Miracle-dz/UniFAR-FTUs huggingface dataset:
Lower pole of patella fractures treated with non-absorbable trans-osseous sutures: an effective surgical method to avoid implant related complications

Background: The treatment option for inferior pole of patella fracture is still being debated. Although tension‑band wiring is the most widely used technique to treat patellar fractures, metal implant‑related complications such as implant failure, palpable hardware are very common and additional procedures are often necessary to treat the complications. The aim of the study was to evaluate the functional results in patients with inferior pole of patella fracture treated by trans-osseous non-absorbable suture fixation.Methods: Patients who underwent trans-osseous suture fixation by no. 5 Ethibond for post-traumatic distal pole patella fracture were included in the study. This was a prospective study conducted at a tertiary care Government Hospital in Kolkata, between December 2018 to May 2020. All patients were followed up at an interval of 2 weeks, 6 weeks, 12 weeks, 6 months and 9 months. Bostman score was used to assess the functional outcomes of the patients.Results: Outcome at final follow-up was assessed with Bostman scoring system. In a total of 11 patients, 8 (72.8%) patients showed excellent and 3 (27.2%) patients had good results during the final follow-up. None of the patients demonstrated unsatisfactory result. At the end of 9 months, the average Bostman score for 11 patients was 27.9. Conclusions: The trans-osseous suturing with non-absorbable sutures is a safe and effective fixation technique for the treatment of distal pole patella fractures. It allows for rapid recovery with minimal implant‑related complications. It also reduces the re-surgery rates significantly.
Dimming control scheme based on hybrid LACO-SCFDM for visible light communications

This paper proposes a hybrid layered asymmetrically clipped optical (HLACO) single-carrier frequency-division multiplexing (SCFDM) scheme for dimmable visible light communication. It designs a signal structure that combines layered asymmetrically clipped optical (LACO)-SCFDM and negative LACO-SCFDM in proportion for improving the inherent weaknesses of orthogonal frequency-division multiplexing (OFDM)-based dimmable schemes and further enhancing the system performance. Compared to the HLACO-OFDM-based dimming scheme, it obtains a lower bit error ratio and enables efficient communication over broader dimming range. Its spectral efficiency realizes 2.875 bit·s−1·Hz−1 within the dimming range of 30%–70%, and the attainable average spectral efficiency gains exceed at least 19.21% compared to other traditional dimmable schemes.
Effect of music on anxiety and pain during ultrasound-guided core needle breast biopsy: a randomized controlled trial.

PURPOSE Although imaging-guided core needle breast biopsy is a minimally invasive diagnostic procedure, it is reported that patients may experience anxiety and pain. Interventions to reduce anxiety are important for high quality health services during imaging-guided core needle breast biopsy. The purpose of this study was to evaluate the effect of music intervention on anxiety and pain levels of patients undergoing ultrasound-guided core needle breast biopsy. METHODS In a prospective randomized controlled design, patients who were referred for ultrasound-guided core needle breast biopsy were invited to the study and randomized into the intervention group who received standard care with classical music intervention before and during the biopsy procedure, and the control group who received only standard care. Both groups received local anesthesia. The Spielberger State-Trait Anxiety Inventory and the Visual Analogue Scale (VAS) were used for measuring anxiety and pain levels after the procedure. One-way multivariate analysis of variance test was used to find the effect of music intervention on patient anxiety and pain. RESULTS There were 31 patients (48.4%) in the intervention group and 33 (51.6%) in the control group; the groups were similar in terms of sociodemographic characteristics and general (trait) anxiety levels. The patients in the music intervention group had significantly lower state anxiety score than the control group (p = 0.008) with a mean difference of 3.8 (95% CI, 1.0-6.6). The mean difference of VAS pain score was 6.0 (95% CI, 2.2-14.2), which not statistically significant between groups (p = 0.150). There was no significant correlation between the VAS and the state anxiety scale (r = 0.003, p = 0.980). CONCLUSION Music reduced anxiety, but not pain during ultrasound-guided core needle breast biopsy. These results have implications especially for low and middle-income countries where low-cost and easily implemented interventions are needed to address patient anxiety during breast biopsy procedures.
Transformer Model Identification by Ārtap: A Benchmark Problem

The paper presents how Ārtap can be used for determining the equivalent circuit parameters of a one phase transformer as a benchmark problem. The following unknown parameters of the equivalent circuit are identified: primary resistance and primary leakage reactance, secondary resistance and secondary leakage reactance, finally magnetizing resistance, and magnetizing reactance. The known quantities from measurement are the primary voltage, primary current, power factor, secondary voltage, and the load resistance. Algorithms implemented in Ārtap are used for determining the transformer parameters and the results are compared with the analytical solution.
A pandemic as the mother of invention? Collegial online collaboration to cope with the COVID-19 pandemic

ABSTRACT This article aims to present how music teachers in Sweden used the facebook group Musiklärarna in the first two months of the COVID-19 pandemic (March andApril, 2020) to cope with challenges related to teaching music. The study is based on Biesta’s perspective on the teacher profession. With the consent of the participants, we have analysed the 303 posts (and their comments) that directly addressed the COVID-19 situation during that period. We found that the group works as an important collegial forum and that the teachers pragmatically use the group to solve educational problems; further, the posts concerning work-conditions get the most engagement. The most frequent types of posts concerned how to design teaching situations under the new conditions. Specifically, asking questions, sharing material, asking for material and letting off steam were the most common types. Music teachers seem to be loyal, collegial and intent on solving any challenge to facilitate students’ learning as regulated in the syllabus. We hope this article can motivate other researchers to perform similar studies or build on our results. We conclude by speculating about what the new normal will be for music teachers when the pandemic is over.
A Case Study on Pathogen Transport, Deposition, Evaporation and Transmission: Linking High-Fidelity Computational Fluid Dynamics Simulations to Probability of Infection

A high-fidelity, low-Mach computational fluid dynamics simulation tool that includes evaporating droplets and variable-density turbulent flow coupling is well-suited to ascertain transmission probability and supports risk mitigation methods development for airborne infectious diseases such as COVID-19. A multi-physics large-eddy simulation-based paradigm is used to explore droplet and aerosol pathogen transport from a synthetic cough emanating from a kneeling humanoid. For an outdoor configuration that mimics the recent open-space social distance strategy of San Francisco, maximum primary droplet deposition distances are shown to approach 8.1 m in a moderate wind configuration with the aerosol plume transported in excess of 15 m. In quiescent conditions, the aerosol plume extends to approximately 4 m before the emanating pulsed jet becomes neutrally buoyant. A dose–response model, which is based on previous SARS coronavirus (SARS-CoV) data, is exercised on the high-fidelity aerosol transport database to establish relative risk at eighteen virtual receptor probe locations.
Analysis of Polygonum Aviculare and Polygonum Maritimum for Minerals by Flame Atomic Absorption Spectrometry (FAAS), Polyphenolics by High-Performance Liquid Chromatography-Electrospray Ionization – Mass Spectrometry (HPLC-ESI-MS), and Antioxidant Properties by Spectrophotometry

Abstract Polygonum aviculare and Polygonum maritimum, commonly known as knotgrass and sea knotgrass, have been widely used for several purposes. Leaves, stems, and roots of these species were evaluated for mineral composition, phytochemical contents, and antioxidant properties. The minerals were characterized by flame atomic absorption spectrometry (FAAS). The polyphenolics were investigated colorimetrically and by high-performance liquid chromatography-electrospray ionization – mass spectrometry (HPLC-ESI-MS). The antioxidant potential was evaluated by total antioxidant capacity (TAC), DPPH-radical scavenging activity, and reducing power (RPA). The mineral contents differed remarkably between and within species. For P. maritimum, the leaves showed the highest sodium, potassium, calcium, and magnesium contents while the roots accumulated the highest iron. The stems of P. aviculare contained higher Na, K, Ca and Fe compared to roots and leaves. P. maritimum extracts contained higher phytochemical contents compared to P. aviculare. The stems and leaves of P. maritimum were the richest in polyphenols and flavonoids while the roots possessed the highest condensed tannins. For P. aviculare, the stems contained the highest phenolics. HPLC-ESI-MS determined 20 phenolics including quinic acid, gallic acid, protocatechuic acid, (+)-catechin, quercetin-3-O-galactoside, and cirsiliol. P. maritimum extracts contained more antioxidants than P. aviculare. The results suggest that the selected species may be important sources of bioactive molecules.
Calcium Carbonate Can Be Used to Manage Soilless Substrate pH for Blueberry Production

Blueberry (Vacciniumcorymbosum interspecific hybrids) production in soilless substrates is becoming increasingly popular. Soilless substrates have low pH buffering capacity. Blueberry plants preferentially take up ammonium, which acidifies the rhizosphere. Consequently, soilless substrates where blueberry plants are grown exhibit a tendency to get acidified over time. Agricultural lime (CaCO3) is commonly used to raise soil and substrate pH in other crops, but it is rarely used in blueberry cultivation. We hypothesized that substrate amendment with low rates of agricultural lime increases substrate pH buffering capacity and provides nutritional cations that can benefit blueberry plants. We tested this hypothesis in a greenhouse experiment with ‘Emerald’ southern highbush blueberry plants grown in rhizoboxes filled with a 3:1 mix of coconut coir and perlite. We found that substrate amendment with CaCO3 did not cause high pH stress. This amendment maintained substrate pH between 5.5 and 6.5 and provided Ca and Mg for plant uptake. When blueberry plants were grown in CaCO3-amended substrate and fertigated with low pH nutrient solution (pH 4.5), they exhibited greater biomass accumulation than plants grown in unamended substrates. These results suggest that low rates of CaCO3 could be useful for blueberry cultivation in soilless substrates.
Investment Differences Between Public and Private Firms: Evidence From U.S. Tax Returns

Abstract Using tax data, we compare the investment behavior of public and private firms for a representative sample of all U.S. corporations. We find that while both types of firms invest similarly in physical capital, public firms out-invest private firms in R&D. Compared to observationally-similar private firms, public firms invest roughly 50% more in R&D relative to their asset bases. Further, public firms dedicate 7.4 percentage points more of their investments to R&D than private firms. This stronger public firm R&D investment is muted when shareholder earnings pressures are heightened, but not so much as to overcome the baseline investment advantage.
Improved synthesis of imatinib mesylate

Objective To obtain the improved synthesis of imatinib mesylate . Methods 4-[(4-methyl-piperazin-1-yl) methyl〗benzoyl chloride dihydrochloride and 4-methyl-N3-[4-(3-pyridyl) pyrimidin-2-yl]-1,3-phenylenediamine were used as starting raw mate-rial to perform a condensation reaction in the aqueous phase to give imatinib free base , which was then neutralized with methanesulfonic acid to obtain the novel antineoplastic tyrosinase inhibitor imatinib mesylate by the use of a two -step reaction . Results The improved syn-thesis was considered to have the advantages of low cost , easy post-processing, high purity, high yield and environmental pollution with the HPLC purity≥99.7%and the single impurity<0.1%. Conclusion The total yield of the novel method was 81.5%, having an e-nough broad industrial production prospect . The targeted compound structure was confirmed by 1 H NMR and ESI-MS.
It’s their fault: Partisan attribution bias and its association with voting intentions

This research examined how people explain major outcomes of political consequence (e.g., economic growth, rising inequality). We argue that people attribute positive outcomes more and negative outcomes less to their own political party than to an opposing party. We conducted two studies, one before the 2016 U.S. presidential election (N = 244) and another before the 2020 election (N = 249 registered voters), that examined attributions across a wide array of outcomes. As predicted, a robust partisan attribution bias emerged in both studies. Although the bias was largely equivalent among Democrats and Republicans, it was magnified among those with more extreme political ideology. Further, the bias predicted unique variance in voting intentions and significantly mediated the link between political ideology and voting. In sum, these data suggest that partisan allegiances systemically bias attributions in a group-favoring direction. We discuss implications of these findings for emerging research on political social cognition.
Application of the dual stream model to neurodegenerative disease: evidence from a multivariate classification tool in primary progressive aphasia

ABSTRACT Background: A clinical diagnosis of primary progressive aphasia relies on behavioral characteristics and patterns of atrophy to determine a variant: logopenic; nonfluent/agrammatic; or semantic. The dual stream model is a contemporary paradigm that has been applied widely to understand brain-behavior relationships; however, applications to neurodegenerative diseases like primary progressive aphasia are limited. Aims The primary aim of this study is to determine if the dual stream model can be applied to a neurodegenerative disease, such as primary progressive aphasia, using both behavioral and neuroimaging data. Methods & Procedures: We analyzed behavioral and neuroimaging data to apply a multivariate classification tool (support vector machines) to determine if the dual stream model extends to primary progressive aphasia. Sixty-four individuals with primary progressive aphasia were enrolled (26 logopenic variant, 20 nonfluent/agrammatic variant, and 18 semantic variant) and administered four behavioral tasks to assess three linguistic domains (naming, repetition, and semantic knowledge). We used regions of interest from the dual stream model and calculated the cortical volume for gray matter regions and white matter structural volumes and fractional anisotropy. We applied a multivariate classification tool (support vector machines) to distinguish variants based on behavioral performance and patterns of atrophy. Outcomes & Results: Behavioral performance discriminates logopenic from semantic variant and nonfluent/agrammatic from semantic variant. Cortical volume distinguishes all three variants. White matter structural volumes and fractional anisotropy primarily distinguish nonfluent/agrammatic from semantic variant. Regions of interest that contribute to each classification in cortical and white matter analyses demonstrate alignment of logopenic and nonfluent/agrammatic variants to the dorsal stream, while the semantic variant aligns with the ventral stream. Conclusions: A novel implementation of an automated multivariate classification suggests that the dual stream model can be extended to primary progressive aphasia. Variants are distinguished by behavioral and neuroanatomical patterns and align to the dorsal and ventral streams of the dual stream model. Application of the dual stream model to PPA
Strategi Komunikasi Pemasaran Produk Kopi Kawa Daun Tanah Datar dalam Membangun Brand Awareness

Kawa daun telah dikenal masyarakat Minangkabau yang syarat akan nilai budaya dan nilai historisnya. Hadirnya industri kreatif, Kopi Kawa Daun sebagai produk Tanah Datar, Sumatera Barat. Selain mencari market yang luas, branding produk menjadi penting untuk pencapaian jangka panjang brand. Desain, pesan, promosi serta komunikasi brand Kopi Kawa Daun, dirancang sedemikian rupa sehingga mencirikan nilai historis dan identik dengan budaya Minangkabau. Komunikasi pemasaran itu sendiri merupakan proses penyampaian pesan dengan cara bujukan atau ajakan untuk menawarkan sebuah produk baik barang atau jasa. Dalam menjalankan strategi pemasaran guna mendapatkan perhatian dan juga kepercayaan konsumen terhadap suatu merek, perusahaan memerlukan media atau saluran yang dapat dijadikan sebagai perantara dalam proses komunikasi antara perusahaan dengan konsumen. Tujuan dari penelitian ini adalah untuk mengetahui dan menganalisis strategi komunikasi pemasaran produk kopi kawa daun Tanah Datar dalam menciptakan brand awareness. Penelitian ini menggunakan metode penelitian yang digunakan adalah kualitatif, dalam pengumpulan data menggunakan wawancara mendalam, observasi dan dokumentasi. Informan dipilih dengan menggunakan teknik purposive sampling. Sementara untuk melihat keabsahan data penelitian ini menggunakan triangulasi sumber.Berdasarkan hasil penelitian diketahui bahwa Komunikasi Pemasaran Kopi Kawa Daun untuk membangun brand awareness konsumen terhadap produk. Brand awareness publik dikategorikan berdasarkan pengalaman publik yaitu pada tahap brand recall dan brand recognition dan berdasarkan brand produk yaitu pada tahap top of mind.
A simple method for predicting emerging SARS-CoV-2 variants using outgroups infecting non-human hosts

The ability to predict emerging variants of SARS-CoV-2 would be of enormous value, as it would enable proactive design of vaccines in advance of such emergence. Based on molecular evolutionary analysis of S protein, we found a significant correspondence in the location of amino acid substitutions between SARS-CoV-2 variants recently emerging and their relatives that infected bat and pangolin before the pandemic. This observation suggests that a limited number of sites in this protein are repeatedly substituted in independent lineages of this group of viruses. It follows, therefore, that the sites of future emerging mutations in SARS-CoV-2 can be predicted by analyzing their relatives (outgroups) that have infected non-human hosts. We discuss a possible evolutionary mechanism behind these substitutions and provide a list of frequently substituted sites that potentially include future emerging variants in SARS-CoV-2.
Distinguishing Personality Recognition and Quantification of Emotional Features Based on Users' Information Behavior in Social Media

The purpose of this paper is to explore the emotional composition, psychological characteristics, and the consistency between information behavior and attitude of social media users, and to provide reference for online public opinion monitoring, topic detection, and emotional situation evaluation. Based on big-five personality theory and self-difference theory, this paper takes 12,151 Twitter texts during Hurricane Maria as the analysis objects, extracts the personality characteristics of the texts based on convolution neural network, and analyzes the subjectivity and emotional polarity of the texts by Python. Based on the experimental results, this paper analyzes the psychological characteristics and information needs reflected by social media users' information behavior in disaster environment and further verifies and expounds the reasons for the inconsistent information behavior and attitude of social media users in disaster environments.
High-speed target tracking algorithm for the pulse-sequence-based image sensor

This paper proposed a high-speed target tracking algorithm based on the pulse-sequence-based image sensor. The algorithm separates the target from the background through the statistical distribution of the pulses in a single frame of data. In order to achieve more accurate target tracking, the phenomenon of image lag in the process of capturing the high-speed moving target is studied. The positioning deviation is compensated by estimating the image lag length of the moving target. The algorithm is implemented with pipeline processing on ﬁeld-programmable gate array (FPGA). The positioning accuracy of the algorithm is veriﬁed with input data from a pulse-sequence image sensor model. The veri-ﬁcation results show that the maximum position deviation of the target at different speeds is 0.94 pixels. In the experiment of tracking a 40 m/s moving ball, this algorithm can provide real-time position information within 44 ns.
Exploring How Public Libraries Can Build Situational Interest in Science

Abstract This project aimed to cultivate library patrons’ interest in earth and space science, using research on how situations can trigger and support interest to deepen across time. The project featured a dynamic but low-tech library display that showcased thematic content to help patrons realize and develop their interest in earth and space science topics. Patrons engaged with and returned regularly to the display, which predicted their participation in additional activities outside of viewing the display, indicating deepening interest. This approach uses a passive program to help libraries build patrons’ interest in accessing science resources and programs.
Efficient seismic ray tracing based on the shortest path method

Limiting the number of valid nodes around a reference ray can greatly reduce the calculation time of the shortest-path method (SPM). The calculation is executed by increasing the number of cells and/or nodes in the target area, step by step, until the rays converge. The ray obtained in the previous step is used as a reference ray, and the initial reference rays are given by the ordinary SPM. The Dijkstra algorithm and binary heap sorting method are used, as in the ordinary SPM. As the cell and node numbers increase, the calculation time for the modified SPM (mSPM) is reduced compared to that for the ordinary SPM. In the 3-D (100 × 100 × 100 km3) checkerboard velocity pattern model, the relative calculation time becomes two to four orders of magnitude smaller. The calculation time for the mSPM itself is approximately proportional to E log2(V), where E is the edge (ray path segment) number and V is the vertex (node) number, as seen in the heap sorting algorithm. The mean traveltime and ray path differences between the mSPM and pseudo-bending method (PBM) are small, less than 0.005 s and around 0.6 km, respectively, and slightly larger than those with respect to the ordinary SPM. The total differences from the exact solution are estimated to be less than 0.01 s and 1.0 km, which are sufficiently small for traveltime tomography. The traveltime and ray path can be improved by utilizing iterative calculations, shifting of the starting point and more neighbour nodes. The ray path obtained by the mSPM can be a local minimum, according to velocity models. The relative mean traveltime and ray path differences between adjacent cells and nodes generally show trends similar to those of the traveltime and ray path differences from the PBM. Hence, these relative differences can help reveal the behaviour of the differences from the PBM.