Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on shoreline identification method based on partition fitting evaluation strategy

In the unknown water environment, unmanned ships’ perception of unknown water environment, map construction, and identification and ranging of obstacles have become research hotspots in the field of water environment perception. The visual SLAM (simultaneous localization and mapping) scheme is used to obtain the unmanned ship’s navigational waters to obtain the unknown waters environment. The mathematical model is established based on the feature points extracted by the ORB-SLAM2 algorithm, that is, the feature point coordinates are extracted to establish a coordinate system, and the lowest point coordinates are used as the starting point to assume the shoreline, and the shoreline After the upper and lower feature points are partitioned, the feature points in the area above the shoreline are curve-fitted, and then the reflection curve is obtained according to the reflection principle, and finally the variance calculation is performed on the points in the reflection curve and the points in the area below the shoreline. When the variance is the smallest value or Get the shoreline position when it is zero. The results show that the method can accurately identify the location of the shoreline and lay the foundation for the unmanned ship to realize surface target recognition.
Design of a mid-infrared single-mode laser based on parity-time symmetry breaking in air-clad hollow-core ZBLAN fiber micro-resonator

In this paper, we propose a single-mode laser operating in the mid-infrared regime by exploiting parity-time (PT) breaking in a whispering gallery mode (WGM) micro-resonator based on air-clad hollow-core ZBLAN fibers. By introducing alternate gain–loss modulation regions with refractive indices respectively having the same real parts but opposite imaginary parts into the air hole clad region of the hollow-core fiber infiltrated with optical functional materials, a PT symmetry system could be set up and specific WGM in PT-broken state whose electric field distribution matches the gain–loss modulation pattern can be excited to realize single-mode laser emission around 5 μm. And moreover, simulation results indicate that high precision laser wavelength tuning with a sensitivity of 1.623 nm RIU−1 can be achieved by adjusting the refractive index of the functional materials filled into the cladding air holes.
Robust signal recovery for ℓ 1–2 minimization via prior support information

In this paper, a theoretical analysis on the signal recovery is provided by weighted ℓ 1–2 minimization when partial support information is available. We establish a sufficient condition for the weighted ℓ 1–2 minimization, which in absence of prior support information is proved to be much better than the state-of-the-art one. In particular, if at least 50% of the estimated support information is accurate, the sufficient condition is weaker than the analogous one of the standard ℓ 1–2 minimization. In addition, a series of numerical experiments are conducted by the modified DCA-ℓ 1–2 method to support the performance of weighted ℓ 1–2 minimization. The excellent recovery performance of weighted ℓ 1–2 minimization is showed compared with the state-of-the-art weighted ℓ 1 minimization and weighted ℓ q (0 < q < 1) minimization when the measurement matrix is highly coherent.
The Effect of Skilled Labor Intensity on Corporate Dividend Payouts

This study shows that skilled-labor-intensive firms have lower dividend payouts. A one-standard-deviation increase in skilled labor intensity on average results in a 0.74 percentage point decline in the propensity to pay dividends and a 0.72 percentage point decrease in dividend payout ratio. Our evidence suggests that greater labor adjustment costs (LACs) of skilled labor increase future cash flow uncertainty, which discourages managers from paying dividends. Consistently, we find that an exogenous increase (decrease) in LACs following the shock of 2017 H-1B policy changes (the shock of 2005 Hurricane Katrina) leads treated firms to lower (heighten) their dividend payouts. Collectively, these findings indicate a strong dampening effect of LACs on corporate dividend payouts.
Application of Life Cycle Assessment and Similar Methodologies in Asset Management: A Multiple Case Study

Life Cycle Thinking (LCT) methodologies are increasingly adopted by Asset Management (AM) organizations to assess the sustainability impact of decisions in policy-making and strategic planning. Despite the adoption of these methodologies, in particular the Life Cycle Assessment (LCA), operationalization of the outcomes seems to lack attention in industry and research. This research aims to explore and better understand the application of LCT outcomes in AM decision-making. An exploratory literature review shows that the current LCT research strongly focuses on LCT as a method and methodological improvement to advance the adoption of the method, while the application of the LCT outcomes receives less attention. Based on the literature review a number of postulates were formulated and tested in an exploratory multiple case study at various AM organizations in the Netherlands, in which LCT has been adopted. Comparing these postulates with empirical findings indicates fundamental differences between LCT theory and practice, which seem to limit the application of the LCT outcomes. The research reveals that more attention is needed on the assistance in the operationalization of LCT outcomes. Furthermore, practitioners should consider redirecting some efforts from improving the analysis itself towards the operationalization of the LCT outcomes.
Physician Entrepreneurship: Understanding Medical Startups from Ideation, Innovation to IPO

We live in extraordinary times where new healthcare innovations require novel ideas and requisite capital funding to commercialize products and services beyond the idea phase. Stalled innovations within the US healthcare sector have diminished the physician-patient health encounter. In response to this urgent-to-resolve challenge, many physicians have opted to become medical entrepreneurs to take on a portion of innovative healthcare delivery. In our study, we focus attention on empirical evidence that answers the research question: How do physician entrepreneurs navigate medical startups from ideation, innovation to IPO? We sought to theoretically test effectuation theory of entrepreneurship as a decision-making framework that can be used by physician entrepreneurs. We designed a qualitative multi-case study research method to answer the research question. This method was best suited to capture rich descriptive data, contexts, quality or meanings, processes, and human experiences of physician entrepreneurs. There are three expected contributions towards knowledge accumulation on physician entrepreneurship, medical startups, and venture capital funding: exclusive processes, insights into decision-making, and understandings of quality or meaning of lived experiences that illuminate interesting insights. This study amplifies personal voice through subjective perspectives of physician entrepreneurs that might not be heard elsewhere.
High-Order Expansion Based Saddlepoint Approximation Errors of the Heston Stochastic Volatility Model

The Fourier inversion method solves the Heston option pricing formula. However, this method does experience the noteworthy disadvantage of a computationally sedate solution process. As a result, the literature introduces faster approximations with accuracies later improved by the joint application of a transform deriving a Saddlepoint Approximation. The Saddlepoint Approximation method has various successful applications in statistics and mathematical finance. Among which option pricing in the Heston model resides. This paper investigates the quality of this Saddlepoint Approximation for high expansion orders and thereby the diversification of the solution method. The functional run-time performance and applicability are not a prioritized concern.
Predicting psoriasis using routine laboratory tests with random forest

Psoriasis is a chronic inflammatory skin disease that affects approximately 125 million people worldwide. It has significant impacts on both physical and emotional health-related quality of life comparable to other major illnesses. Accurately prediction of psoriasis using biomarkers from routine laboratory tests has important practical values. Our goal is to derive a powerful predictive model for psoriasis disease based on only routine hospital tests. We collected a data set including 466 psoriasis patients and 520 healthy controls with 81 variables from only laboratory routine tests, such as age, total cholesterol, HDL cholesterol, blood pressure, albumin, and platelet distribution width. In this study, Boruta feature selection method was applied to select the most relevant features, with which a Random Forest model was constructed. The model was tested with 30 repetitions of 10-fold cross-validation. Our classification model yielded an average accuracy of 86.9%. 26 notable features were selected by Boruta, among which 15 features are confirmed from previous studies, and the rest are worth further investigations. The experimental results demonstrate that the machine learning approach has good potential in predictive modeling for the psoriasis disease given the information only from routine hospital tests.
Genome-Wide Association Mapping Identifies Novel Panicle Morphology Loci and Candidate Genes in Sorghum

Panicle morphology is an important trait in racial classification and can determine grain yield and other agronomic traits in sorghum. In this study, we performed association mapping of panicle length, panicle width, panicle compactness, and peduncle recurving in the sorghum mini core panel measured in multiple environments with 6,094,317 single nucleotide polymorphism (SNP) markers. We mapped one locus each on chromosomes 7 and 9 to recurving peduncles and eight loci for panicle length, panicle width, and panicle compactness. Because panicle length was positively correlated with panicle width, all loci for panicle length and width were colocalized. Among the eight loci, two each were on chromosomes 1, 2, and 6, and one each on chromosomes 8 and 10. The two loci on chromosome 2, i.e., Pm 2-1 and Pm 2-2, were detected in 7 and 5 out of 11 testing environments, respectively. Pm 2-2 colocalized with panicle compactness. Candidate genes were identified from both loci. The rice Erect Panicle2 (EP2) ortholog was among the candidate genes in Pm 2-2. EP2 regulates panicle erectness and panicle length in rice and encodes a novel plant-specific protein with unknown functions. The results of this study may facilitate the molecular identification of panicle morphology-related genes and the enhancement of yield and adaptation in sorghum.
Orthopaedic Surgery Residency Program Social Media Presence During the COVID-19 Pandemic

Background: In light of away rotation and in-person interview cancellations for the 2020 to 2021 application cycle, social media has become a popular tool for orthopaedic surgery residency programs to highlight their strengths, curricula, and social life to prospective applicants. The authors sought to explore the proliferation and utilization of 3 popular social media platforms by both orthopaedic surgery departments and residencies. Methods: Orthopaedic surgery departmental and residency program social media accounts and their creation dates across Facebook, Twitter, and Instagram were identified using a standardized search methodology. Residency Instagram accounts were further evaluated for the number of posts, followers, likes, and comments. Both departments and residency programs were cohorted by affiliation with a US News &World Report (USNWR) top 50 American hospital for orthopaedics or by status as a Doximity top 20 program based on reputation. Results: Across a total of 192 residency programs included for analysis, Instagram was the most popular social media platform (61.5%), followed by Twitter (19.8%) and Facebook (10.4%). Conversely, orthopaedic departments more frequently used Facebook (33.9%) and Twitter (28.1%) over Instagram (17.2%). Of the 118 residency Instagram accounts, 102 (86.4%) were created after the onset of the COVID-19 pandemic. Larger residency programs (≥6 spots/year) and those programs in the Doximity top 20 or affiliated with USNWR top 50 orthopaedic hospitals had a greater number of followers as well as likes and comments per post (p < 0.05 for all). Conclusions: Given the recruitment challenges faced by residency programs because of the COVID-19 pandemic, Instagram has rapidly become a prominent platform for attracting orthopaedic surgery applicants. These accounts have a large number of followers, particularly for residency programs with higher Doximity reputation rankings.
Functional Integration of Adult-Generated Neurons in Diabetic Goto-Kakizaki Rats

Adult-born neurons in the dentate gyrus (DG) make important contributions to learning as they integrate into neuronal networks. Neurogenesis is dramatically reduced by a number of conditions associated with cognitive impairment, including type 2 diabetes mellitus (T2DM). Increasing neurogenesis may thus provide a therapeutic target for ameliorating diabetes-associated cognitive impairments, but only if new neurons remain capable of normal function. To address the capacity for adult-generated neurons to incorporate into functional circuits in the hyperglycemic DG, we measured Egr1 expression in granule cells (GCs), BrdU labeled four weeks prior, in Goto-Kakizaki (GK) rats, an established model of T2DM, and age-matched Wistars. The results indicate that while fewer GCs are generated in the DG of GK rats, GCs that survive readily express Egr1 in response to spatial information. These data demonstrate that adult-generated GCs in the hyperglycemic DG remain functionally competent and support neurogenesis as a viable therapeutic target.
Pharmacological Inhibition of Inositol-Requiring Enzyme 1α RNase Activity Protects Pancreatic Beta Cell and Improves Diabetic Condition in Insulin Mutation-Induced Diabetes

β-cell ER stress plays an important role in β-cell dysfunction and death during the pathogenesis of diabetes. Proinsulin misfolding is regarded as one of the primary initiating factors of ER stress and unfolded protein response (UPR) activation in β-cells. Here, we found that the ER stress sensor inositol-requiring enzyme 1α (IRE1α) was activated in the Akita mice, a mouse model of mutant insulin gene-induced diabetes of youth (MIDY), a monogenic diabetes. Normalization of IRE1α RNase hyperactivity by pharmacological inhibitors significantly ameliorated the hyperglycemic conditions and increased serum insulin levels in Akita mice. These benefits were accompanied by a concomitant protection of functional β-cell mass, as shown by the suppression of β-cell apoptosis, increase in mature insulin production and reduction of proinsulin level. At the molecular level, we observed that the expression of genes associated with β-cell identity and function was significantly up-regulated and ER stress and its associated inflammation and oxidative stress were suppressed in islets from Akita mice treated with IRE1α RNase inhibitors. This study provides the evidence of the in vivo efficacy of IRE1α RNase inhibitors in Akita mice, pointing to the possibility of targeting IRE1α RNase as a therapeutic direction for the treatment of diabetes.
Effectiveness of lumbar support with built-in massager system on spinal angle profiles among high-powered traffic police motorcycle riders: A randomised controlled trial

Traffic police riders are exposed to prolonged static postures causing significant angular deviation of the musculoskeletal, including the lumbar angle (L1-L5). This postural alteration contributes to awkward posture, musculoskeletal disorders and spinal injury, especially in the lower back area, as it is one of the most severe modern diseases nowadays. Thus, the study aimed to evaluate the effect of lumbar support with a built-in massager system on spinal angle profiles among traffic police riders. A randomised controlled trial (pre-testpost-test control design) was used to assess spinal angle pattern while riding the high-powered motorcycle for 20 minutes. Twenty-four traffic police riders were randomly selected to participate and 12 riders were assigned to the control group and 12 riders to the experimental group. The pre-test and post-test were conducted at a one-week interval. Each participant was required to wear a TruPosture Smart Shirt (to monitor spinal posture). The TruPosture Apps recorded the spinal angle pattern. The data indicated that the police riders using motorcycle seat with lumbar support and built-in massager system showed a huge improvement in maintaining posture which only involves slight spinal angle deviation changes from the spinal reference angle throughout the 20 minutes ride. The data collected then were analysed using the Mann-Whitney test and Wilcoxon signed-ranked test to verify a statistically significant difference between and within the control and experimental groups. There were significant differences in all sensors between the control group and experimental groups (p<0.05) and within the experimental group. According to the findings, it can be said that the ergonomic intervention prototype (lumbar support with built-in massager system) successfully helps to maintain and improve the natural curve of the spinal posture. This indirectly would reduce the risk of developing musculoskeletal disorders and spinal injury among traffic police riders.
Pain assessment in horses using automatic facial expression recognition through deep learning-based modeling

The aim of this study was to develop and evaluate a machine vision algorithm to assess the pain level in horses, using an automatic computational classifier based on the Horse Grimace Scale (HGS) and trained by machine learning method. The use of the Horse Grimace Scale is dependent on a human observer, who most of the time does not have availability to evaluate the animal for long periods and must also be well trained in order to apply the evaluation system correctly. In addition, even with adequate training, the presence of an unknown person near an animal in pain can result in behavioral changes, making the evaluation more complex. As a possible solution, the automatic video-imaging system will be able to monitor pain responses in horses more accurately and in real-time, and thus allow an earlier diagnosis and more efficient treatment for the affected animals. This study is based on assessment of facial expressions of 7 horses that underwent castration, collected through a video system positioned on the top of the feeder station, capturing images at 4 distinct timepoints daily for two days before and four days after surgical castration. A labeling process was applied to build a pain facial image database and machine learning methods were used to train the computational pain classifier. The machine vision algorithm was developed through the training of a Convolutional Neural Network (CNN) that resulted in an overall accuracy of 75.8% while classifying pain on three levels: not present, moderately present, and obviously present. While classifying between two categories (pain not present and pain present) the overall accuracy reached 88.3%. Although there are some improvements to be made in order to use the system in a daily routine, the model appears promising and capable of measuring pain on images of horses automatically through facial expressions, collected from video images.
The Risk of Iatrogenic Hypercalcemia in Patients Undergoing Calcium Sulphate Beads Implantation in Prosthetic Joint Surgery: A Systematic Review

Calcium sulphate beads are increasingly being used in the management of prosthetic joint infections (PJI). Traditionally their use was limited to a void or dead space-filling combined with other additives such as Hydroxyapatite. Over the last decade, they have been developed to act more frequently as an antibiotics delivery system. Stimulan, a bio-absorbable form of Calcium sulfate, theoretically has an increased risk of hypercalcemia. Over the last few years, there have been published case reports which report it as an isolated cause of iatrogenic hypercalcemia. The sparsity of literature on this topic makes it difficult for surgeons to decide on the use of Calcium sulphate beads in patients with hypercalcemia predisposition in conditions like autoimmune disorders, sarcoidosis, malignancy, granulomatous diseases, heterotopic ossification, and hyperparathyroidism. The study was performed to assess the risk of hypercalcemia in patients after Calcium sulphate beads implantation in PJI. Two reviewers searched relevant literature in 3 online databases using cochrane methodology for systematic reviews. Studies reporting complications with the use of calcium sulphate beads in prosthetic joints were included. Studies reporting on less than five patients and studies reporting use in any other surgeries were excluded. The search of databases resulted in a total of 96 articles. After screening, a total of four articles were deemed suitable to be included in the analysis. A total of 1049 patients underwent calcium sulfate beads implantation, out of which 44 (4.2%) reported hypercalcemia with 41 (3.91%) transient in nature and 3 (0.28%) required management, including one with ICU admission. The result of this systematic review shows that calcium sulphate beads are safe and effective against PJI. There is a significant risk of transient hypercalcemia in susceptible patients and a low risk of symptomatic hypercalcemia.
Lethal Interactions of SARS-CoV-2 with Graphene Oxide: Implications for COVID-19 Treatment

The rapid transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-driven infection signifies an ultimate challenge to global health, and the development of effective strategies for preventing and/or mitigating its effects are of the utmost importance. In the current study, an in-depth investigation for the understanding of the SARS-CoV-2 inactivation route using graphene oxide (GO) is presented. We focus on the antiviral effect of GO nanosheets on three SARS-CoV-2 strains: Wuhan, B.1. 1.7 (U.K. variant), and P.1 (Brazilian variant). Plaque assay and real-time reverse transcription-polymerase chain reaction (RT-PCR) showed that 50 and 98% of the virus in a supernatant could be cleared following incubation with GO (100 μg/mL) for 1 and 60 min, respectively. Transmission electron microscopy (TEM) analysis and protein (spike (S) and nucleocapsid (N) proteins) decomposition evaluation confirm a two-step virus inactivation mechanism that includes (i) adsorption of the positively charged spike of SARS-CoV-2 on the negatively charged GO surface and (ii) neutralization/inactivation of the SARS-CoV-2 on the surface of GO through decomposition of the viral protein. As the interaction of S protein with human angiotensin-converting enzyme 2 (ACE2) is required for SARS-CoV-2 to enter into human cells, the damage to the S protein using GO makes it a potential candidate for use in contributing to the inhibition of the worldwide spread of SARS-CoV-2. Specifically, our findings provide the potential for the construction of an effective anti-SARS-CoV-2 face mask using a GO nanosheet, which could contribute greatly to preventing the spread of the virus. In addition, as the effect of surface contamination can be severe in the spreading of SARS-CoV-2, the development of efficient anti-SARS-CoV-2 protective surfaces/coatings based on GO nanosheets could play a significant role in controlling the spread of the virus through the utilization of GO-based nonwoven cloths, filters, and so on.