Miracle-dz/UniFAR-FTUs huggingface dataset:
Paradoxical effects of social media use on workplace interpersonal conflicts

Abstract The prevalence of social media use urged researchers to identify its antecedents and consequences. However, research related to social media use in occupational settings has been substantially ignored. Therefore, this study aims to examine the effect of job stress on social media use (social media addiction and work-related social media activities) and its effect on interpersonal conflict at the workplace. The study was conducted using a cross-sectional design. An online questionnaire survey was used to collect data from 253 office employees working in the oil and gas industry in Malaysia. Structural equation modelling was employed for statistical analysis using smart PLS. Results demonstrate a significant positive effect of job stress on social media use (social media addiction and work-related activities on social media) and its significant positive effect on interpersonal conflict in the workplace. Social media behaviour mediates the relationship between job stress and workplace interpersonal conflicts. The study findings show that employees use social media to cope with job stress, which in turn increases interpersonal conflicts at the workplace. Further, the inclination towards social media use indicates the absence of active social support at the workplace. The study findings support the efforts of organisational stakeholders to manage workplace stress by reducing employee’s dependency on online social media and by encouraging “offline active social support” in the offices.
Comprehensive comparison of protective effect of customized multi-layered versus boil-and-bite mouth guard on orofacial tissues: A finite element analysis framework

This paper aims to numerically investigate the protective efficiency of multilayered and boil-and-bite mouthguards on orofacial hard and soft tissues subjected to impact loadings. To the best of our knowledge, this is the first attempt which studies the protective efficacy of mouthguards on orofacial injuries including both hard and soft tissues such as articular disks, stylomandibular and sphenomandibular ligaments, that are commonly neglected in clinical and numerical studies. To address this issue, a finite element based numerical framework has been proposed using the Abaqus finite element software. This study considers three different situations of the craniofacial structure, without any mouthguard, with the customized multilayered mouthguard and with a boil-and-bite mouthguard. The protective effectiveness of mouthguards is numerically evaluated based on pressure and displacement distributions on the orofacial hard and soft tissues under two different actual impact loadings. In all cases the results revealed that the customized multilayered mouthguard can more effectively reduce the stress concentration on orofacial hard and soft tissues which is the key factor to evaluate the protective efficiency of different types of mouthguard. As an example, a comparison between the protective efficiency of multilayered and boil-and-bite mouthguards reveals that under uppercut punch impact loading, the multilayered mouthguard performs 18.45% and 21.32% more effective respectively for upper and lower teeth and stylomandibular ligament. Furthermore, the simulation results for stylomandibular ligament and articular disk enable us to conclude that wearing a customized multilayered mouthguard cannot be replaced by a boil-and-bite mouthguard, since it causes more harm in comparison to the unprotected case.
Biological Variation and Reference Change Value of Routine Hematology Measurands in a Population of Managed Bottlenose Dolphins (Tursiops truncatus)

Simple Summary Calculating hematological reference intervals for bottlenose dolphins poses a challenge due to a limited number of reference individuals. However, individual reference intervals (iRIs) can be used to overcome this limitation. We evaluated the biological variations in hematological measurands and calculated the index of individuality (IoI) and the reference change value (RCV), which enable the production of iRIs, in healthy managed bottlenose dolphins. Analysis of IoI indicates that the use of iRIs is suitable for most hematological measurands. Furthermore, the calculated RCV can be applied to other dolphins that have undergone serial hematological exams. These tools provide valuable information for interpreting hematologic exams in managed bottlenose dolphins. Abstract Hematological analyses are particularly useful in assessing a dolphin’s health status. However, the creation of appropriate reference intervals for this species is difficult due to the low number of reference individuals. The implementation of individual reference intervals (iRIs) allows researchers to overcome this limitation and, moreover, also consider the within-individual variability. The aims of this study were (1) to evaluate the biological variations in some hematological measurands, including erythrocytes (RBC), hematocrit (Hct), mean cellular volume and hemoglobin content (MCV and MCHC, respectively), RBC distribution width (RDW), leukocytes (WBC), and platelets (PLT); and (2) to calculate the index of individuality (IoI) and reference change value (RCV), which enable the production of iRIs, in healthy managed bottlenose dolphins. Seven dolphins were included, and the results of six hematological exams were analyzed for each animal. Analytical imprecision (CVa), within-dolphin variation (CVi), and between-dolphins variations (CVg) were calculated, and the IoI and RCV were derived for each measurand. All the hematological measurands had intermediate IoI except WBC, for which Iol was low. The calculated RCV ranged from 10.33% (MCV) to 186.51% (WBC). The results reveal that the majority of hematological measurands have an intermediate level of individuality in dolphins, and thus the application of iRIs is appropriate. The calculated RCV can also be applied to other managed dolphins and could be useful in interpreting serial CBC exams.
Human Papillomavirus Infection and EGFR Exon 20 Insertions in Sinonasal Inverted Papilloma and Squamous Cell Carcinoma

This study aimed to clarify the roles of high-risk human papillomavirus (HR-HPV) infection and epidermal growth factor receptor (EGFR) exon 20 mutations in sinonasal inverted papilloma (IP) and sinonasal squamous cell carcinoma (SNSCC). Samples were collected from 20 cases with IP, 7 with IP and squamous cell carcinoma (IP-SCC), and 20 with SNSCC and examined for HPV infection and EGFR exon 20 mutations. Low- or high-risk HPV DNA was observed in 25% of IP, 57.1% of IP-SCC, and 35% of SNSCC cases. Transcriptionally active HR-HPV infections in IP-SCC and SNSCC, accompanied by p16 overexpression, were observed in 28.5% and 25% of cases, respectively. Heterozygous EGFR exon 20 amino acid insertions (ex20ins), located between amino acids 768–774, were observed in 45% of IP, 28.5% of IP-SCC, and 0% of SNSCC and chronic sinusitis cases. EGFR phosphorylation sites were located at tyrosine (Y) 845, Y1068, Y1086, and Y1197 and induced PI3K/AKT/mTOR activation. The phosphorylation pattern of EGFR with ex20ins resembled that of HPV-related SNSCC and oropharyngeal cancer. The transcriptionally active HR-HPV infection and ex20ins might be responsible for the pathogenesis of IP-SCC cases with different fashions. Since IP-SCC might be a multifactorial disease, further investigation is needed to understand IP-SCC etiology.
Asymptotic giant branch stars in the Large Magellanic Cloud: evolution of dust in circumstellar envelopes

We calculated theoretical evolutionary sequences of asymptotic giant branch (AGB) stars, including formation and evolution of dust grains in their circumstellar envelope. By considering stellar populations of the Large Magellanic Cloud (LMC), we calculate synthetic colour-colour and colour-magnitude diagrams, which are compared with those obtained by the Spitzer Space Telescope. The comparison between observations and theoretical predictions outlines that extremely obscured carbon-stars and oxygen-rich sources experiencing hot bottom burning (HBB) occupy well defined, distinct regions in the colour-colour ($[3.6]-[4.5]$, $[5.8]-[8.0]$) diagram. The C-rich stars are distributed along a diagonal strip that we interpret as an evolutionary sequence, becoming progressively more obscured as the stellar surface layers enrich in carbon. Their circumstellar envelopes host solid carbon dust grains with size in the range $0.05 2$, are the descendants of stars with initial mass $M_{in} \sim 2.5 - 3 M_{\odot}$ in the very latest phases of the AGB life. The oxygen-rich stars with the reddest colours ($[5.8]-[8.0] > 0.6$) are those experiencing HBB, the descendants of $\sim 5 M_{\odot}$ objects formed $10^{8}$ yr ago; alumina and silicates dust start forming at different distances from the central star. The overall dust production rate in the LMC is $\sim 4.5 \times 10^{-5} M_{\odot}/yr$, the relative percentages due to C- and M- star being respectively 85$%$ and 15 $%$.
Precursors for synthetic aperture radar

In this paper we study waveform design for synthetic-aperture radar (SAR) imaging through dispersive media. Under the assumptions of scalar wave propagation through a causal dielectric medium and single-scattering from an isotropic point scatterer, we use asymptotic analysis to derive the asymptotic approximation to the scattered electric field. From this asymptotic approximation, we define a sensing precursor that we propose for the transmit waveform for SAR imaging through dispersive material. We compare our sensing precursor with previously defined optimal waveforms (Varslot et al 2011 SIAM J. Appl. Math. 71 1780–800) in terms of both propagation and scattering capabilities, as well as imaging performance. With the filtered back-projection imaging algorithm that we use, we find that for high levels of signal-to-noise ratio (SNR), the optimal waveforms contain higher frequencies and thus produce better images. For low levels of SNR, the transmitted optimal waveforms and the sensing precursors are similar, thus giving comparable images.
The Impact of COVID-19 Pandemic on Medical Imaging Workers: Infection Sources, Awareness and Commitment to relevant Safety Guidelines

COVID-19 virus disease is an infectious disease caused by SARS-Cov-2 virus, as the diagnostic imaging department play a remarkable role in detecting and diagnosing of COVID-19 in early stages, therefore, medical imaging workers should be aware of infection control guidelines to prevent the transmission of the disease. A cross-sectional descriptive study survey design was conducted from July 15, 2020 to September 15, 2020, in diagnostic imaging departments in Palestine, aimed to evaluate the impact of COVID-19 pandemic on medical imaging workers; in terms of infection sources, awareness and commitment to relevant safety guidelines. From a 205 valid responses, there was 54.5% governmental, 27.2% private, and 18.3% from NGOs sector. Female were 26.8% and 81.9% holding BA degree, about 41.2% are less than five years of experience. 36.1% had a previous positive COVID-19 result, of them there was 61.6% due to nosocomial infection. Only 63.2% were confidence of their hospital preparedness for COVID-19, 65.1% felt that their department is capable of dealing with COVID-19 patients, 43.3% revealed that they had training on handling COVID-19 patients, 58.7% reported that selfreading was their source of information about COVID-19, inadequate training or knowledge about hand hygiene and proper use of PPE was noted. Our findings emphasize the vital need of expanded COVID-19 pandemic training for medical imaging workers, as well as related protective measures
Algebraic Signature-Based Public Data Integrity Batch Verification for Cloud-IoT

With the rapid development of Internet of Things, the related data are growing explosively. However, IoT devices have limited storage and computing capabilities so that they cannot deal with massive data storage and computing locally. The integration of IoT and cloud is regarded as an effective solution to the above issue, i.e., IoT devices outsource collected data to cloud to enjoy powerful storage and computing resources. Because the data stored in cloud are out of the control of IoT users, some security risks need to be addressed in advance. In this article, we propose a public data integrity verification scheme, called AIVCI, to check the data integrity for Cloud-IoT scenarios. First, based on algebraic signature and homomorphic hash function, AIVCI can efficiently complete data auditing. Second, AIVCI adopts blind technology to prevent the privacy leakage of IoT data and further protect the privacy of IoT users. Third, batch auditing is implemented to improve auditing efficiency and meet realistic demands for Cloud-IoT scenarios. And a new data structure named Improved Divide and Conquer Table (ID&CT) is designed to realize efficient data dynamics. Finally, the security and performance analyses demonstrate that AIVCI is more secure and efficient.
Probing Grade 10 Students about Their Mathematical Errors on Simplifying Algebraic Fractions

The purpose of this research was to explore to what extent probing learners'1 errors on simplifying algebraic fractions would help them to reduce those errors. The study assumed that students' errors and misconceptions persist because they handle mathematical concepts as if they were isolated chunks of knowledge. A sample of 15 grade 10 girls took part in the research. Data was collected in three stages. A pre-test requiring learners to simplify algebraic fractions was issued to the students. Thereafter, their scripts were analysed for errors. During interviews, students were probed on the errors they exhibited in solving the tasks. Students then wrote a post-test to determine how much errors and misconceptions were overcome as a result of the probing process. The results showed that students overcame 98.6 per cent of their pre-test errors. We recommend that in every case, teachers need to be on the lookout of their learners' mathematical errors. Then they must probe their learners on the errors as it helps learners to overcome their errors as this study shows.
Optimizing Outcomes in Flexible Ureteroscopy: A Narrative Review of Suction Techniques

Objective: The aim of this review is to summarize the existing suction systems in flexible ureteroscopy (fURS) and to evaluate their effectiveness and safety. Methods: A narrative review was performed using the Pubmed and Web of Science Core Collection (WoSCC) databases. Additionally, we conducted a search on the Twitter platform. Studies including suctions systems in fURS were included. Editorials, letters and studies reporting intervention with semirigid ureteroscopy, PCNL and mPCNL were excluded. Results: A total of 12 studies were included in this review. These studies comprised one in vitro study, one ex vivo study, one experimental study and eight cohort studies. The Pubmed and WoSCC searches identified three suction techniques (Irrigation/Suctioning system with control of pressure, suction ureteral access sheath (sUAS) and direct in scope suction (DISS)), and the Twitter search identified four of them. The overall results showed that suction is an effective and safe technique that improves stone-free rates, reduces operative time and limits complication rates after fURS. Conclusions: The use of suctioning during common endourological procedures has been shown to improve safety and efficacy in several indications. However, randomized controlled trials are needed to confirm this.
The First Survival Score for Patients Treated with Whole-Brain Radiotherapy Plus Simultaneous Integrated Boost for Brain Metastases

Simple Summary A model was generated to judge survival after whole-brain radiotherapy plus simultaneous boost (WBRT+SIB) for cerebral metastases. Initially, three models, each including three prognostic groups, were created and compared for accuracy in prognosticating death ≤ 6 and survival ≥ 6 months using the corresponding positive predictive values (PPVs). PPVs to predict death ≤ 6 and survival ≥ 6 months were 85% and 57% for Model 1 (considering performance status = KPS and the number of lesions), 83% and 75% for Model 2 (KPS, lesions, age), and 86% and 78% for Model 3 (KPS, lesions, age, extra-cerebral metastases), respectively. The three models were accurate in predicting death ≤ 6 months and Models 2 and 3 were more precise than Model 1 in predicting survival ≥6 months. Model 2 appears preferable for many patients. Patients with poor survival prognoses may not benefit from adding SIB. Abstract A modern approach for brain metastases includes whole-brain radiotherapy plus simultaneous boost (WBRT+SIB). We developed a survival score in 128 patients treated with WBRT+SIB. Three models, each including three prognostic groups, were created. Positive predictive values (PPVs) for death ≤6 and survival ≥6 months were calculated. On multivariate analyses, performance score (KPS) and the number of brain metastases were significantly associated with survival. On univariate analyses, age showed a strong trend, and extra-cerebral cranial metastases a trend. In Model 1 (KPS, number of lesions), compared groups had 6-month survival rates of 15%, 38% and 57%. In Model 2 (KPS, lesions, age), rates were 17%, 33% and 75%, and in Model 3 (KPS, lesions, age, extra-cerebral metastases), 14%, 34% and 78%. PPVs for death ≤6 and survival ≥6 months were 85% and 57% (Model 1), 83% and 75% (Model 2), and 86% and 78% (Model 3). Thus, all models were accurate in predicting death ≤ 6 months; poor-prognosis patients may not benefit from SIB. Models 2 and 3 were superior in predicting survival ≥ 6 months. Given that Model 3 requires more data (including extensive staging), Model 2 is considered favorable for many patients. If extra-cerebral metastases are already known or extensive staging has been performed, Model 3 can also be used.
Campus Abnormal Behavior Recognition With Temporal Segment Transformers

The intelligent campus surveillance system is beneficial to improve safety in school. Abnormal behavior recognition, a field of action recognition in computer vision, plays an essential role in intelligent surveillance systems. Computer vision has been actively applied to action recognition systems based on Convolutional Neural Networks (CNNs). However, capturing sufficient motion sequence features from videos remains a significant challenge in action recognition. This work explores the challenges of video-based abnormal behavior recognition on campus. In addition, a novel framework is established on long-range temporal video structure modeling and a global sparse uniform sampling strategy that divides a video into three segments of identical durations and uniformly samples each snippet. The proposed method incorporates a consensus of three temporal segment transformers (TST) that globally connects patches and computes self-attention with joint spatiotemporal factorization. The proposed model is developed on the newly created campus abnormal behavior recognition (CABR50) dataset, which contains 50 human abnormal action classes with an average of over 700 clips per class. Experiments show that it is feasible to implement abnormal behavior recognition on campus and that the proposed method is competitive with other peer video recognition in terms of Top-1 and Top-5 recognition accuracy. The results suggest that TST-L+ can improve campus abnormal behavior recognition, corresponding to Top-1 and Top-5 accuracy results of 83.57% and 97.16%, respectively.
MCP-1-2518 (A>G) polymorphism and asthma risk: a pilot case-control study in Cameroon

Introduction there is little data on the genetic determinants of asthma in Cameroon and sub-Saharan Africa, yet the involvement of genetics in the pathogenesis of this disease has been reported in the literature for several years. This study aims to investigate the possible role of MCP-1 2518 for the risk of asthma in Cameroonians. Methods we performed a case-control study on 30 volunteers suffering from asthma, matched by aged and sex to 30 healthy subjects. We determine the polymorphism of MCP-1 2518 using restriction fragment length polymorphism following Polymerase Chain Reaction (RFLP-PCR). Fisher exact test was used to compare proportions, with a threshold of significance set at 0.05. Results the average age of cases was 21±10 years with 17 (56.7%) females. The distribution of the MCP-1-2518 (A>G) gene polymorphism in people with asthma was as follows: 3 for AA, 5 for GG, and 22 for AG. The minor G allele was predominant (90%) in people with asthma. It was significantly associated with asthma whether the genotype was heterozygous AG or homozygous GG (p<0.01). Conclusion MCP-1-2518 (A>G) shows an association with asthma in our sample. Future larger studies evaluating several polymorphisms are needed to describe the genetic determinants of asthma in Cameroon and sub-Saharan Africa.
goose-fronting in Received Pronunciation across time: A trend study

Abstract The current study analyzes the trajectory of the goose vowel in Received Pronunciation (RP) over ten decades (1920s-2010s). Recordings of eighty-seven RP speakers were transcribed in ELAN, and vowel tokens were extracted by FAVE, measuring F1 and F2 values at the midpoint. Showing the life-cycle of a sound change from start to (almost) completion, the results confirm that goose-fronting has been an active sound change for many decades in RP, with F2 starting to increase in the middle of the twentieth century and accelerated changes in the 1970s and the 2010s. We observe similar predictor strengths of linguistic factors as in previous studies. The results are interpreted in light of the social changes in the social composition of the RP group in the second part of the twentieth century, involving increased dialect contact.
Roadmap to digital supply chain resilience under investment constraints

ABSTRACT In a world bombarded with unprecedented challenges, it is paramount for organizations to embrace resilience in all their processes, albeit supply chain management. In the wake of ever-intensifying race for digital transformation, it is crucial for organizations to follow structured roadmaps towards building digital supply chain resilience (DSCR) through striking a balance between supply chain resilience (SCR) and supply chain vulnerabilities (SCV), in a manner that does not erode profits, neither expose the organization to increasing vulnerabilities. The paper addresses the evolution of SCR, the SCR and SCV drivers, and recommends investment in particular Industry 4.0 (I4.0) enablers. The outcomes of this paper are (a) a discussion of the complementary relationship between SCR and SCV drivers; (b) a thorough understanding of the possible contributions of I4.0 technologies towards DSCR; and (c) a roadmap for future research into the integration of SCR drivers and SCV constrained by the resilience fitness space (RFS).
Recent Research on Cannabis sativa L.: Phytochemistry, New Matrices, Cultivation Techniques, and Recent Updates on Its Brain-Related Effects (2018–2023)

Cannabis sativa L. is a plant that humankind has been using for millennia. The basis of its widespread utilization is its adaptability to so many different climatic conditions, with easy cultivability in numerous diverse environments. Because of its variegate phytochemistry, C. sativa has been used in many sectors, although the discovery of the presence in the plant of several psychotropic substances (e.g., Δ9-tetrahydrocannabinol, THC) caused a drastic reduction of its cultivation and use together with its official ban from pharmacopeias. Fortunately, the discovery of Cannabis varieties with low content of THC as well as the biotechnological development of new clones rich in many phytochemical components endorsed with peculiar and many important bioactivities has demanded the reassessment of these species, the study and use of which are currently experiencing new and important developments. In this review we focus our attention on the phytochemistry, new matrices, suitable agronomic techniques, and new biological activities developed in the five last years.