Miracle-dz/UniFAR-FTUs huggingface dataset:
The impact of social media marketing on youth buying behaviour in an emerging country

The research aims to investigate the impact of social media marketing (SMM) on youth buying behavior in Pakistan. This study is empirically supported by the results of a survey conducted by the authors in ten universities in Lahore city (Pakistan) in March-June 2020 on a sample of 244 students (social media users) aged from 18 to 35. By conceptually dividing social media marketing into SMM advantages and website design & features, the purpose of this study became more specific: (1) to find the relationship between SMM advantages (convenience, timesaving, security of knowledge) and youth buying behavior; (2) to find the relationship between website features & design and youth buying behavior. Results of the analysis of the aggregate influence of SMM advantages on Pakistani youth buying behavior showed that they increase the intention to purchase by 42.9%. At the same time, website design & features used within social media marketing have even more positive effects on youth buying behavior, increasing the intention to purchase by 55.2%. Young buyers in Pakistan prefer attractive and well-designed websites or social media with many unique features for buying products and services. Thus, all research hypotheses are proved based on the survey data: social media marketing raised by unit positively affects Pakistani youth buying behavior by 53.5%, and the rest 46.5% could be conditioned by other non-market external and internal factors. The novelty of this study lies in investigating behavior patterns of the fast-growing segment of consumers of Pakistan, which, are the most active consumers of goods and services and social media users today and in the future.
Intentional Communication: Computationally Easy or Difficult?

Human intentional communication is marked by its flexibility and context sensitivity. Hypothesized brain mechanisms can provide convincing and complete explanations of the human capacity for intentional communication only insofar as they can match the computational power required for displaying that capacity. It is thus of importance for cognitive neuroscience to know how computationally complex intentional communication actually is. Though the subject of considerable debate, the computational complexity of communication remains so far unknown. In this paper we defend the position that the computational complexity of communication is not a constant, as some views of communication seem to hold, but rather a function of situational factors. We present a methodology for studying and characterizing the computational complexity of communication under different situational constraints. We illustrate our methodology for a model of the problems solved by receivers and senders during a communicative exchange. This approach opens the way to a principled identification of putative model parameters that control cognitive processes supporting intentional communication.
Telemedicine home CPAP titration and follow-up in the COVID-19 scenario

Introduction Continuous positive airway pressure (CPAP) titration was dramatically affected by the coronavirus disease 2019 (COVID-19) pandemic due to increased biological risk. This study aimed to compare successful CPAP adaptation and compliance with home telemedicine CPAP titration with the usual method based on face-to-face visits. Methodology A prospective cohort using telemedicine home CPAP titration and follow-up during the COVID-19 pandemic (TC) was compared with a retrospective cohort receiving face-to-face pre-pandemic home titration (RC). The TC included a subgroup with a smartphone application (TC-APP). Successful CPAP adaptation and compliance at 1 month of follow-up were the main endpoints, while patient satisfaction and costs were secondary endpoints. Results 210 consecutive patients were evaluated (80 RC and 130 TC). 36 patients were in the TC-APP subgroup. CPAP titration was successful in 90% in RC versus 95% in TC and 100% in TC-APP. No compliance differences between groups were found at 1 month (4.79 h·night−1 RC, 4.33 h·night−1 TC and 4.59 h·night−1 TC-APP). Mean±sd patient satisfaction out of 10 was 7.69±2.05 in RC versus 9.02±0.64 in TC (p<0.001). 64% of the TC-APP subgroup reported that their telemedicine strategy influenced an increase in CPAP use (p=0.011). CPAP adaptation with follow-up had an estimated direct staff cost per patient of EUR 19.61±8.61 in TC with no smartphone application used versus EUR 23.79±9.94 in TC-APP (p=0.048). Conclusions Telemedicine in CPAP titration and early follow-up is equivalent to the usual care in terms of successful adaptation and compliance, while achieving greater patient satisfaction. Telemedicine home CPAP titration and early follow-up is equivalent to usual care in adaptation and compliance while achieving greater patient satisfaction. The use of the mHealth application may help patients self-empower and encourage increased CPAP use. https://bit.ly/3xwvwLX
The Implementation Process of Two Evidence-Based Protocols: A Spatial Neglect Network Initiative

Introduction Spatial neglect, a neurocognitive disorder of lateralized spatial attention, is prevalent among stroke survivors especially in inpatient rehabilitation facilities (IRFs). The ultimate goal of the project was to improve spatial neglect care in inpatient rehabilitation and trained as many OTs as possible using both tools in their regular practices as the means to achieve our overall objective. Therefore, we conducted a project aimed at implementing two evidence-based protocols, one for assessment (KF-NAP®) and the other for treatment (KF-PAT®), and share the implementation process, which included barriers and facilitators identified during and after the process, and implementation outcomes. Methods Sixteen IRFs were involved. The Knowledge-To-Action Cycle was used to describe the process of knowledge inquiry (training), translating knowledge (implementation) and evaluating the use of knowledge in clinical practice (outcomes). Barriers and strategies were reported using the Consolidated Framework for Implementation Research and identified through a survey, after the study concluded. Results Thirty-two therapists at the participating sites were trained to some level of the KF-NAP and KF-PAT. Throughout the project and also once after it finished, different barriers were identified by researchers and clinicians, who then determined together actions to eliminate or minimize the barriers. For example, multiple sites reported: “not having time to train other staff at their hospital due to high patient volume and other responsibilities. ” Discussion The project shared our implementation process which demonstrated the importance of using implementation methods and incorporating a researcher-clinician partnership, not only for knowledge generation but also knowledge translation. Frequent communications and exchanging information with stakeholders at different levels, may be determinant to the success of each implementation phase. Further research is needed.
Multi-task learning for low-frequency extrapolation and elastic model building from seismic data

Low-frequency signal content in seismic data as well as a realistic initial model are key ingredients for robust and efficient full-waveform inversions. However, acquiring low-frequency data is challenging in practice for active seismic surveys. Data-driven solutions show promise to extrapolate low-frequency data given a high-frequency counterpart. While being established for synthetic acoustic examples, the application of bandwidth extrapolation to field datasets remains non-trivial. Rather than aiming to reach superior accuracy in bandwidth extrapolation, we propose to jointly reconstruct low-frequency data and a smooth background subsurface model within a multi-task deep learning framework. We automatically balance data, model and trace-wise correlation loss terms in the objective functional and show that this approach improves the extrapolation capability of the network. We also design a pipeline for generating synthetic data suitable for field data applications. Finally, we apply the same trained network to synthetic and real marine streamer datasets and run an elastic full-waveform inversion from the extrapolated dataset.
Memorable nature-based tourism experience, place attachment and tourists’ environmentally responsible behaviour

ABSTRACT This study tests a new model for memorable nature-based tourism experiences by examining the effects of novelty, experiencescape, experience co-creation, experience intensification and satisfaction. The study also examines the relationship between memorable nature-based tourism experiences, place attachment and tourists' environmentally responsible behaviour. Data were gathered from tourists who visited a national park within the three months preceding the data collection period (January-March 2021) using an online survey questionnaire distributed through Amazon Mechanical Turk (MTurk) in March 2021. This study's main contributions include the expansion of the memorable tourism experience construct and the inclusion of four key variables that influence place attachment in the formation of tourists' memorable nature-based tourism experiences. The relationship between place attachment and tourists' environmentally responsible behaviour was also shown to be significant.
Comparative Metabolomics Study of the Impact of Articaine and Lidocaine on the Metabolism of SH-SY5Y Neuronal Cells

Articaine (ATC) and lidocaine (LDC) are the local anesthetics (LAs) currently most employed in dentistry. Cases of paresthesia, reported more frequently for ATC, have raised concerns about their potential neurotoxicity, calling for further investigation of their biological effects in neuronal cells. In this work, the impact of ATC and LDC on the metabolism of SH-SY5Y cells was investigated through 1H NMR metabolomics. For each LA, in vitro cultured cells were exposed to concentrations causing 10 and 50% reductions in cell viability, and their metabolic intracellular and extracellular profiles were characterized. Most effects were common to ATC and LDC, although with varying magnitudes. The metabolic variations elicited by the two LAs suggested (i) downregulation of glycolysis and of glucose-dependent pathways (e.g., one-carbon metabolism and hexosamine biosynthetic pathway), (ii) disturbance of branched chain amino acids (BCAA) catabolism, (iii) downregulation of TCA cycle anaplerotic fueling and activation of alternative energy producing pathways, (iv) interference with choline metabolism and (v) lipid droplet build-up. Interestingly, LDC had a greater impact on membrane phospholipid turnover, as suggested by higher phosphatidylcholine to phosphocholine conversion. Moreover, LDC elicited an increase in triglycerides, whereas cholesteryl esters accumulated in ATC-exposed cells, suggesting a different composition and handling of lipid droplets.
Upfront Next Generation Sequencing in Non-Small Cell Lung Cancer

In advanced non-small cell lung cancer (NSCLC), patients with actionable genomic alterations may derive additional clinical benefit from targeted treatment compared to cytotoxic chemotherapy. Current guidelines recommend extensive testing with next generation sequencing (NGS) panels. We investigated the impact of using a targeted NGS panel (TruSight Tumor 15, Illumina) as reflex testing for NSCLC samples at a single institution. Molecular analysis examined 15 genes for hotspot mutation variants, including AKT1, BRAF, EGFR, ERBB2, FOXL2, GNA11, GNAQ, KIT, KRAS, MET, NRAS, PDGFRA, PIK3CA, RET and TP53 genes. Between February 2017 and October 2020, 1460 samples from 1395 patients were analyzed. 1201 patients (86.1%) had at least one variant identified, most frequently TP53 (47.5%), KRAS (32.2%) or EGFR (24.2%). Among these, 994 patients (71.3%) had clinically relevant variants eligible for treatment with approved therapies or clinical trial enrollment. The incremental cost of NGS beyond single gene testing (EGFR, ALK) was CAD $233 per case. Reflex upfront NGS identified at least one actionable variant in more than 70% of patients with NSCLC, with minimal increase in testing cost. Implementation of NGS panels remains essential as treatment paradigms continue to evolve.
A Low-Cost Method for Understanding How Nature-Based Early Learning and Childcare Impacts Children’s Health and Wellbeing

Nature-based play and learning provision is becoming increasingly popular across the early learning and childcare (ELC) sector in Scotland. However, there remains a lack of understanding of how the program is expected to function. This has implications for program learning and may affect wider rollout of the program. Secondary data analysis of parent interviews (n = 22) and observations (n = 7) in Scottish ELC settings, and review of internationally published studies (n = 33) were triangulated to develop a program theory using the Theory of Change approach. This approach makes a program’s underlying assumptions explicit by systematically demonstrating the relationship between each component: inputs, activities, outcomes, impact, and the contexts of the program. Findings suggested that location of outdoor nature space, affordances, availability of trained practitioners, and transport to location lead to activities such as free play, educator-led activities, and interactions with nature, resulting in longer durations of physical activity, interactions with peers and educators, and increased engagement with the natural environment. These activities are vital for supporting children’s physical, cognitive, social, and emotional development. Our results demonstrate the value of using secondary data analysis to improve our understanding of the underlying theory of nature-based ELC which can support future evaluation designs. These findings will be of interest to program evaluators, researchers, practitioners, and funders, who find themselves with limited resources and want to better understand their program before investing in an evaluation. We encourage researchers and evaluators in the field of early years and outdoor play in other countries to refine this logic model in their own context-specific setting.
Stochastic Dynamic Electrospray Ionization Mass Spectrometric Quantitative Analysis of Metronidazole in Human Urine

Abstract The study reports quantification of metronidazole (MTZ) in clinical human urine employing our innovative stochastic dynamic equation D”SD =2.6388. 10-17. (–). There are direct analysis without presence of internal standard, using ultra-high accuracy nano-electrospray ionization (ESI) mass spectrometry (MS), quantum chemistry and chemometrics, respectively. The linear calibration D”SD =f(conc.) equations are obtained for concentration range 2.5 to 25000 ng. (mL)-1 of spiked urine samples, examining analyte MS ions at m/z 171.0998, 172.0718, 172.04081, 213.1463, 181.0722 and 151.1114, respectively. There is achieved exact coefficient of linear correlation (|r|=1) between theory and experiment of ion at m/z 172.04081. The major challenge to quantify MTZ in urine sample is that it stabilizes cations [M+H]+ of two tautomers, which equilibrium varies drastically within the standard linear calibration dynamic range. The fragmentation patterns depend on analyte tautomers and it unambiguous assignment in multicomponent samples with complex sample matrix effect (SME) is unable to be made without mediation to an independent physico-chemical law. To solve the problem, herein, is used, again, above equation, which is designed a bridge between quantitative and multidimensional structural analytical chemistry, when is used complementary with Arrhenius’s quantum chemical diffusion parameter (DQC.) There is achieved |r|=0.98 of D”SD=f(DQC’) examining tautomeric molecular and fragment ions of MTZ. GRAPHICAL ABSTRACT
Liver Function Tests and FIB-4 Score as Predictors of Severity in COVID-19 Patients from the South-West of Romania

Background: The coronavirus disease 2019 pandemic (COVID-19) is the most important global health crisis to date. In this study, we performed an analysis to find the association between liver damage, FIB-4 score and the severity of COVID-19 disease. Methods: We included a total of 580 patients that tested positive for SARS-CoV-2 infection and were hospitalized. No patient included had any known history of liver disease. Liver function tests were performed, and FIB-4 score was calculated in order to assess their involvement in the disease progression. Results: More than half of the patients had elevated liver function tests. Age, high body mass index, associated heart disease and diabetes were associated with poor outcome. Corticosteroids, antibiotics, and anticoagulants strongly correlated with liver injuries. Liver impairment and injury, as well as a FIB-4 score higher than 3.5, also correlated with higher degrees of disease severity. Conclusion: Liver injury and elevated FIB-4 score were associated with poor clinical outcome and disease severity, as well as being a valuable tool to predict COVID-19-related mortality.
Exploring grower strategies and needs for enhancing organic disease management of tomato late blight

Abstract Late blight, caused by the oomycete Phytophthora infestans, poses a significant challenge to organic tomato and potato production systems across the globe. To enhance education and outreach programming pertaining to tomato organic late blight management in Wisconsin, we sought to identify grower strategies and needs through an online survey conducted during spring 2018. Our findings demonstrated that organic growers emphasized crop diversity, crop rotation and soil health in their late blight management decisions. Grower concerns about biopesticides were identified and suggest that the use of input-based products within integrated management programs could be enhanced by further research on effectiveness and modes of actions. Additionally, stronger emphasis on oomycete pathogen biology and the significance of late blight as a community disease were identified as important areas of emphasis in the development of organic disease management education programming and resources that promote more effective cultural and chemical disease management strategies that adhere to the regulation and principles underlying the USDA National Organic Program. The integration of a live polling questionnaire conducted in winter 2019 allowed us to corroborate findings from the online survey and underscored the importance of two-way learning to enhance outreach efforts between Extension and organic growers in Wisconsin and the surrounding upper Midwestern states.
Crossover of Work Engagement: The Moderating Role of Agreeableness

Work engagement can cross over from one individual to another, and this process may depend on several factors, such as the work context or individual differences. With this study, we argue that agreeableness, one of the Big five personality measures that characterized empathetic, can be instrumental in the crossover process. Specifically, we hypothesize that agreeableness can facilitate this process so that engagement of an actor can more easily cross over to their partner when either of them or both have high agreeableness. To evaluate our hypotheses, we implemented an intervention to the working schedules of 74 participants for two weeks. The intervention involved pairing participants to work together so that to create dyads with varying levels of dissimilarity. The results from a multilevel regression model indicate that there is a crossover effect and partner’s work engagement can be transferred to actor after a two-week collaboration. This effect is further intensified if either one or both members in the dyad are characterized by high levels of agreeableness. These findings help to decode the mechanisms underlying the crossover process and illustrate how to ideally coordinate work dyads to take advantage of the crossover effect and maximize employee engagement.
Developing a first-year seminar course in statistics and data science

Statistical literacy is an increasingly important skill for today’s students. Undergraduate enrollments in statistics at both the introductory and advanced level have skyrocketed, and statistics education researchers have done much to modernize the curricula and increase student engagement. The course describes in this paper explores an alternative approach to statistical literacy and data science: a discussion-oriented, first-year seminar course. The seminar course emphasizes real data problems, student-led discussions and critiques, and the use of statistics in media and policy decisions. This paper will discuss the structure and justification, the content, and challenges instructors may face when adapting the course to their own institution.
Evaluating Cost Savings from Truck Caravanning

Truck platooning and related autonomous vehicle coordination concepts have been proposed as sustainable ways to increase profits and improve service quality. Recently the concept of truck caravanning, a hybrid truck platooning with only one truck driver required per platoon, has been proposed in the literature. This paper describes the research effort in developing a model that can estimate the cost savings of truck caravanning. The motivation of the proposed model is to investigate if substantial monetary savings exist to justify the initial capital investment (both in equipment and infrastructure) required for the implementation of the truck caravanning concept. A linear programming model is developed and used to evaluate different size networks. Results from numerical experiments indicate that a caravan size of four trucks or greater is needed for significant cost savings to be achieved and that driver compensation is the most critical factor dictating profitability.
Changes in Fecal Carriage of Extended-Spectrum β-Lactamase Producing Enterobacterales in Dutch Veal Calves by Clonal Spread of Klebsiella pneumoniae

This study aimed to characterize the changes in fecal carriage of Extended-Spectrum β-Lactamase (ESBL) producing Enterobacterales (ESBL-PE) in a single Dutch veal calves. During the rearing period at the Dutch veal farm, a decrease in fecal carriage of cefotaxime-resistant Escherichia coli isolates was observed after 2 weeks at the veal farm, while an increase of cefotaxime-resistant Klebsiella pneumoniae isolates was demonstrated. E. coli and K. pneumoniae were isolated from rectal swabs collected from 110 veal calves in week 2, 6, 10, 18, and 24 after their arrival at the farm. ESBL-PE isolates were selectively cultured and identified by MALDI-TOF. ESBL genes were characterized by RT-PCR, PCRs, and amplicon sequencing. A total of 80 E. coli and 174 K. pneumoniae strains were isolated from 104 out of 110 veal calves. The prevalence of ESBL-E. coli decreased from week 2 (61%) to week 6 (7%), while an unexpected increase in ESBL-K. pneumoniae colonization was detected in week 6 (80%). The predominant ESBL genes detected in E. coli isolates were blaCTX-M-15 and the non-ESBL gene blaTEM-1a, while in K. pneumoniae blaCTX-M-14 gene was detected in all isolates. Four cefotaxime-resistant K. pneumoniae isolates were randomly selected and characterized in deep by transformation, PCR-based replicon typing, and whole-genome sequencing (WGS). The clonal relatedness of a subgroup of nine animals carrying K. pneumoniae ESBL genes was investigated by Multi Locus sequence typing (MLST). In four ESBL-K. pneumoniae isolates, blaCTX-M-14 was located on IncFIIK and IncFIINK plasmid replicons and the isolates were multi-drug resistant (MDR). MLST demonstrated a clonal spread of ESBL-K. pneumoniae ST107. To the best of our knowledge, this is the first study to report a change in fecal carriage of ESBL-PE over time in the same veal calf during the rearing period.