establish a new blow-up criterion for the general case γ + c 0 α 2 ≥ 0 involving local-in-space conditions on the initial data.
CLINICAL REVIEW Sleep disorders and Parkinson disease; lessons from genetics

Parkinson disease is a common, age-related neurodegenerative disorder, projected to af ﬂ ict millions of individuals in the near future. Understanding its etiology and identifying clinical, genetic or biological markers for Parkinson disease onset and progression is therefore of major importance. Various sleep-related disorders are the most common group of non-motor symptoms in advanced Parkinson disease, but they can also occur during its prodromal phase. However, with the exception of REM sleep behavior disorder, it is unclear whether they are part of the early pathological process of Parkinson disease
Effect of Tuber Soaking Types and Fertilization Rates on Growth and Productivity of Potato

o address the current challenge of rising fertilizer costs and limited expansion of cultivated areas in Egypt, a field experiment was conducted for two successive seasons (2021 and 2022) to evaluate the effect of different tuber soaking techniques before planting and various rates of NPK recommended doses on potato growth and quality attributes. A split plot design with complete randomized blocks, consisting of 15 treatments; the soaking types included no soaking, soaking in normal water, and soaking in magnetized water, while the fertilization rates comprised 100% NPK of the recommended dose, fulvic acid+ 75% NPK from the recommended dose, fulvic acid+ 50% NPK of the recommended dose, biochar+ 75% NPK from the recommended dose, and biochar+ 50% NPK from the recommended dose. The results indicated that soaking tubers in magnetized water before planting yielded the highest values in terms of vegetative growth parameters, chlorophyll contents, ion percentage, potato yield, and quality. Furthermore, plants fertilized with 100% NPK of the recommended dose exhibited the maximum vegetative growth and yield. Likewise, the treatment involving fulvic acid+ 75% NPK showed the maximum values in terms of chlorophyll contents, nutrients percentage, and tuber quality. Based on these findings, it is recommended to soak tubers in magnetized water before planting and fertilize the plants with fulvic acid+ 75% NPK of the recommended dose. This approach can help reduce production costs by 25% while still achieving high potato yield and quality.
Ionospheric Ambipolar Electric Fields of Mars and Venus: Comparisons Between Theoretical Predictions and Direct Observations of the Electric Potential Drop

We test the hypothesis that their dominant driver of a planetary ambipolar electric field is the ionospheric electron pressure gradient (∇Pe). The ionospheres of Venus and Mars are mapped using Langmuir probe measurements from NASA's Pioneer Venus Orbiter (PVO) and Mars Atmosphere and Volatile EvolutioN (MAVEN) missions. We then determine the component of the ionospheric potential drop that can be explained by the electron pressure gradient drop along a simple draped field line. At Mars, this calculation is consistent with the mean potential drops measured statistically by MAVEN. However, at Venus, contrary to our current understanding, the thermal electron pressure gradient alone cannot explain Venus' strong ambipolar field. These results strongly motivate a return to Venus with a comprehensive plasmas and fields package, similar to that on MAVEN, to investigate the physics of atmospheric escape at Earth's closest analog.
On optimizing the sensor spacing for pressure measurements on wind turbine airfoils

This research article presents a robust approach to optimizing the layout of pressure sensors around an airfoil. A genetic algorithm and a sequential quadratic programming algorithm are employed to derive a sensor layout best suited to represent the expected pressure distribution and, thus, the lift force. The fact that both optimization routines converge to almost identical sensor layouts suggests that an optimum exists and is reached. By comparing against a cosine-spaced sensor layout, it is demonstrated that the underlying pressure distribution can 5 be captured more accurately with the presented layout optimization approach. Conversely, a 39-55 % reduction in the number of sensors compared to cosine spacing is achievable without loss in lift prediction accuracy. Given these benefits, an optimized sensor layout improves the data quality, reduces unnecessary equipment and saves cost in experimental setups. While the optimization routine is demonstrated based on the generic example of the IEA 15 MW reference wind turbine, it is suitable for a wide range of applications requiring pressure measurements around airfoils. 10
The Ambiguity of ‘True’ in English, German, and Chinese

Through a series of empirical studies involving native speakers of English, German, and Chinese, this paper reveals that the predicate ‘true’ is inherently ambiguous in the empirical domain. Truth statements such as “It is true that Tom is at the party” seem to be ambivalent between two readings. On the first reading, the statement means “Re-ality is such that Tom is at the party”. On the second reading, the statement means “According to what X believes, Tom is at the party”. While there appear to exist some cross-cultural differences in the interpretation of the statements, the overall findings robustly indicate that ‘true’ has multiple meanings in the realm of empirical matters.
Selﬁsh Corporations

We study how perceptions of corporate responsibility inﬂuence policy preferences and the effectiveness of corporate communication when agents have imperfect memory recall. Using a new large-scale survey of U.S. citizens on their support for corporate bailouts, we ﬁrst establish that the public demands corporations to behave better within society, a sentiment we label “big business discontent. ” Using random variation in the order of survey sections and in the exposure to animated videos, we then show that priming respondents to think about corporate responsibility lowers the support for bailouts. This ﬁnding suggests that big business discontent inﬂuences policy preferences. Furthermore, we ﬁnd that messages which paint a positive picture of corporate responsibility can “backﬁre,” as doing so brings attention to an aspect on which the public has negative views. In contrast, reframing corporate bailouts in terms of economic tradeoffs increases support for the policy. We develop a memory-based model of decision-making and communication to rationalize these ﬁndings.
Hybrid-Segmentor: A Hybrid Approach to Automated Damage Detection on Civil Infrastructure

Detecting and segmenting cracks in infrastructure, such as roads and buildings, is crucial for safety and cost-eﬀective maintenance. In spite of the potential of deep learning, there are challenges in achieving precise results and handling diverse crack types. With the proposed dataset and model, we aim to enhance crack detection and infrastructure maintenance. This study proposes a novel approach termed Hybrid-Segmentor, which uses a convolutional neural network path that is well-suited for extracting ﬁne-grained local features and a transformer path to extract global features that beneﬁt from understanding the overall structure. This hybrid method makes the model more generalizable to various shapes, surfaces, and sizes of cracks. To achieve a balanced computational cost, the study incorporates eﬃcient self-attention in the transformer path and introduces a comparatively simpler decoder compared to the complexity of the two encoder paths. This combination strategically optimizes the extraction of global and local features while maintaining computational eﬃciency. The model was trained using a combined binary cross entropy and Dice loss function on a large reﬁned dataset of 12,000 crack images generated from 13 publicly available datasets. Our studies demonstrate that the model eﬃciently utilizes convolutional layers and transformers to extract local and global features. Hybrid-Segmentor outperforms existing benchmark models across 5 quantitative metrics (accuracy 0.971, precision 0.804, recall 0.744, F1-score 0.770, and IoU score 0.630), achieving state-of-the-art status. Finally, through careful qualitative analysis, we show that the model is capable of addressing discontinuities, detecting small non-crack regions, handling low-quality images, and detecting crack contours more accurately than existing models.
Spatial appraisal of groundwater quality for drinking purposes: A case study of Kalihati Upazila, Bangladesh

With the aim of improving public health interventions, this study was conducted to ensure sustainable groundwater quality by adopting Geographical Information System (GIS) and Water Quality Index (WQI) for drinking purposes in Paikara Union, Kalihati Upazila of Bangladesh. Fifteen groundwater samples were randomly collected from different hand tubewells in April 2019 and analyzed for pH, electrical conductivity (EC), total dissolved solids (TDS), total hardness (TH), major cations and anions. Almost all physicochemical parameters fell within the acceptable limit of national and international standards, though a few samples exceeded the standard limit considering As +3 , Fe +3 and PO 3–4 concentrations. The spatial distribution of the quality parameters across the study area was depicted employing ArcGIS 10.5 software; therein it was revealed that slightly acidic water is dominant in the central and southern parts. Overall, TH–total cation, Cl–NO 3 , total anion–NO 3 and total anion–Cl show a very strong correlation, and contrarily, the pairs of pH, EC, TDS are poorly correlated with most of the variables and no remarkable relationship is found between pH and TH. Furthermore, WQI of the samples ranged from 20.42 to 143.36, with 73.7, 24.1, and 2.2% of the entire study area falling under excellent, good, and poor quality categories for drinking purposes, respectively. From the results, it can be inferred that the groundwater of the study area is suitable for drinking purposes but awareness-raising on chemical contents in the water at the household level is recommended.
A Comparison of Neural-Network-Based Intrusion Detection against Signature-Based Detection in IoT Networks

Over the last few years, a plethora of papers presenting machine-learning-based approaches for intrusion detection have been published. However, the majority of those papers do not compare their results with a proper baseline of a signature-based intrusion detection system, thus violating good machine learning practices. In order to evaluate the pros and cons of the machine-learning-based approach, we replicated a research study that uses a deep neural network model for intrusion detection. The results of our replicated research study expose several systematic problems with the used datasets and evaluation methods. In our experiments, a signature-based intrusion detection system with a minimal setup was able to outperform the tested model even under small traffic changes. Testing the replicated neural network on a new dataset recorded in the same environment with the same attacks using the same tools showed that the accuracy of the neural network dropped to 54%. Furthermore, the often-claimed advantage of being able to detect zero-day attacks could not be seen in our experiments.
Apgar scores in puppies following the induction of etomidate compared with alfaxalone or propofol for cesarean section

Background and Aim: The Apgar score is a useful assessment of neonatal viability in dogs. The Apgar score in puppies born by cesarean section can be lower than vaginal delivery because all anesthetic drugs can cross the placenta. Therefore, anesthetic drugs with minimal cardiorespiratory effect and rapid elimination are recommended for cesarean section. The present study aimed to compare Apgar scores in puppies born after the induction of etomidate, alfaxalone or propofol, and those maintained with isoflurane inhalation during cesarean section. Materials and Methods: Thirty-six bitches were equally divided in the three anesthetic drug groups. Modified Apgar scores were assessed at 5, 15, and 60 min after delivery. Intraoperative vital signs and Apgar scores were compared using a linear mixed model and adjusted pairwise comparisons using Bonferroni analysis. Results: A total of 125 puppies were included in this study. Age, body weight, litter size, type of surgery, delivery time, anesthetic and surgical duration, and intraoperative vital signs did not significantly differ between the groups. Puppies in the alfaxalone and propofol groups had significantly higher Apgar scores than the etomidate group in both elective and emergency surgery. In elective surgery, Apgar scores at 5 min after delivery did not differ significantly between groups. At 15 and 60 min after delivery, Apgar scores in the etomidate group were significantly lower than those in the other groups. In emergency surgery, Apgar scores were significantly lower in the etomidate group than in the alfaxalone group at all time points. Conclusion: Induction with alfaxalone and propofol resulted in better outcomes with higher Apgar scores and neonatal viability than etomidate. Therefore, alfaxalone and propofol should be used as anesthetic induction drugs in both elective and emergency cesarean sections. Keywords: anesthesia, Apgar, puppies, viability, vigorous.
A Cross-sectional Study

Results: Fusobacterium necrophorum was detected in 20.5% of patients and 9.4% of asymptomatic students. Group A -hemolytic streptococcus was detected in 10.3% of patients and 1.1% of asymptomatic students. Group C/G -hemolytic streptococcus was detected in 9.0% of patients and 3.9% of asymptomatic students. Mycoplasma pneumoniae was detected in 1.9% of patients and 0 asymptomatic students. Infection rates with F. necrophorum, group A streptococcus, and group C/G streptococcus increased with higher Centor scores (P < 0.001).