Miracle-dz/UniFAR-FTUs huggingface dataset:
A Rare Case of Giant Cavernous Hemangioma of the Maxillary Sinus

Patient: Male, 32-year-old Final Diagnosis: Cavernous hemangioma Symptoms: Epistaxis • facial asymmetry • nasal obstruction Medication: — Clinical Procedure: — Specialty: Otolaryngology Objective: Rare disease Background: Hemangiomas are commonly located in the head and neck and rarely in the paranasal sinuses. These are benign vascular lesions, but with an increased risk of bleeding. The surgical approach must have detailed prior planning, given the increased risk of intraoperative bleeding. We herein describe the case of a 32-year-old male patient with recurrent epistaxis, nasal obstruction, and facial deformity due to a giant cavernous hemangioma successfully treated by endoscopic sinus surgery. Case Report: A 32-year-old man had nasal obstruction and intermittent epistaxis for 2 months. Physical examination also revealed facial deformity with enlargement of the nasal base and bulging in the maxillary region on the right. A soft and friable lesion occupying the entire right nasal cavity without bone erosion was observed on computed tomography (CT scan). Before surgery, the patient underwent angiographic evaluation, with evidence of main irrigation of the lesion by the right maxillary artery, which was then embolized. The patient underwent endoscopic nasal surgery. He maintained postoperative follow-up for 18 months, without recurrence of the lesion. Anatomopathological examination confirmed a cavernous hemangioma. Conclusions: Cavernous hemangioma is a benign lesion of the paranasal sinuses. Due to non-specific clinical and radiological findings, its preoperative diagnosis is always challenging. The high index of suspicion of the malignancy should only be discarded after complete anatomopathological evaluation. A correct diagnosis is essential to avoid facial anatomical remodeling while excluding the diagnosis of other malignant lesions.
The boundaries of meaning: a case study in neural machine translation

The success of deep learning in natural language processing raises intriguing questions about the nature of linguistic meaning and ways in which it can be processed by natural and artiﬁcial systems. One such question has to do with subword segmentation algorithms widely employed in language modeling, machine translation, and other tasks since 2016. These algorithms often cut words into semantically opaque pieces, such as ‘period’, ‘on’, ‘t’, and ‘ist’ in ‘period | on | t | ist’. The system then represents the resulting segments in a dense vector space, which is expected to model grammatical relations among them. This representation may in turn be used to map ‘period | on | t | ist’ (English) to ‘par | od | ont | iste’ (French). Thus, instead of being modeled at the lexical level, translation is reformulated more generally as the task of learning the best bilingual mapping between the sequences of subword segments of two languages; and sometimes even between pure character sequences: ‘p | e | r | i | o | d | o | n | t | i | s | t | ’ → ‘p | a | r | o | d | o | n | t | i | s | t | e’. Such subword segmentations and alignments are at work in highly eﬃcient end-to-end machine translation systems, despite their allegedly opaque nature. The computational value of such processes is un-questionable. But do they have any linguistic or philosophical plausibility? I attempt to cast light on this question by reviewing the relevant details of the subword segmentation algorithms and by relating them to important philosophical and linguistic debates, in the spirit of making artiﬁcial intelligence more transparent and explainable. Translation of some words is transparent in that they are translatable by a competent translator even if they are novel to him or her, based on a translation of known subword units such as morphemes or phonemes. Our hypothesis is that a segmentation of rare words into appropriate subword units is suﬃcient to allow for the neural translation network to learn transparent translations, and to generalize this knowledge to translate and produce unseen words (Sennrich, Haddow, and Birch 2016, 1716).
The Role of Courtyards within Acute Mental Health Wards: Designing with Recovery in Mind

The role of courtyards and other outdoor spaces in the recovery of acute mental healthcare users has been gaining international appreciation and recognition. However, the physical properties and conditions necessary for therapeutic and rehabilitative engagement remain to be clearly established. This paper contributes to that knowledge by triangulating evidence from the literature, exemplar case studies of good practice and first-hand accounts of the experiences of staff and service users from four acute mental health facilities. The findings are then aligned with a well-established recovery framework (CHIMES) in light of existing landscape architecture knowledge. Within the complexity of varied mental health environments, this work establishes landscape architectural design requirements and qualities essential for recovery. Rather than adopting a prescriptive quantitative approach setting out areas, numbers of elements, etc., the proposed framework recommends a performance-based model and the creation of a cohesive network of microspaces that mesh into a design of outdoor areas. In this way, design details, materials, vegetation and the variety of spaces can be modified to suit service user population demographics and site-specific needs.
Bidirectional Constant Current String-to-Cell Battery Equalizer Based on L2C3 Resonant Topology

In battery equalization systems, equalization speed, control complexity, and length of energy flow path are the important figures of merits. This article presents a novel bidirectional L2C3 resonant converter in a unique equalizer architecture with constant balancing current and fixed frequency control. The constant balancing current can be customized to achieve a stable balancing speed. The common equalizer unit transfers power bidirectionally between the entire string and any single cell. Design considerations of L2C3-based bidirectional equalizer are analyzed in detail, which ensures zero-voltage switching among all mosfets during the equalization process. The circuit is designed with synchronous rectification using the first harmonics approximation. The key contributions of this article include: a new bidirectional resonant topology for battery equalization; bidirectional constant current balancing with open-loop control; simplified synchronous rectification. An equalizer prototype with four lithium-ion battery cells at a balancing current of 500 mA is built and tested. The L2C3 circuit operates at 200 kHz with a peak efficiency of 89.4% and 90.1% under two balancing modes. Experimental results show the proposed scheme exhibits outstanding balancing performance.
A Crystal-Less Clock Generation Technique for Battery-Free Wireless Systems

The size of wireless systems is required to be reduced in many applications, such as ultra-low-power sensor nodes and wearable/implantable devices, where battery and crystal are the two main bottlenecks in system miniaturization. In recent years, battery-free radios based on wireless power transfer (WPT) have shown great potential in miniature wireless systems, while a reliable on-chip clock without a crystal remains a design challenge. Conventional methods utilized the RF WPT tone as the reference for clock generation, but the high RF frequency leads to high power consumption. In comparison, using a lower WPT frequency results in an antenna with a larger size. In this work, the $2^{\mathrm{nd}}$ -order inter-modulation (IM2) component of the two RF WPT tones is extracted to lock an on-chip oscillator, providing a low-jitter PVT-robust clock. In this way, the wireless systems can benefit from: 1) The clock recovery circuits operate at a low IM2 frequency, reducing the power consumption. 2) The WPT can be set to a high RF frequency to minimize the antenna. Fabricated in 65 nm CMOS process, the proposed crystal-less clock generator takes a small area of 0.023 mm2 in a wireless system chip. Measured results show −92 dBc/Hz@10 kHz phase noise and 6.8 $\mu \text{W}$ power.
Homoclinic Orbits of Planar Maps: Asymptotics and Mel'nikov Functions

Homoclinic orbits to saddle fixed points of planar diffeomorphisms generically imply complicated dynamics due to Smale Horseshoes. Such orbits can be computed only numerically, which is time-consuming. The aim of this project is to explore an alternative method to compute homoclinic orbits near degenerate fixed points of codimension 2 with a double multiplier 1. The method will be based on approximating the map near the bifurcation by the time-1-shift along orbits of a planar ODE and evaluating the Mel’nikov function along its homoclinic loop. Zeroes of this Mel’nikov function are intersections of the stable and unstable manifold and will approximate the homoclinic orbit. The main part of this project is devoted to the derivation of a prediction for both the homoclinic orbit and the homoclinic bifurcation curve in the case of the normal form of 1:1 resonance.
Green Synthesis and Study of Biological Activity of New Benzopyrimidoazepines: Reduction of Organic Pollutants Using Synthesized Fe3O4/TiO2/CuO@MWCNTs MNCs

Abstract In this work rhizome of Petasites hybridus was used for preparing water extract and utilized as green media for generating Fe3O4/TiO2/CuO@ Multi-Walled Carbon Nanotubes (MWCNTs) magnetic nanocomposites and its activity was evaluated by using in the one-pot multicomponent reactions (MCRs) of anilines, diethyl oxalate, activated acetylenic compounds, α-haloketones, ammonium acetate and aroyle(alkaloyl)isocyanates in aqueous at room temperature to produce of novel benzopyrimidoazepine derivatives in excellent yields. Moreover, the reduction of organic pollutants such 4-nitrophenol (4-NP) was performed by synthesized Fe3O4/TiO2/CuO@MWCNTs in H2O at room temperature. The outcomes showed this catalyst was decreased organic contaminants in the low time. The generated benzopyrimidoazepines have hydroxyl and two NH functional groups that have acidic hydrogen and show high antioxidant activity. The antioxidant activity order of some synthesized compounds was as TBHQ ≈ BHT>7b>7d>7c>7a. Also, antimicrobial ability of obtained benzopyrimidoazepines was investigated with the disk diffusion method, and two Gram-negative and Gram-positive bacteria and compounds 7b, 7c, 7e, and 7g have maximum effect on Escherichia coli relative to Gram positive and negative bacteria due to good diameter of inhibition zone. The short time of reactions, excellent efficiency of product, easy separation of catalyst and products employed process to the synthesis of benzopyrimidoazepines are some advantages of this procedure. HIGHLIGHTS Green chemistry is the use of a set of principles to reduce or eliminate the use or generation of unsafe materials in the design, fabrication, and applications of chemical products. Among solvents, water is a green solvent and very suitable for performing the organic reaction. The present procedure avoids the use of toxic solvents. Heterocyclic compounds hold a prominent position in medicinal chemistry owing to their wide spectrum of biological activities, such as antimalarial, antimicrobial, antitumor, anticancer, antidepressant, antiviral, antidiabetic, anti-inflammatory, and anti-HIV. The benzoazepine skeleton is a famous pharmacophore that is existed in several behavioral disorder drugs, such as imipramine, diazepam, and lorazepam. Graphical Abstract
Chemical Characterization for the Detection of Impurities in Tainted and Natural Curcuma longa from India Using LIBS Coupled with PCA

The present manuscript explores a spectroscopic technique to select turmeric powder, free from impurities, and has compounds of medicinal importance among the tainted and natural turmeric. Six Curcuma longa (turmeric powder) samples, named S1, S2, S3, S4, S5, and S6, were analyzed to discriminate between tainted and natural turmeric using the LIBS and multivariate technique. Other techniques such as UV–Vis, FTIR, and EDX are also used to ascertain the elements/compounds showing the medicinal properties of C. longa. Spectral lines of carbon, sodium, potassium, magnesium, calcium, iron, strontium, barium, and electronic bands of CN molecules were observed in the LIBS spectra of turmeric samples. Spectral signatures of toxic elements such as lead and chromium are also observed in the LIBS spectra of all samples except S6. Adulteration of metanil yellow, a toxic azo dye, is used to increase the appearance of curcumin when the actual curcumin content is low. The presence of spectral lines of lead and chromium in the LIBS spectra of S1 to S5 suggested that it may be adulterated with lead chromate which is used for coloring turmeric. Further, the presence of sulfur in EDX analysis of sample S5 indicates that it may also have been adulterated with metanil (C18H14N3NaO3S). The concentration of samples’ constituents was evaluated using CF-LIBS, and EDX was used to verify the results obtained by CF-LIBS. The principal component analysis applied to the LIBS data of the turmeric samples has been used for instant discrimination between the sample based on their constituents. We also analyzed antioxidant activity and total phenolic and flavonoid content of different turmeric samples and found a negative Pearson correlation with heavy metals. The presence of curcumin in turmeric is confirmed using LIBS and UV–Vis, which have medicinal properties.
Cooperative Job Scheduling and Data Allocation in Data-Intensive Parallel Computing Clusters

In data-intensive parallel computing clusters, it is important to provide deadline-guaranteed service to jobs while minimizing resource usage (e.g., network bandwidth and energy). Under the current computing framework (that first allocates data and then schedules jobs), in a busy cluster with many jobs, it is difficult to achieve high data locality (hence low bandwidth consumption), deadline guarantee, and high energy savings simultaneously. We model the problem to simultaneously achieve these three objectives using integer programming. Due to the NP-hardness of the problem, we propose a heuristic Cooperative job Scheduling (CSA) and data Allocation method. CSA novelly reverses the order of data allocation and job scheduling in the current computing framework. Job-scheduling-first enables CSA to proactively consolidate tasks with more common requested data to the same server when conducting deadline-aware scheduling, and also consolidate the tasks to as few servers as possible to maximize energy savings. This facilitates the subsequent data allocation step to allocate a data block to the server that hosts most of this data's requester tasks, thus maximally enhancing data locality. To achieve the tradeoff between data locality and energy savings with specified weights, CSA has a cooperative recursive refinement process that recursively adjusts the job schedule and data allocation schedule. We further propose two enhancement algorithms (i.e., minimum k-cut data reallocation algorithm and bipartite based task reassignment algorithm) to further improve the performance of CSA through additional data reallocation and task reassignment, respectively. Trace-driven experiments in the simulation and the real cluster show that CSA outperforms other schedulers in supplying deadline-guarantee and resource-efficient services and the effectiveness of each enhancement. Also, the enhancement algorithms are effective in improving CSA.
Topology in SU(2) lattice gauge theory and parallelization of functional magnetic resonance imaging

In this thesis, I discuss topological properties of quenched SU(2) lattice gauge fields. In particular, clusters of topological charge density exhibit a power-law. The exponent of that power-law can be used to validate models for lattice gauge fields. Instead of working with fixed cutoffs of the topological charge density, using the notion of a watermark'' is more convenient. Furthermore, I discuss how a parallel computer, originally designed for lattice gauge field simulations, can be used for functional magnetic resonance imaging. Multi parameter fits can be parallelized to achieve almost real-time evaluation of fMRI data.
Assessment of Vitamin D Level in Patients with Psoriasis and Its Correlation with Disease Severity: A Case–Control Study

Background Chronic plaque psoriasis is a chronic inflammatory skin disorder. Vitamin D has been shown to have effects on keratinocyte differentiation as well as immune regulation in the skin. Objective The main objective of this study was to assess the 25hydroxyvitamin D [25 (OH) D] level in patients with psoriasis in comparison with healthy control subjects. Materials and Methods This case–control study included 180 persons (120 cases and 60 age- and sex-matched control subjects) from outpatient department of BPKIHS, a tertiary care hospital in eastern Nepal. Severity of psoriatic skin lesions was assessed using psoriasis area severity index (PASI) scoring. Serum vitamin D level was assessed by chemiluminescent immunoassay. Results The mean serum 25(OH) D levels in psoriatic patients and controls were 19.57 ± 6.85 ng/mL and 23.63 ± 6.40 ng/mL, respectively. The difference was statistically significant even after adjusting for confounding factors in a multivariate analysis (aOR 2.929, 95% CI 1.376–6.230). Low serum 25(OH) D levels were negatively associated with the severity of disease (r= −0.628, P= 0.01). Conclusion Serum 25(OH) D levels are significantly lower in psoriatic patients than in healthy control subjects. Deficiency of serum 25(OH) D was associated with severity of disease with an inverse relationship with PASI score.
Application of a low order panel method to complex three-dimensional internal flow problems

An evaluation of the ability of a low order panel method to predict complex three-dimensional internal flow fields was made. The computer code VSAERO was used as a basis for the evaluation. Guidelines for modeling internal flow geometries were determined and the effects of varying the boundary conditions and the use of numerical approximations on the solutions accuracy were studied. Several test cases were run and the results were compared with theoretical or experimental results. Modeling an internal flow geometry as a closed box with normal velocities specified on an inlet and exit face provided accurate results and gave the user control over the boundary conditions. The values of the boundary conditions greatly influenced the amount of leakage an internal flow geometry suffered and could be adjusted to eliminate leakage. The use of the far-field approximation to reduce computation time influenced the accuracy of a solution and was coupled with the values of the boundary conditions needed to eliminate leakage. The error induced in the influence coefficients by using the far-field approximation was found to be dependent on the type of influence coefficient, the far-field radius, and the aspect ratio of the panels.
Long-term analysis of a savings program in elementary school

The prevalence of in-school savings programs (ISSPs) for children and youth is widespread, but research on their effectiveness is limited. This study investigates the long-term effects of an ISSP conducted in one U.S. elementary school. Survey data were collected on the financial behaviors of high school students, who participated in or did not participate in an ISSP while attending the same elementary school at the same time. The results from a probit analysis of data controlling for demographic variables showed that ISSP participants compared with non-participants were more likely to have a bank account in high school. They also were more likely to have opened a bank account before attending high school. Further results show that high school students with bank accounts are more likely to save regularly, indicating that ISSP contributes indirectly to saving regularly through its direct influence on getting students to open a bank account and open it early.
Fake News Spreaders Detection: Sometimes Attention Is Not All You Need

Guided by a corpus linguistics approach, in this article we present a comparative evaluation of State-of-the-Art (SotA) models, with a special focus on Transformers, to address the task of Fake News Spreaders (i.e., users that share Fake News) detection. First, we explore the reference multilingual dataset for the considered task, exploiting corpus linguistics techniques, such as chi-square test, keywords and Word Sketch. Second, we perform experiments on several models for Natural Language Processing. Third, we perform a comparative evaluation using the most recent Transformer-based models (RoBERTa, DistilBERT, BERT, XLNet, ELECTRA, Longformer) and other deep and non-deep SotA models (CNN, MultiCNN, Bayes, SVM). The CNN tested outperforms all the models tested and, to the best of our knowledge, any existing approach on the same dataset. Fourth, to better understand this result, we conduct a post-hoc analysis as an attempt to investigate the behaviour of the presented best performing black-box model. This study highlights the importance of choosing a suitable classifier given the specific task. To make an educated decision, we propose the use of corpus linguistics techniques. Our results suggest that large pre-trained deep models like Transformers are not necessarily the first choice when addressing a text classification task as the one presented in this article. All the code developed to run our tests is publicly available on GitHub.
Estimation of children’s age based on dentition via panoramic radiography in Surabaya, Indonesia

Background: Age may be estimated using tooth eruption sequence and/or calcification stage. Because many factors may affect the time of eruption, the tooth calcification stage shows higher accuracy than the time of tooth eruption. Demirjian’s and Willems’ methods have been most commonly used for dental age estimation. Both Willems and Demirjian use the calcification stage as an indicator. Studies comparing these methods have shown varied results, as they have been performed on different populations. Purpose: This paper aims to analyse the estimation of children's age based on dentition via panoramic radiography in Surabaya, Indonesia. Methods: This is a cross-sectional study using a purposive sampling method. One hundred digital panoramic radiographs of children between 6 and 15 years that match the inclusion criteria from the Airlangga University dental hospital in Surabaya, Indonesia were evaluated. One researcher analysed estimated dental age (EDA) three times in a one-week time-lapse using Demirjian’s and Willems’ methods. Statistical analysis was carried out using a Paired t-test and Wilcoxon signed-rank test. EDA was calculated using both Demirjian’s and Willems’ methods. Results: The mean chronological age (CA) was 10.57 ± 2.70 for males and 10.73 ± 2.84 for females. The mean difference between CA and EDA using the Demirjian and Willems methods was -0.57 ± 1.17 and 0.10 ± 0.96 for males and 0.58 ± 1.40 and 0.44 ± 0.94 for females. Conclusion: The results suggest that Willems’ method is more precise than Demirjian’s method in males and females and more suitable for children in Surabaya, Indonesia.