Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of Acute Low-Dose Gamma Irradiation on Biomass Accumulation and Secondary Metabolites Production in Cotinus coggygria Scop. and Fragaria × ananassa Duch. Red Callus Cultures

Cotinus coggygria Scop. (smoketree) and Fragaria × ananassa Duch. (strawberry) are two industrially important species due to their composition in bioactive compounds. In this study, we investigated the effects of acute low-dose gamma irradiation (15, 20, 25, 30, 35 and 40 Gy) on two red callus cultures established in smoketree and strawberry. The biomass production, dry weight, content of phenols, flavonoids, monomeric anthocyanins’, index of anthocyanins polymerization and antioxidant activity were evaluated. For the smoketree callus, a negative correlation between irradiation doses and callus biomass accumulation was observed. For the strawberry callus, irradiation did not significantly affect the accumulation of the biomass. An increased dry weight was observed in irradiated smoketree callus, while for treated strawberry callus, a decrease was recorded. Irradiation with 30 Gy was stimulative for polyphenols’ accumulation in both cultures; however, the increase was significant only in the strawberry callus. The flavonoids increased in the 30 Gy strawberry variants, while it significantly decreased in smoketree callus irradiated with 35 and 40 Gy. In irradiated strawberry callus, except for the 25 Gy variant (1.65 ± 0.4 mg C-3-GE/g DW), all treatments caused an increase in anthocyanins’ accumulation. In smoketree, except for the 15 Gy variant (2.14 ± 0.66 mg C-3-GE/g DW), the irradiation determined an increase in anthocyanins synthesis, with the highest value being seen in the 20 Gy variant (2.8 ± 0.94 mg C-3-GE/g DW). According to UPLC-HRMS investigations, an unidentified compound increased by 99% at the 30 Gy dose in strawberry callus, while in smoketree, maslinic acid increased by 51% after irradiation with 40 Gy. The results of this study showed, for the first time, the differential response of two performant callus cultures to low-dose gamma irradiation, a biotechnological method that can be used to stimulate the synthesis of important flavonoids and triterpenes.
Development process for preliminary aircraft sizing methods with regard to new technologies

Purpose The purpose of this study is to develop and describe a process which can be applied to develop new methods in the context of preliminary aircraft sizing in a successful and efficient way. Design/methodology/approach The tasks to development new aircraft sizing methods are systematically analyzed. In particular, repeating and nonrepeating tasks and common or unique tasks. Then ordered in a sequence and described generically. Findings A development process for new aircraft design methods which are necessary for new technologies or configurations is introduced and explained step by step. Practical implications Introducing the capability to deal with new technologies or configurations, aircraft design tools or aircraft concepts requires new sizing methods. Originality/value The paper presents a systematic approach which can be used to develop a great amount of new sizing methods with a comparable usability and quality standard in an efficient and effective way.
Automatic Evaluation of Instructional Videos Based on Video Features and Student Watching Experience

Instructional videos are often a key component of online learning, and their quality significantly influences online learning outcomes and student satisfaction. However, instructional video evaluation is time-consuming. To solve this problem, this study developed an automatic evaluation method for instructional videos. This method first establishes a metric to evaluate instructional videos based on two aspects: video features and watching experience. An automatic scoring method for each indicator was developed based on video and clickstream data. Finally, all the scores were input into the evaluation model to obtain the evaluation result. Our experimental results showed that 85% of the evaluation results using our proposed model are consistent with manual quality evaluation. Therefore, our method can perform automatic evaluation of instructional videos while achieving acceptable accuracy, which is helpful in reducing the workload associated with manual evaluation and improving the quality of online teaching.
Hypothyroidism Among College Students and Its Association With Academic Performance: A Cross-Sectional Study

Background: Little is known about the impact of hypothyroidism and its contribution to learning difficulties and academic performance in college-age students. Objective: The objective is toassess the frequency of hypothyroidism and its associations with academic performance in college-age students. Methods: A cross-sectional study included 395 students studying across various Jeddah universities and selected by non-probability convenient sampling. Students self-answered the survey using Google Forms. The survey included demographic data, thyroid data, academic achievement as measured by overall grade point average (GPA), and student persistence as measured by academic failure and delay. Results: Three hundred ninety-five students were included, their median age was 23 years (17-33), 96 were males (24.3%) and 299 were females (75.7%). Their median GPA was 4 (2.76-4). Thirty-two students (8.1%) had been treated for hypothyroidism and eight students (25.8%) were non-compliant with therapy. Odds of hypothyroidism increased among females (OR 3.33, 95% CI: 0.99-10.78, p=0.048), older age (OR 2.60, 95% CI: 1.33-5.77, p=0.009), those with a positive family history of thyroid illnesses (OR 5.49, 95% CI: 2.30-13.07, p<0.001), and those with academic failure (OR 3.31, 95% CI: 1.43-7.30, p=0.003) and academic delay (OR 2.83, 95% CI: 1.14-7.05, p=0.020). There was no significant association between hypothyroidism and GPA (OR 2.42, 95% CI: 0.83-7.77, P=0.092). Conclusion: Hypothyroidism was prevalent among college students (8%), especially among older females. Hypothyroidism was associated with difficult student persistence, but this association did not reflect on their overall academic achievement. Incompliance with thyroid replacement therapy may be a common issue among hypothyroid patients. Further studies should focus on specific tests of the cognitive function of different learning domains and the role of treatment.
Microstructural Dynamics and Rheology of Suspensions of Rigid Fibers

The dynamics and rheology of suspensions of rigid, non-Brownian fibers in Newtonian fluids are reviewed. Experiments, theories, and computer simulations are considered, with an emphasis on suspensions at semidilute and concentrated conditions. In these suspensions, interactions between the particles strongly influence the microstructure and rheological properties of the suspension. The interactions can arise from hydrodynamic disturbances, giving multibody interactions at long ranges and pairwise lubrication forces over short distances. For concentrated suspensions, additional interactions due to excluded volume (contacts) and adhesive forces are addressed. The relative importance of the various interactions as a function of fiber concentration is assessed.
Quadratically Constrained Quadratic Optimal Problem in Robust Relay Networks

The paper investigates the problem of a distributed robust relay beamforming in one-way relay networks with imperfect channel state information. The aim is to maximize the SNR (signal-to-noise ratio) of the receiver with the constraint of the total transmits power of relays is less than a certain predefined threshold. Because the channel is imperfect and the objective function is fractional quadratic form, the optimal problem is a non-convex problem which is hard to be solved. We first change the fractional problem into a non-fractional one. Second, we consider the semi-definite programming (SDP) method efficiently by exploiting S-procedure theorem and relaxing the rank-one constrain to obtain the robust beamforming vector. The paper gives the schematic total algorithm too. Numerical results show that the proposed algorithm can solve the maximum problem with robust features efficiently and obtain satisfactory results.
Multimodal object description network for dense captioning

A new multimodal object description network (MODN) model for dense captioning is proposed. The proposed model is constructed by using a vision module and a language module. As for vision module, the modified faster regions-convolution neural network (R-CNN) is used to detect the salient objects and extract their inherited features. The language module combines the semantics features with the object features obtained from the vision module and calculate the probability distribution of each word in the sentence. Compared with existing methods, a multimodal layer in the proposed MODN framework is adopted which can effectively extract discriminant information from both object and semantic features. Moreover, MODN can generate object description rapidly without external region proposal. The effectiveness of MODN on the famous VOC2007 dataset and Visual Genome dataset is verified.
Discovery and Analyses of Caulimovirid-like Sequences in Upland Cotton (Gossypium hirsutum)

Analyses of Illumina-based high-throughput sequencing data generated during characterization of the cotton leafroll dwarf virus population in Mississippi (2020–2022) consistently yielded contigs varying in size (most frequently from 4 to 7 kb) with identical nucleotide content and sharing similarities with reverse transcriptases (RTases) encoded by extant plant pararetroviruses (family Caulimoviridiae). Initial data prompted an in-depth study involving molecular and bioinformatic approaches to characterize the nature and origins of these caulimovirid-like sequences. As a result, here, we report on endogenous viral elements (EVEs) related to extant members of the family Caulimoviridae, integrated into a genome of upland cotton (Gossypium hirsutum), for which we propose the provisional name “endogenous cotton pararetroviral elements” (eCPRVE). Our investigations pinpointed a ~15 kbp-long locus on the A04 chromosome consisting of head-to-head orientated tandem copies located on positive- and negative-sense DNA strands (eCPRVE+ and eCPRVE-). Sequences of the eCPRVE+ comprised nearly complete and slightly decayed genome information, including ORFs coding for the viral movement protein (MP), coat protein (CP), RTase, and transactivator/viroplasm protein (TA). Phylogenetic analyses of major viral proteins suggest that the eCPRVE+ may have been initially derived from a genome of a cognate virus belonging to a putative new genus within the family. Unexpectedly, an identical 15 kb-long locus composed of two eCPRVE copies was also detected in a newly recognized species G. ekmanianum, shedding some light on the relatively recent evolution within the cotton family.
Function mining for the $ $-N$_{ch}$ correlations in pp and pp(bar) collisions based on symbolic regression

The investigation and analysis of the correlation between the mean transverse momentum (< PT >) of charged particles and the charged particle multiplicity (Nch) allow physicists to understand the contribution of multipleparton interactions to the particle production mechanism. A symbolic regression (SR) method, based on gene expression programming (GEP), is proposed for mining a function that describes the < PT > -Nch correlation in proton–proton and proton–antiproton (pp and pp(bar)) collisions at collision energies from IRS to LHC. The discovered function simulates and models the correlation between < PT > and Nch in wide energy range s 1/2 . In the framework of the proposed GEP model for < PT > −Nch correlation, the equation obtained describes the main features of the experimental data. Predictions for < PT > −Nch correlations at the future LHC collision energy of 14 TeV are obtained. The accuracy of the calculated and predicted results is assessed by comparing them with the available experimental data and the theoretical ones.
Design and Analysis of Rectangular Microstrip Array Antenna at Ka Band Becon Frequency 20.2GHz

The design and analysis of single double (1×2) and four (1×4) element linear rectangular micro strip array antennas is done to achieve high gain and directivity. The operating frequency of the proposed array antenna is Ka-band, 20.2GHz which is a Beacon frequency of GSAT-14 launched by ISRO.The substrate material used is common for the single, double (1×2) and four (1×4) i.e. FR4 with a thickness of 0.8mm and the dielectric constant is 4.4. The antenna elements are placed uniform at a same distance. The feeding network used here is a parallel or corporate feed network. The power splitting and impedance matching is done using RF Wilkinson power divider. The entire proposed micro strip phased array antenna is evaluated using HFSS software tool.
Facilitating factors encouraging girl learners to choose science, technology, engineering, and mathematical subjects and related careers:

In recent years, there has been a drive to recruit more women into science, technology, engineering, and mathematics (STEM) careers. However, a perceived lack of interest by girl learners in STEM subjects and careers presents a challenge. Therefore, the purpose of this study was to investigate the reasons that encourage high school girls to choose STEM subjects and careers. A qualitative design that adopted the case study approach using the interpretivist paradigm was chosen for this study. The data were collected using a focus group with a novel sample of girls taking technical subjects at a technical high school in a rural area. The study identified four facilitating factors that steer girl learners towards choosing STEM subjects and STEM-related careers. These factors were primary school experience, parental influence, prosperity through employment and entrepreneurial opportunities, breaking stereotypes, and being a role model. The insights gained from this study could be beneficial to the government, businesses, social activists, schools, teachers, and other relevant stakeholders in encouraging girl learners to choose STEM-related and related careers.
A Bayesian approach to the one way ANOVA under unequal variance

This study involves testing the equality of several normal means under unequal variances, which is the setup of one-way analysis of variances (one-way ANOVA). Several tests are available in the literature, however, most of them perform poorly in terms of type I error rate under unequal variances. In fact, Type I errors can be highly inflated for some of the commonly used tests, a serious issue that seems to have been overlooked. Even though several tests have been proposed to overcome the problem, most of them show difficulty in calculation. Accordingly, the test for ANOVA with estimation of parameters using Bayesian approach is proposed as an alternative to such tests. The proposed test is compared with four existing tests such as the original test, James’s test, Welch’s test and the parametric bootstrap (PB) test. Type I error rates and powers of the tests are evaluated using Monte Carlo simulation. Our results indicated that the performance of the proposed test is superior to the original test and is comparable to James’s test, Welch’s test and the PB test, controlling Type I error rate quite well and showing high power of the test. Our study suggested that the proposed test has high performance and should be used as an alternative to the four existing tests due to its simple formula.
Lexical propensities in phonology: corpus and experimental evidence, grammar, and learning

Author(s): Zymet, Jesse | Advisor(s): Hayes, Bruce P; Zuraw, Kie | Abstract: Traditional theories of phonological variation propose that morphemes be encoded with descriptors such as [+/- Rule X], to capture which of them participate in a variable process. More recent theories predict that morphemes can have LEXICAL PROPENSITIES: idiosyncratic, gradient rates at which they participate in a process—e.g., [0.7 Rule X]. This dissertation argues that such propensities exist, and that a binary distinction is not rich enough to characterize participation in variable processes. Corpus investigations into Slovenian palatalization and French liaison reveal that individual morphemes pattern across an entire propensity spectrum, and that encoding individual morphemes with gradient status improves model performance. Furthermore, an experimental investigation into French speakers’ intuitions suggests that they internalize word- specific propensities to undergo liaison. The dissertation turns to modeling language learners’ ability to acquire the idiosyncratic behavior of individual attested morphemes while frequency matching to statistical generalizations across the lexicon. A recent model based in Maximum Entropy Harmonic Grammar (MaxEnt) makes use of general constraints that putatively capture statistical generalizations across the lexicon, as well as lexical constraints governing the behavior of individual words. A series of learning simulations reveals that the approach fails to learn statistical generalizations across the lexicon: lexical constraints are so powerful that the learner comes to acquire the behavior of each attested form using only these constraints, at which point the general constraint is rendered ineffective. A GENERALITY BIAS is therefore attributed to learners, whereby they privilege general constraints over lexical ones. It is argued that MaxEnt fails to represent this property in its current formulation, and that it be replaced with the hierarchical MIXED-EFFECTS LOGISTIC REGRESSION MODEL (MIXED-EFFECTS MAXENT), which is shown to succeed in learning both a frequency-matching grammar and lexical propensities, by encoding general constraints as fixed effects and lexical constraints as a random effect. The learner treats the grammar and lexicon differently, in that vocabulary effects are subordinated to broad, grammatical effects in the learning process.
Improving the Accuracy of Continuous Blood Glucose Measurement Using Personalized Calibration and Machine Learning

Despite tremendous developments in continuous blood glucose measurement (CBGM) sensors, they are still not accurate for all patients with diabetes. As glucose concentration in the blood is <1% of the total blood volume, it is challenging to accurately measure glucose levels in the interstitial fluid using CBGM sensors due to within-patient and between-patient variations. To address this issue, we developed a novel data-driven approach to accurately predict CBGM values using personalized calibration and machine learning. First, we scientifically divided measured blood glucose into smaller groups, namely, hypoglycemia (<80 mg/dL), nondiabetic (81–115 mg/dL), prediabetes (116–150 mg/dL), diabetes (151–181 mg/dL), severe diabetes (181–250 mg/dL), and critical diabetes (>250 mg/dL). Second, we separately trained each group using different machine learning models based on patients’ personalized parameters, such as physical activity, posture, heart rate, breath rate, skin temperature, and food intake. Lastly, we used multilayer perceptron (MLP) for the D1NAMO dataset (training to test ratio: 70:30) and grid search for hyperparameter optimization to predict accurate blood glucose concentrations. We successfully applied our proposed approach in nine patients with type 1 diabetes and observed that the mean absolute relative difference (MARD) decreased from 17.8% to 8.3%.
Dimensions of variation: Agreement with nominative objects in Icelandic

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cdh23 affects congenital hearing loss through regulating purine metabolism

Introduction The pathogenic gene CDH23 plays a pivotal role in tip links, which is indispensable for mechanoelectrical transduction in the hair cells. However, the underlying molecular mechanism and signal regulatory networks that influence deafness is still largely unknown. Methods In this study, a congenital deafness family, whole exome sequencing revealed a new mutation in the pathogenic gene CDH23, subsequently; the mutation has been validated using Sanger sequencing method. Then CRISPR/Cas9 technology was employed to knockout zebrafish cdh23 gene. Startle response experiment was used to compare with wide-type, the response to sound stimulation between wide-type and cdh23−/−. To further illustrate the molecular mechanisms underlying congenital deafness, comparative transcriptomic profiling and multiple bioinformatics analyses were performed. Results The YO-PRO-1 assay result showed that in cdh23 deficient embryos, the YO-PRO-1 signal in inner ear and lateral line neuromast hair cells were completely lost. Startle response experiment showed that compared with wide-type, the response to sound stimulation decreased significantly in cdh23 mutant larvae. Comparative transcriptomic showed that the candidate genes such as atp1b2b and myof could affect hearing by regulating ATP production and purine metabolism in a synergetic way with cdh23. RT-qPCR results further confirmed the transcriptomics results. Further compensatory experiment showed that ATP treated cdh23−/− embryos can partially recover the mutant phenotype. Conclusion In conclusion, our study may shed light on deciphering the principal mechanism and provide a potential therapeutic method for congenital hearing loss under the condition of CDH23 mutation.
diseño de eventos experienciales corporativos: el caso del Evento World Corporate Golf Challenge

Los eventos corporativos son una excelente herramienta de relaciones públicas tanto a nivel interno como externo y ayudan a crear experiencias que vinculan a sus públicos con la organización en cuestión. En esta investigación analizaremos el caso del Torneo World Corporate Golf Challenge, la mayor competición de golf amateur del mundo, desde la perspectiva de los eventos corporativos experienciales. Los eventos deportivos de golf adquirieron especial protagonismo en los años anteriores a la pandemia por sus posibilidades de ofrecer experiencias relacionales entre los públicos de las empresas (tanto entre clientes como empleados). Los torneos de golf han mostrado ser una herramienta de relaciones públicas apropiada para promover experiencias significativas que generan cercanía y confianza entre las empresas participantes y sus grupos de interés. Se ha estudiado el Caso World Corporate Golf Challenge desde la perspectiva del diseño de la experiencia corporativa en sus dimensiones sensorial, emocional, intelectual, relacional y de acción.