Miracle-dz/UniFAR-FTUs huggingface dataset:
Bowel Preparation Instructions for Outpatient Colonoscopy Delivered by a Specialist Endoscopy Nurse was Superior to That Delivered by an Endoscopist

1.3. Results: Four-thousand-eight-hundred-and-seventy-seven subjects (85.0%) were in the Nurse group while 860 subjects (15.0%) were in the Endoscopist group. A total Boston Bowel Preparation Score ≥6 was achieved in 4721 of the 4877 (96.8%) subjects in the Nurse group when compared with 807 of the 860 (93.8%) subjects in the Endoscopist group (p<0.001). A total of 1624 of the 5737 (28.3%) subjects had adenomas on colonoscopy. There was no significant difference in the adenoma detection rate in the Nurse group when compared with the Endoscopist group [1388/4877 (28.5%) vs. 236/860 (27.4%), p=0.285]. There was also no significant difference in the total number of adenomas detected in the Nurse group when compared with the Endoscopist group [mean± standard deviation 0.48±1.08 vs. 0.44±1.18, p=0.412].
Effects of Algorithmic Music on the Cardiovascular Neural Control

Music influences many physiological parameters, including some cardiovascular (CV) control indices. The complexity and heterogeneity of musical stimuli, the integrated response within the brain and the limited availability of quantitative methods for non-invasive assessment of the autonomic function are the main reasons for the scarcity of studies about the impact of music on CV control. This study aims to investigate the effects of listening to algorithmic music on the CV regulation of healthy subjects by means of the spectral analysis of heart period, approximated as the time distance between two consecutive R-wave peaks (RR), and systolic arterial pressure (SAP) variability. We studied 10 healthy volunteers (age 39 ± 6 years, 5 females) both while supine (REST) and during passive orthostatism (TILT). Activating and relaxing algorithmic music tracks were used to produce possible contrasting effects. At baseline, the group featured normal indices of CV sympathovagal modulation both at REST and during TILT. Compared to baseline, at REST, listening to both musical stimuli did not affect time and frequency domain markers of both SAP and RR, except for a significant increase in mean RR. A physiological TILT response was maintained while listening to both musical tracks in terms of time and frequency domain markers, compared to baseline, an increase in mean RR was again observed. In healthy subjects featuring a normal CV neural profile at baseline, algorithmic music reduced the heart rate, a potentially favorable effect. The innovative music approach of this study encourages further research, as in the presence of several diseases, such as ischemic heart disease, hypertension, and heart failure, a standardized musical stimulation could play a therapeutic role.
Identification Method of Wheat Cultivars by Using a Convolutional Neural Network Combined with Images of Multiple Growth Periods of Wheat

Wheat is a very important food crop for mankind. Many new varieties are bred every year. The accurate judgment of wheat varieties can promote the development of the wheat industry and the protection of breeding property rights. Although gene analysis technology can be used to accurately determine wheat varieties, it is costly, time-consuming, and inconvenient. Traditional machine learning methods can significantly reduce the cost and time of wheat cultivars identification, but the accuracy is not high. In recent years, the relatively popular deep learning methods have further improved the accuracy on the basis of traditional machine learning, whereas it is quite difficult to continue to improve the identification accuracy after the convergence of the deep learning model. Based on the ResNet and SENet models, this paper draws on the idea of the bagging-based ensemble estimator algorithm, and proposes a deep learning model for wheat classification, CMPNet, which is coupled with the tillering period, flowering period, and seed image. This convolutional neural network (CNN) model has a symmetrical structure along the direction of the tensor flow. The model uses collected images of different types of wheat in multiple growth periods. First, it uses the transfer learning method of the ResNet-50, SE-ResNet, and SE-ResNeXt models, and then trains the collected images of 30 kinds of wheat in different growth periods. It then uses the concat layer to connect the output layers of the three models, and finally obtains the wheat classification results through the softmax function. The accuracy of wheat variety identification increased from 92.07% at the seed stage, 95.16% at the tillering stage, and 97.38% at the flowering stage to 99.51%. The model’s single inference time was only 0.0212 s. The model not only significantly improves the classification accuracy of wheat varieties, but also achieves low cost and high efficiency, which makes it a novel and important technology reference for wheat producers, managers, and law enforcement supervisors in the practice of wheat production.
Who Will Establish New Trade Relations? Looking for Potential Relationship in International Nickel Trade

Nickel ore sand and its concentrate are the main sources of raw nickel materials in various countries. Due to its uneven distribution throughout the world, the international trade of nickel ore sand is also unstable. Looking for potential links in the changing international nickel ore trade can help governments find potential partners, make strategic preparations in advance, and quickly find new partners when original trade relationships break down. In this paper, we build an international nickel ore trade network using a link prediction method to find potential trade relations between countries. The results show that China and Italy, China and Denmark, China and Indonesia, and China and India are most likely to establish trade relations within five years. Finally, according to the research results, suggestions regarding the international nickel ore trade are proposed.
A CAN-Bus Lightweight Authentication Scheme

The design of the Controller Area Network (CAN bus) did not account for security issues and, consequently, attacks often use external mobile communication interfaces to conduct eavesdropping, replay, spoofing, and denial-of-service attacks on a CAN bus, posing a risk to driving safety. Numerous studies have proposed CAN bus safety improvement techniques that emphasize modifying the original CAN bus method of transmitting frames. These changes place additional computational burdens on electronic control units cause the CAN bus to lose the delay guarantee feature. Consequently, we proposed a method that solves these compatibility and security issues. Simple and efficient frame authentication algorithms were used to prevent spoofing and replay attacks. This method is compatible with both CAN bus and CAN-FD protocols and has a lower operand when compared with other methods.
Digital transformation maturity assessment: development of the digital transformation capability maturity model

The use of on-premises technology in the business environment to create a competitive advantage is ushering in a new era known as digital transformation. Although companies are aware of its potential benefits, they face challenges creating a clear roadmap to reform their existing processes in line with these technologies. Maturity models are developed to assist organisations by providing extensive guidance and a roadmap for improvement. However, as a result of the systematic literature review and its analysis, it was observed that none of the 18 existing maturity models in the digital transformation domain fully satisfies all the criteria of suitability, completeness, clearness, and objectivity. To close this research gap, this study aims to develop a holistic maturity model in the digital transformation domain, entitled DX-CMM, by applying a theoretically grounded development approach, which has so far been neglected despite its remarkable relevance. The purpose of DX-CMM is to assist organisations by providing current capability and maturity determination, deriving a gap analysis, and creating a comprehensive roadmap for improvement in a standardised way. An exploratory case study is also conducted to check the applicability of the model in this study.
Circadian Sleep-Activity Rhythm across Ages in Down Syndrome

Across all ages, individuals with Down syndrome (DS) experience high rates of sleep problems as well as cognitive impairments. This study sought to investigate whether circadian rhythm disruption was also experienced by people with DS and whether this kind of sleep disorder may be correlated with cognitive performance. A cross-sectional study of 101 participants (58 with DS, 43 with typical development) included individuals in middle childhood (6–10 years old), adolescence (11–18 years old), and young adulthood (19–26 years old). Sleep and markers of circadian timing and robustness were calculated using actigraphy. Cognitive and behavioral data were gathered via a novel touchscreen battery (A-MAPTM, Arizona Memory Assessment for Preschoolers and Special Populations) and parent questionnaire. Results indicated that children and adolescents with DS slept the same amount as peers with typical development, but significant group differences were seen in phase timing. The circadian robustness markers, interdaily stability and intradaily variability of sleep-wake rhythms, were healthiest for children regardless of diagnostic group and worst for adults with DS. Amplitude of the 24-h activity profile was elevated for all individuals with DS. In analyses of the correlations between sleep quality, rhythms, and cognition in people with DS, interdaily stability was positively correlated with reaction time and negatively correlated with verbal and scene recall, a finding that indicates increased stability may paradoxically correlate with poorer cognitive outcomes. Further, we found no relations with sleep efficiency previously found in preschool and adult samples. Therefore, the current findings suggest that a thorough examination of sleep disorders in DS must take into account age as well as circadian robustness to better understand sleep-cognitive correlations in this group.
Wave-based active vibration control of a membrane structure

Wave-based active vibration control of a membrane structure by using the Active Sink Method is studied in this paper. Unlike the modal-based vibration control method which attempts to suppress several vibration modes that have already been excited, wave-based active controller can keep vibration modes inactive by stopping the formation of standing waves in the structure. First, the wave transfer matrix is deduced to characterize the wave transmission in the membrane structure. Then, feedforward wave control laws are derived analytically to absorb reflected waves or eliminate transmitted waves. The validity of the proposed active wave controllers is verified through numerical simulations. Simulation results show that by using the active wave controllers no standing waves will be produced in the structure, and the vibration of the membrane structure is suppressed significantly.
Guillain-Barré syndrome in a child with COVID-19 associated multi system inflammatory syndrome

Multi-system inflammatory syndrome in children (MIS-C) associated with SARS-CoV-2 is a new entity affecting a small percentage of children during the COVID-19 pandemic. This usually presents with multi-organ dysfunction, predominantly affecting cardiovascular, muco-cutaneous, and gastrointestinal systems. Till now, neurological manifestations as a part of this spectrum, such as, encephalopathy, inflammatory CNS syndromes, cerebrovascular disease, and Guillain-Barré syndrome (GBS), have been well reported in adults, but there is a paucity of data from the paediatric age group. Here, we present a case of a 6-year-old girl who presented to us with progressive, bilaterally symmetrical ascending weakness of lower limbs followed by upper limbs along with drooling of saliva and dyspnea. Nerve conduction studies showed motor axonal neuropathy suggestive of GBS and child was treated accordingly with intravenous immunoglobulin. On 4th day of admission, the child developed high grade fever spikes, hypotension and diarrhoea. Hence, worked up for MIS-C which revealed elevated inflammatory markers with positive SARS-CoV-19 IgM, IgG antibodies. The diagnosis was hence revised to GBS with MIS-C, the child was then started on methylprednisolone following which the child showed both clinical and biochemical improvement and was then discharged. A high index of suspicion for the possibility of MIS-C should be kept in mind in the present pandemic times, as the immune-mediated damages in MIS-C are potentially treatable with a timely institution of intensive care measures along with the use of steroids, IV-Ig, and plasmapheresis.
Minimizing the Size and Ozone Emission of Electrostatic Precipitators Using Dielectric and Rolled Carbon Film Coatings

Electrostatic precipitators (ESPs) are widely used to control air pollution. However, their applications in portable air cleaners are limited owing to ozone generation during the discharging process. In this article, we developed a compact two-stage ESP that combines corona discharging and particle collection modules. The former generates an extremely small amount of ozone using dielectric film coating, whereas the latter has a large specific surface area. A polypropylene (PP) film is coated as a dielectric material on the ground electrode of the discharging module. The corona current is reduced by the PP film, which in turn reduces the ozone generation. The efficiency of atmospheric particle collection and ozone generation were evaluated by varying the flow rates and applied voltages of the four-channel discharging and roll-type collection modules. Additionally, the specific surface area of 707 m2/m3 of the roll-type collection module minimized the size of the device by increasing its integrity. The proposed ESP with PP coating exhibited the tendency of a conventional ESP that follows the Deutsch equation. All particles of size over 1 μm were removed from the atmosphere by the proposed device at a flow rate of 194.4 L/min, which is more than three times that of human breathing. Furthermore, our experimental device removed more than 50% of the ultrafine particles of size 0.3 μm without ozone generation. Therefore, the proposed device can be potentially used in portable or wearable air-cleaning devices to aid individual healthcare.
Entrepreneurial Leadership and Sustainable Development—A Systematic Literature Review

The main aim of this study was to clarify the current literary inconsistencies regarding the characteristics of entrepreneurial leadership and its impact on sustainability. Additionally, another aim was to establish the framework of entrepreneurial leadership and to highlight the main gaps in the entrepreneurial leadership literature. The entrepreneurial leadership literature started to develop recently as a new leadership style that is required to fulfill the current business changes in the fourth industrial revolution. The researchers conducted a narrative literature review to assess the status of entrepreneurial leadership in academia, literature gaps, and the impact of entrepreneurial leadership on the sustainability performance of organizations. Furthermore, the researchers main aim was to investigate the following research question: is entrepreneurial leadership a fixed or a multidimensional concept that differs based on industry, context, and firm size? Regarding the answer to this question, the current study found that entrepreneurial leadership is a multidimensional concept as it is reflected in different perspectives, which indicates the inconsistency of the characteristics of entrepreneurial leadership claimed in the literature. Research limitations—the current study focused on assessing the literature review status of entrepreneurial leadership. Based on that, this study’s limitation is represented in not focusing on testing entrepreneurial leadership’s impact on sustainability either quantitatively or qualitatively. On the contrary, it contributed by analyzing the status of the entrepreneurial leadership literature. Future studies need to further assess this relationship between both concepts and reach an agreement about the common characteristics of entrepreneurial leadership. Originality/value—the current study contributes to the entrepreneurial leadership literature as it highlighted the existing gaps and the inconsistency in the literature. Additionally, it contributed theoretically by connecting entrepreneurial leadership to the existing literature. Furthermore, empirically, it highlighted the contribution of entrepreneurial leadership by emphasizing the impact of it on organizational sustainable development performance. This study represents a call for scholars to focus more on entrepreneurial leadership given its contribution to organizational performance.
Decoding the transcriptome of denervated muscle at single‐nucleus resolution

Background Skeletal muscle exhibits remarkable plasticity under both physiological and pathological conditions. One major manifestation of this plasticity is muscle atrophy that is an adaptive response to catabolic stimuli. Since the heterogeneous transcriptome responses to catabolism in different types of muscle cells are not fully characterized, we applied single-nucleus RNA sequencing (snRNA-seq) to unveil muscle atrophy related transcriptional changes at single nucleus resolution. Methods Using a sciatic denervation mouse model of muscle atrophy, snRNA-seq was performed to generate single-nucleus transcriptional profiles of the gastrocnemius muscle from normal and denervated mice. Various bioinformatics analyses, including unsupervised clustering, functional enrichment analysis, trajectory analysis, regulon inference, metabolic signature characterization and cell-cell communication prediction, were applied to illustrate the transcriptome changes of the individual cell types. Results A total of 29,539 muscle nuclei (normal vs denervation: 15,739 vs 13, 800) were classified into 13 nuclear types according to the known cell markers. Among these, the type IIb myonuclei were further divided into two subgroups, which we designated as type IIb1 and type IIb2 myonuclei. In response to denervation, the proportion of type IIb2 myonuclei increased sharply (78.12% vs 38.45%, p <0.05). Concomitantly, trajectory analysis revealed that denervated type IIb2 myonuclei clearly deviated away from the normal type IIb2 myonuclei, indicating that this subgroup underwent robust transcriptional reprogramming upon denervation. Signature genes in denervated type IIb2 myonuclei included Runx1, Gadd45a, Igfn1, Robo2, Dlg2, and Sh3d19 (p <0.001). The gene regulatory network analysis captured a group of atrophy-related regulons (Foxo3, Runx1, Elk4, Bhlhe40) whose activities were enhanced (p <0.01), especially in the type IIb2 myonuclei. The metabolic landscape in the myonuclei showed that most of the metabolic pathways were downregulated by denervation (p <0.001), while some of the metabolic signaling, such as glutathione metabolism, was specifically activated in the denervated type IIb2 myonulei. We also investigated the transcriptomic alterations in the type I myofibers, muscle stem cells, fibro-adipogenic progenitors, macrophages, endothelial cells and pericytes and characterized their signature responses to denervation. By predicting the cell-cell interactions, we observed that the communications between myofibers and muscle resident cells were diminished by denervation. Conclusion Our results define the myonuclear transition, metabolic remodeling and gene regulation networks reprogramming associated with denervation-induced muscle atrophy and illustrate the molecular basis of the heterogeneity and plasticity of muscle cells in response to catabolism. These results provide a useful resource for exploring the molecular mechanism of muscle atrophy.
Functional Characterization of the Nep1-Like Protein Effectors of the Necrotrophic Pathogen – Alternaria brassicae

Alternaria brassicae is an important necrotrophic pathogen that infects the Brassicaceae family. A. brassicae, like other necrotrophs, also secretes various proteinaceous effectors and metabolites that cause cell death to establish itself in the host. However, there has been no systematic study of A. brassicae effectors and their roles in pathogenesis. The availability of the genome sequence of A. brassicae in public domain has enabled the search for effectors and their functional characterization. Nep1-like proteins (NLPs) are a superfamily of proteins that induce necrosis and ethylene biosynthesis. They have been reported from a variety of microbes including bacteria, fungi, and oomycetes. In this study, we identified two NLPs from A. brassicae viz. AbrNLP1 and AbrNLP2 and functionally characterized them. Although both AbrNLPs were found to be secretory in nature, they localized differentially inside the plant. AbrNLP2 was found to induce necrosis in both host and non-host species, while AbrNLP1 could not induce necrosis in both species. Additionally, AbrNLP2 was shown to induce pathogen-associated molecular pattern (PAMP)-triggered immunity in both host and non-host species. Overall, our study indicates that AbrNLPs are functionally and spatially (subcellular location) distinct and may play different but important roles during the pathogenesis of A. brassicae.
JAMIA Sept02 I

Web-based three-dimensional Virtual Body Structures (W3D-VBS) is a next-generation immersive anatomical training system for teaching human anatomy over the Internet. It uses Visible Human data to dynamically explore, select, extract, visualize, manipulate, and stereoscopically palpate realistic virtual body structures with a haptic device. Tracking user’s progress through evaluation tools helps customize lesson plans. A self-guided “virtual tour” of the whole body allows investigation of labeled virtual dissections repetitively, at any time and place a user requires it. ■ J Am Med Inform Assoc. 2002;9:425–436. DOI 10.1197/jamia.M1106. BHARTI TEMKIN, ERIC ACOSTA, PAUL HATFIELD, ERHAN ONAL, ALEX TONG
Implementation of a Vaccination Program Based on Epidemic Geospatial Attributes: COVID-19 Pandemic in Ohio as a Case Study and Proof of Concept

Geospatial vaccine uptake is a critical factor in designing strategies that maximize the population-level impact of a vaccination program. This study uses an innovative spatiotemporal model to assess the impact of vaccination distribution strategies based on disease geospatial attributes and population-level risk assessment. For proof of concept, we adapted a spatially explicit COVID-19 model to investigate a hypothetical geospatial targeting of COVID-19 vaccine rollout in Ohio, United States, at the early phase of COVID-19 pandemic. The population-level deterministic compartmental model, incorporating spatial-geographic components at the county level, was formulated using a set of differential equations stratifying the population according to vaccination status and disease epidemiological characteristics. Three different hypothetical scenarios focusing on geographical subpopulation targeting (areas with high versus low infection intensity) were investigated. Our results suggest that a vaccine program that distributes vaccines equally across the entire state effectively averts infections and hospitalizations (2954 and 165 cases, respectively). However, in a context with equitable vaccine allocation, the number of COVID-19 cases in high infection intensity areas will remain high; the cumulative number of cases remained >30,000 cases. A vaccine program that initially targets high infection intensity areas has the most significant impact in reducing new COVID-19 cases and infection-related hospitalizations (3756 and 213 infections, respectively). Our approach demonstrates the importance of factoring geospatial attributes to the design and implementation of vaccination programs in a context with limited resources during the early stage of the vaccine rollout.