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本研究では、知的障害児が繰り下がりのある減法を習得する過程を分析し、指導との関連を検討することを目的とした。対象は、小学校知的障害特別支援学級に在籍する６年生の女児１名。指導は、算数の時間に計７回実施した。指導では、お金の種類についての学習、1000円は100円９枚と10円10枚に両替できること、解答が誤答の場合は、なぜ間違えたのかについてその理由を児に尋ねることなどを行った。半具体物を用いて1000－（商品代）を示した後、具体物を操作しておつりを計算するよう求めた。分析は、教師が提示した問題に対する児の解答の正誤、誤答の場合は、児が誤答に至った理由を言語化した内容、解答にかかった時間をもとに行った。その結果、1000－３位数のうち、減数の百の位および十の位が０以外で一の位が０の問題について、第５回目までは誤答が続いたが、第６回、第７回は正答となり、解答に要した時間も短くなった。半具体物を用いた式の提示、および、児が具体物の操作をして解答したことにより、10の補数概念が促進され、繰り下がりのある減法の理解につながったと考えられた。, The purpose of this study was to analyze how children with an intellectual disability acquire subtraction calculation with borrowing using concrete objects. The subject was one girl in the 6th grade who is enrolled in a special needs class at an elementary school. 7 guidance sessions were given during math class. Guidance consisted of learning about types of money and how 1000 yen is made up of 9 100-yen coins and 10 10-yen coins. If a wrong answer was given, the reason for the wrong answer was inquired of the subject. Using semi-concrete objects, equations 1000 - (merchandise price) were shown and the subject was asked to calculate the change using concrete objects. Analysis was conducted based on the right or wrong of the subject’s answer to the problem given by the teacher, verbalizing the process of the subject’s reaching the wrong answer, and the time it took to reach the correct answer. As a result, of the equations 1000 - a 3-digit number, for problems in which the subtracting number was 3 digits or 2 digits other than 0, 1 digits was 0, wrong answers were given until the 5th time. However, right answers were given for the 6th and 7th time and the time required to reach the correct answers decreased. By presenting the equation using semi-concrete objects and by the subject reaching the answer using concrete objects, the concept of tens complement was promoted, leading to the understanding of subtraction calculation with borrowing.

Retrospective performance evaluation of a computer-aided detection (CAD) system on standard posteroanterior (PA) chest radiographs (PA-CXR) in detection of pulmonary nodules, infectious consolidation, pneumothorax, pleural effusion, aortic calcification, cardiomegaly and rib fractures compared to radiologists analyzing PA-CXR including dual-energy subtraction radiography (further termed as DESR).PA-CXR/DESR images of 197 patients were included. All patients underwent chest CT (gold standard) within a short interval (mean 28 hours). All images were evaluated by three blinded readers for the presence of pulmonary nodules, infectious consolidation, pneumothorax, pleural effusion, aortic calcification, cardiomegaly, and rib fractures. Meanwhile PA-CXR were analyzed by a CAD software. CAD results were compared to the majority result of the three readers. Sensitivity and specificity were calculated. McNemar's test was applied to test for significant differences. Interobserver agreement was defined using Cohen's kappa (κ).Sensitivity of the CAD software was significantly higher (p0.05) for detection of infectious consolidation and pulmonary nodules (67.9% vs 26.8% and 54% vs 35.6%, respectively; p0.001) compared to radiologists analyzing DESR images. For the residual evaluated pathologies no statistical significant differences could be found. Overall, mean inter observer agreement between the three radiologists was moderate (k = 0.534). The best interobserver agreement could be reached for pneumothorax (k = 0.708) and pleural effusion (k = 0.699), while the worst was obtained for rib fractures (k = 0.412).The CAD system has the potential to improve the detection of infectious consolidation and pulmonary nodules on CXR images.

Recurrent neural networks (RNNs) can remember temporal contextual information over various time steps. The well-known gradient vanishing/explosion problem restricts the ability of RNNs to learn long-term dependencies. The gate mechanism is a well-developed method for learning long-term dependencies in long short-term memory (LSTM) models and their variants. These models usually take the multiplication terms as gates to control the input and output of RNNs during forwarding computation and to ensure a constant error flow during training. In this article, we propose the use of subtraction terms as another type of gates to learn long-term dependencies. Specifically, the multiplication gates are replaced by subtraction gates, and the activations of RNNs input and output are directly controlled by subtracting the subtrahend terms. The error flows remain constant, as the linear identity connection is retained during training. The proposed subtraction gates have more flexible options of internal activation functions than the multiplication gates of LSTM. The experimental results using the proposed Subtraction RNN (SRNN) indicate comparable performances to LSTM and gated recurrent unit in the Embedded Reber Grammar, Penn Tree Bank, and Pixel-by-Pixel MNIST experiments. To achieve these results, the SRNN requires approximate three-quarters of the parameters used by LSTM. We also show that a hybrid model combining multiplication forget gates and subtraction gates could achieve good performance.

The method based on machine vision image processing is used to detect the surface defects of Si3N4 bearing roller. Owing to the variety of defects, small area and low contrast, it is easy to miss or error detection. In this paper, an adaptive update template defect enhancement algorithm based on Gaussian model is proposed. First, a large number of surface images of Si3N4 bearing roller are collected to obtain the non-defect background statistical feature, and the background characteristic curve is fitted by Gaussian model. Further, the initial background template is gained according to the Gaussian curve. Then, combined with the gray distribute of defect images and initial background template, unique adaptive update template can be established. Finally, subtraction operation and nonlinear enhancement are used to improve the comparison of defect information and background. Through inverse sorting, adaptive threshold segmentation and Canny operation, the precise positioning of defects is realized. The enhancement algorithm can effectively enhance the contrast and eliminate the influence of noise. The average detection time is 0.84s, and the detection accuracy is 96.2%.

The arithmetic optimization algorithm (AOA) is a newly developed metaheuristic search technique that simulates the distribution characteristics of the basic arithmetic operations of addition, subtraction, multiplication, and division, and has been employed to solve some real-world optimization problems. However, it has been found that the AOA suffers from poor exploration and prematurely converges to non-optimal solutions, especially when applied to multi-dimensional optimization problems. In this paper, to overcome the shortcomings of the standard AOA, an improved variant of the AOA, called improved arithmetic optimization algorithm (IAOA), is proposed and then employed for optimization of skeletal structures with discrete design variables. Compared to the standard AOA, two major improvements are made in the proposed IAOA: (1) The original formulation of the AOA is modified to enhance the exploration and exploitation capabilities; (2) The proposed IAOA requires fewer algorithm-specific parameters compared with the standard AOA, making it easy to be implemented. To examine the efficiency and robustness of the proposed IAOA, three benchmark structural optimization problems with discrete design variables are investigated and the results are compared to those of the standard AOA and other methods available in the literature. To the best of our knowledge, this is the first attempt to apply AOA to structural optimization. The IAOA not only promotes the exploration capability of the search space but also overcomes the shortcoming of the premature convergence of the standard AOA. Experimental results indicate that IAOA significantly surpasses the standard AOA and achieves results comparable or superior to other state-of-the-art metaheuristics.

Analogical reasoning, for example, inferring that teacher is to chalk as mechanic is to wrench, plays a fundamental role in human cognition. However, whether brain activity patterns of individual words are encoded in a way that could facilitate analogical reasoning is unclear. Recent advances in computational linguistics have shown that information about analogical problems can be accessed by simple addition and subtraction of word embeddings (e.g., wrench = mechanic + chalk − teacher). Critically, this property emerges in artificial neural networks that were not trained to produce analogies but instead were trained to produce general-purpose semantic representations. Here, we test whether such emergent property can be observed in representations in human brains, as well as in artificial neural networks. fMRI activation patterns were recorded while participants viewed isolated words but did not perform analogical reasoning tasks. Analogy relations were constructed from word pairs that were categorically or thematically related, and we tested whether the predicted fMRI pattern calculated with simple arithmetic was more correlated with the pattern of the target word than other words. We observed that the predicted fMRI patterns contain information about not only the identity of the target word but also its category and theme (e.g., teaching-related). In summary, this study demonstrated that information about analogy questions can be reliably accessed with the addition and subtraction of fMRI patterns, and that, similar to word embeddings, this property holds for task-general patterns elicited when participants were not explicitly told to perform analogical reasoning.

The assessment and diagnosis of agricultural drought vulnerability is the basis for the scientific control and prevention of agricultural drought risk. In order to quantitatively evaluate the regional agricultural drought vulnerability and effectively deal with the fuzziness and randomness between evaluation sample and evaluation grade, the entropy fuzzy pattern recognition model, which was coupled with maximum information entropy principle and fuzzy pattern recognition method, was applied to the evaluation of agricultural drought vulnerability. Furthermore, in order to find methods to reduce drought vulnerability, the subtraction set pair potential method was used to further identify the main influence factors of agricultural drought vulnerability. In addition, a case study was carried out in Bengbu City, China. The results showed that during the period from 2001 to 2010, the evaluation value of agricultural drought vulnerability in Bengbu dropped from grade IV to III, which meant that the tolerance of agricultural system to drought had been improved. Moreover, the main factors that affected the vulnerability in Bengbu were precipitation, water use efficiency and irrigation protection area rate. And the latter two were the main objects of regulation and control. Compared with the other three methods, the physical concept of drought vulnerability assessment model based on entropy fuzzy pattern recognition is more obvious, and the evaluation results are reasonable and credible. The drought vulnerability diagnosis method based on subtraction set pair potential can accurately identify key influence factor and provide measures to reduce drought vulnerability and improve drought risk management.

Ground-penetrating radar (GPR) is a well-known geophysical electromagnetic method used to detect the underground facilities such as landmines, pipelines, and cavities. In general, the clutter presented in GPR B-scan image obscures the underground objects, thus damaging the performance of the underground object detection algorithm. In this letter, we proposed a new clutter suppression method based on robust autoencoder (RAE). The proposed algorithm decomposes a GPR B-scan image into its low-rank and sparse components. The low-rank component catches the clutter, whereas the sparse component captures the underground object responses. The commonly used clutter removal algorithms, mean subtraction (MS), singular value decomposition (SVD), robust principal component analysis (RPCA), and morphological component analysis (MCA), are compared with the proposed algorithm on both the numerical simulated data and real GPR data. The visual and quantitative results demonstrate the effectiveness of the proposed RAE-based algorithm over the widely used state-of-the-art clutter removal algorithms.

BACKGROUND Acute gastrointestinal bleeding (GIB) is a life-threatening medical emergency with high morbidity and mortality. Transcatheter embolization with endovascular coils under digital subtraction angiography guidance is a common and effective method for the treatment of GIB with high technical success rates. Duodenal ulcers caused by coils wiggled from the branch of the gastroduodenal artery, which is a rare complication, have not previously been reported in a patient with right intrathoracic stomach. CASE SUMMARY A 62-year-old man had undergone thoracoscopy-assisted radical resection of esophageal cancer and gastroesophageal anastomosis 3 years ago, resulting in right intrathoracic stomach. He was admitted to the hospital 15 mo ago for dizziness and suffered acute GIB during his stay. Interventional surgery was urgently performed to embolize the branch of the gastroduodenal artery with endovascular coils. After 15 mo, the patient was re-admitted with a chief complaint of melena for 2 d, esophagogastroduodenoscopy and abdominal computed tomography revealed that some endovascular coils had migrated into the duodenal bulb, leading to a deep ulcer. Bleeding was controlled after conservative treatment. Seven months later, duodenal balloon dilatation was performed to relieve the stenosis after the removal of a few coils, and the patient was safely discharged with only one coil retained in the duodenum due to difficulties in complete removal and risk of bleeding. Mild melena recurred once during the long-term follow-up. CONCLUSION Although rare, coil wiggle after interventional therapy requires careful attention, effective precautionary measures, and more secure alternative treatment methods.

In this study, to investigate the influence of numerical surface forms on strategy execution in subtraction and addition, 25 college students were required to perform a mental arithmetic task. Behavioral and electroencephalography responses were recorded to explore the stages of strategy execution. Arithmetic problems were presented within 11-20 by Arabic, Chinese and English numerals, respectively. The results showed that, compared with Arabic and Chinese numerals, participants had longer RTs under the condition of English numerals. English numerals induced stronger N100, P200 and P300 amplitudes, and longer latency in P200 and P300 amplitudes than in other conditions. These findings indicated that numerical surface forms affected the execution of mental arithmetic strategies, with Chinese and English numerals being processed deeper in the brain. Especially, the English digital word form occupied more psychological resources, and it was activated more in the frontal area and the parietal area, which would obviously hinder the processing of arithmetic information.

13N-ammonia and 18F-flurpiridaz require longer delays between rest and stress studies to allow for decay, lowering clinical throughput. In this study, we investigated the impact of residual subtraction on MBF and MFR estimates, as well as its effects on diagnostic accuracy. We retrospectively analyzed 63 patients who underwent a dynamic ammonia rest/stress study and 231 patients from the flurpiridaz 301 trial. Residual subtraction was performed by subtracting the mean pre-injection activity in each sampled region from that region’s time activity curve. Corrected and uncorrected MBF and MFR were analyzed. Diagnostic accuracy was compared to quantitative coronary angiograms (QCA) for the flurpiridaz population. With delays between injections above 3 half-lives, and a doubled stress dose, residual activity did not meaningfully increase ammonia MBF (

Background The modified thrombolysis in cerebral infarction (mTICI) scale is a widely used and validated qualitative tool to evaluate angiographic intracerebral inflow following endovascular thrombectomy (EVT). We validated a machine-learning (ML) algorithm to grade digital subtraction angiograms (DSA) using the mTICI scale. Materials and methods We included angiograms of identified middle cerebral artery (MCA) occlusions who underwent EVT. The complete DSA sequences were preprocessed and normalized. We created three convolutional neural networks to classify DSA into two outcomes, low- (mTICI 0,1,2a) and high-grade (mTICI 2b,2c,3). Results We included a total of 234 angiograms in this study. The area under the receiver operating characteristic was 0.863 (95% CI 0.816-0.909), 0.914 (95% CI 0.876-0.951), and 0.890 (95% CI 0.848-0.932) for the anteroposterior (AP), lateral (L), and combined models, respectively, when dichotomizing outcomes into low and high grade. The models' area under the precision-recall curve was 0.879 (95% CI 0.829-0.930), 0.906 (95% CI 0.844-0.968), and 0.887 (95% CI 0.834-0.941) for the AP, L, and combined models. Conclusion In complete cerebral DSA, our angiography-based ML strategy was able to predict mTICI scores following EVT rapidly and reliably for MCA occlusions.

The process of seismic multiple removal in oil seismic exploration is crucial for the imaging of underground structures with primary reflections. The inclusion of prediction and subtraction in the multiple removal method requires adaptive subtraction to remove the complex differences between the true and modeled multiples. The traditional adaptive subtraction method is generally expressed as a linear regression (LR) problem. In this article, we introduce U-net, a popular deep learning tool, to represent the complex differences between the true and modeled multiples in a nonlinear relationship. Thus, we present adaptive subtraction as a non-LR problem. The modeled multiples and full recorded seismic response with multiples and primaries are used as the input and labels to train U-net. The proposed U-net method is able to avoid over-fitting of the primaries due to the sufficient number of 2-D data windows for the training of U-net, as well as the network parameter regularization and the L1 norm minimization constraint on the primaries. The proposed U-net method attains 20.5 dB and 2.5 dB improvement in the signal-to-noise ratio (SNR) using the first synthetic data and second synthetic (Sigsbee2B) data set, respectively, compared with the traditional LR method, and a qualitative improvement for a real data set test.

Background Hepatocellular carcinoma (HCC) is one of the most prevalent cancers worldwide, and if left untreated, one of the most lethal. Ablative therapies including radiofrequency ablation (RFA) play increasingly important role for patients with liver tumors who are not surgical candidates. Monitoring treatment response following ablation is crucial in oncologic imaging. Dynamic contrast-enhanced MRI can assess changes in tumor vascularity and perfusion while subtraction imaging is useful in differentiating residual tumor from post-ablation parenchymal changes. The aim of this study is to compare the role of subtraction MRI and conventional dynamic MRI in assessing treatment response following RFA in patients with HCC. Results The study included 48 patients with 62 HCC lesions who underwent RFA from May to October 2020, followed by MRI evaluation with 1-month interval. Two readers with experience in hepatic imaging interpreted the dynamic and subtraction dynamic MRI. The hepatic focal lesions were classified into “well-ablated” and “residual” groups according to MRI findings, and the agreement between the two readers was evaluated. Using dynamic MRI, the first reader reported 38 well-ablated lesions, and the second reader agreed in 34 of them (89.5%). Residual disease was reported by the first reader in 22 lesions and the second reader disagreed in 10 of them (45.5%) where complete ablation was reported. Thirty-eight out 44 well-ablated lesions (86.4%) showed high signal intensity on non-enhanced T1 images, and 28 lesion (63.6%) showed intermediate T2 signal. All the mis-matched readings occurred in lesions with a high signal intensity in pre-contrast T1 images. Moderate agreement between the two readers was found with Kappa value of 0.467. Significant additive value of subtraction technique to dynamic MRI was detected with a P value of 0.009. No major complications recorded except for a single case of major portal vein branch occlusion. Conclusion MRI is a powerful imaging tool in assessing tumor viability and complications after RFA in patients with HCC. Dynamic MRI study is the gold standard in detecting recurrent lesions while subtraction technique is crucial in differentiating between arterial enhancement due to residual disease and normal hyperintense T1 signal of the ablation zone.

Vehicle segmentation, traffic density estimation and vehicle tracking are some of the important functionalities in smart traffic management. Segmentation of vehicles from traffic surveillance videos can help to realize many applications like speed monitoring, traffic estimation etc. Vehicle segmentation from surveillance videos becomes very challenging due to presence of occlusions, cluttered backgrounds and traffic density variations. In this work, we propose a deep learning adapted active net segmentation model for vehicle segmentation. The proposed solution involves three stages: adaptive background model based subtraction, active net sub netting with CNN, refined from CNN results with ETAN optimization. Adaptive background modeling is based on an adaptive gain function which is constructed from the pixels of the frames in the video. The gain function is able to compensate for the shadow and illumination problems affecting the vehicle segmentation. Deep learning assisted topological active net deformable model is able to provide higher segmentation accuracy in presence of occlusions, cluttered backgrounds and traffic density variations.

In planning randomized clinical trials (RCTs) for diseases such as Alzheimer's disease (AD), researchers frequently rely on the use of existing data obtained from only two time points to estimate sample size via the subtraction of baseline from follow-up measurements in each subject. However, the inadequacy of this method has not been reported. The aim of this study is to discuss the limitation of sample size estimation based on the subtraction of available data from only two time points for RCTs. Mathematical equations are derived to demonstrate the condition under which the obtained data pairs with variable time intervals could be used to adequately estimate sample size. The MRI-based hippocampal volume measurements from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and Monte Carlo simulations (MCS) were used to illustrate the existing bias and variability of estimates. MCS results support the theoretically derived condition under which the subtraction approach may work. MCS also show the systematically under- or over-estimated sample sizes by up to 32.27 % bias. Not used properly, such subtraction approach outputs the same sample size regardless of trial durations partly due to the way measurement errors are handled. Estimating sample size by subtracting two measurements should be treated with caution. Such estimates can be biased, the magnitude of which depends on the planned RCT duration. To estimate sample sizes, we recommend using more than two measurements and more comprehensive approaches such as linear mixed effect models.

In this paper, a color image encryption algorithm based on Fisher-Yates scrambling and DNA subsequence operation (elongation operation, truncation operation, deletion operation, insertion arithmetic) is proposed. Firstly, the three-dimensional color image is transformed into two-dimensional gray image, and the chaotic sequence generated by Chen system and Fisher-Yates scrambling method is used to scramble the plaintext images of R, G and B channels. Secondly, the three channel images of the scrambled plaintext image are transformed into three DNA sequence matrixes by using the DNA coding rules, and then the three DNA sequence matrixes are manipulated by using DNA subsequence operation and DNA addition, subtraction and XOR operation to destroy the scrambled plaintext information. Finally, the color encrypted image is obtained by using the DNA decoding rule. Experimental results and security analysis demonstrate that our encryption algorithm has good performance and may resist against various typical attacks.

One of the fundamental knowledge in mathematics in Primary school is related to the arithmetic operations addition and subtraction. According to the educational programs in mathematics in the Republic of Bulgaria, students start studying these operations in grade 1. The article presents theoretical concepts affecting studying the arithmetic operations addition and subtraction in the education in mathematics at a primary school. The research work identified the specifics of studying the inverse connections between the arithmetic operations addition and subtraction in the education in mathematics for grade 1 are also presented. Some of the significant tasks with importance for discovering the relations between the forward operation addition and the reverse operation subtraction were proposed in the study. A new methodology system of work with tasks where these relations are used was developed and tested. The author studied the knowledge, skills, and competencies of the grade 1 students to solve arithmetic operations addition and subtraction tasks. After the exit diagnostic, it was found out that the students of the class where the new methodology system of work was applied during their education in mathematics have got a higher level of knowledge and skills from competency Cluster Numbers in respect of the arithmetic operations addition and subtraction. The use of mathematical tasks with reverse relations between the arithmetic operations addition and subtraction help the students to develop both the overall mathematical knowledge and the logical thinking of the first-graders.

Purpose The purpose of this study was to investigate the usefulness of temporal subtraction CT (TSCT) of temporal bone CT for the detection of postoperative recurrent/residual cholesteatoma of the middle ear. Methods Thirty-two consecutive patients with surgically proven postoperative recurrent/residual cholesteatoma and 14 consecutive patients without recurrent/residual lesion matched the selection criteria and were retrospectively evaluated. TSCT imaging was generated with the use of serial postoperative CT. Two experienced radiologists and two residents evaluated the presence of bone erosive change by comparison serial CT studies, and CT and TSCT. The detection rate of bone erosive change, sensitivity and specificity of the recurrence/residual lesions, and reading time for each reader were evaluated. Results TSCT + CT significantly improved the detection of bone erosive changes compared to CT-only evaluation (17.4–41.3% vs. 37.0–58.7%, p = 0.008–0.046). The mean sensitivity and specificity of TSCT + CT for experienced radiologists were 0.77 and 1.00, and 0.52 and 0.97 without TSCT. The mean sensitivity and specificity of TSCT + CT for residents were 0.64 and 1.00, and 0.41 and 1.00 without TSCT. Sensitivity showed an increase in all readers. The use of TSCT significantly reduced the reading time per case in all readers (p Conclusion TSCT improves the depiction of newly occurring progressive bone erosive changes, and detection sensitivity and reading time in postoperative recurrence/residual cholesteatoma of middle ear.

La sottrazione in architettura, come deliberato atto progettuale, sembra porsi come un paradosso in quanto approccio apparentemente antinomico alla stessa natura del progetto e della costruzione, entità concepite, per convenzione, come esclusivamente additive e proliferative. In termini più generali, la sottrazione in architettura è l’esito di una rimozione parziale o totale dell’oggetto costruito, derivante da eventi esogeni incontrollati (disastri naturali) o deliberati (guerre, terrorismo), da azioni endogene mirate (demolizioni selettive, modifiche parziali o consistenti dell’esistente) o come conseguenza di processi di obsolescenza e abbandono (rovina). L’utilizzo dunque di un dispositivo progettuale/estetico come la sottrazione – sia questo come effettivo atto concreto de-costruttivo, sia come elaborazione estetico-formale di sottrazione simulata – si situa dunque entro un determinato milieu culturale di registro trasversale – dal più popolare all’accademico – che individua nelle forme del disastro, della rovina o dell’abbandono una sorta di narrazione efficace di un certo spirito millenarista contemporaneo. Nel campo progettuale questo approccio si manifesta tanto nella manipolazione “in negativo” elaborata sull’esistente, quanto nella produzione ex-novo di edifici in cui la sottrazione si presenta come elemento, apparentemente casuale, di discontinuità del rigore monolitico neomodernista. Entrambi gli approcci sembrano trarre dalle variabili indipendenti, anche le più estreme, che modificano ogni opera architettonica nel suo ciclo vitale (l’inesorabile degrado e tutto ciò che esula dal controllo del progetto o, in sostanza, gli “eventi” tschumiani) degli strumenti proattivi in grado di fornire nuovi o rinnovati paradigmi progettuali, mentre a scala urbana, la sottrazione si pone oggi come ‘cura’ necessaria soprattutto dove l’eccesso di materiale costruito in decomposizione, abbandonato o sottoutilizzato si presta a essere progettato ‘in negativo’, ovvero a ritornare a essere risorsa materiale nel circuito del riciclo e offrire i campi di proliferazione di ambiti di naturalità sempre più necessari in un’era di crisi ambientale. Subtraction in architecture, as a deliberate design act, seems to be a paradox as a seemingly antinomian approach to the very nature of design and construction, entities conceived, by convention, as exclusively additive and proliferative. In more general terms, subtraction in architecture is the outcome of partial or total removal of the built object, resulting from uncontrolled exogenous (natural disasters) or deliberate (wars, terrorism) events, from targeted endogenous actions (selective demolitions, partial or substantial modifications of the existing) or as a consequence of processes of obsolescence and abandonment (ruin). Thus, the use of a design/aesthetic device such as subtraction - whether this is as an actual concrete de-constructive act or as an aesthetic-formal elaboration of simulated subtraction - is thus situated within a certain cultural milieu of transversal register - from the most popular to the academic - that identifies in the forms of disaster, ruin or abandonment a kind of effective narrative of a certain contemporary millenarian spirit. In the design field, this approach manifests itself as much in the "negative" manipulation elaborated on the existing as in the ex-novo production of buildings in which subtraction is presented as a seemingly random element of discontinuity from the monolithic neo-modernist rigor. Both approaches seem to draw from the independent variables - even the most extreme ones, that modify any architectural work in its life cycle (the inexorable degradation and all that is beyond the control of the project or, in essence, Tschumian "events") - some proactive tools that can provide new or renewed design paradigms, while at the urban scale, subtraction now emerges as a necessary 'cure' especially where the excess of decaying, abandoned or underutilized built material lends itself to be designed 'by reverse,' that is, to become a material resource again in the recycling circuit and to offer the fields for the proliferation of natural areas, increasingly needed in an era of environmental crisis.

Digital, Resolver ejercicios matemáticos, falencias más relevantes en los educandos quienes tienen los conocimientos, pero se confunden a la hora de resolver los ejercicios matemáticos. Ya que no analizan, descomponen y ejecutan pasos secuencialmente. La investigación buscar desarrollar pensamiento computacional con la ejecución de material educativo en matemática, para brindar solución en cuanto a resolución de ejercicios matemáticos utilizando la adición, sustracción, multiplicación y división a través de la aplicación MENTAL MATH, en el grado cuarto en la I.E Miguel Antonio Caicedo Mena. Mediante actividades dinámicas y lúdicas que lleven a mejorar el proceso de agrupación y ejecución de suma, resta multiplicación y división. Fortaleciendo a los educandos el pensamiento, critico, racional y matemático fusionado con la tecnología, llevándolos a desarrollar competencias tecnológicas de la sociedad de conocimiento. El enfoque cualitativo, metodológica descriptiva. Se aplicó pretest, postest, entrevista y observación para la recolección de datos. En la aplicación Mental Math se desarrolló un curso de 4 unidades temáticas y una evaluación final. Los estudiantes debían avanzar los niveles de complejidad resolviendo las operaciones matemáticas hasta llegar a la división en MENTAL MATH. Los resultados evidenciaron que el desarrollo del pensamiento computacional fortaleció la facilidad en los estudiantes en resolver las cuatro operaciones matemáticas en el grado cuarto. Los aprendices desarrollaron seguridad y tolerancia para enfrentar retos., Solve mathematical exercises, most relevant shortcomings in students who have the knowledge but are confused when solving mathematical exercises. Since they don't parse, decompose, and execute steps sequentially. The research seeks to develop computational thinking with the execution of educational material in mathematics, to provide a solution in terms of solving mathematical exercises using addition, subtraction, multiplication and division through the mental math application, in the fourth grade at I.E Miguel Antonio Caicedo Mena. Through dynamic and playful activities that lead to improve the grouping process and execution of addition, subtraction, multiplication and division. Strengthening critical, rational, and mathematical thinking fused with technology, leading them to develop technological skills for the knowledge society. The qualitative, descriptive methodological approach. Pretest, posttest, interview and observation were applied for data collection. In the mental math application, a course of 4 thematic units and a final evaluation were developed. The students had to advance the levels of complexity by solving the mathematical operations until they reached the division in mental math. The results showed that the development of computational thinking strengthened the ease of students in solving the four mathematical operations in the fourth grade. The trainees developed security and tolerance to face challenges., Maestría, Magíster en Tecnologías Digitales Aplicadas a la Educación, Introducción .............................................................................................................................17 1. Planteamiento del problema.................................................................................................19 1.1. Problema........................................................................................................................19 1.1.1 descripción e identificación del problema. ............................................................19 1.2 Alcance......................................................................................................................27 1.3 Justificación...............................................................................................................28 1.4 Objetivos........................................................................................................................32 1.4.1 Objetivo general ....................................................................................................32 1.4.2 Objetivos específicos.............................................................................................32 2. Bases teóricas.......................................................................................................................33 2.1 estado del arte.................................................................................................................33 A nivel internacional ........................................................................................................34 A nivel nacional................................................................................................................36 2.2 Marco Referencial..........................................................................................................38 2.2.1 Marco teórico. .............................................................................................................38 2.2.2 Marco conceptual. .......................................................................................................41 Educación matemática......................................................................................................41 Estrategias aplicadas a través de las TIC..........................................................................43 Trabajo colaborativo.........................................................................................................44 2.2.3 Marco Legal ................................................................................................................46 2.2.4 Constitución Política de Colombia ..............................................................................46 2.3 Marco Tecnológico ........................................................................................................50 2.3.1 Mental Math (App) .....................................................................................................50 3. Diseño Metodológico...........................................................................................................56 3.1 Tipo de investigación.....................................................................................................56 3.2 Hipótesis. .......................................................................................................................57 3.3 Variables. .......................................................................................................................58 3.4 Operacionalización de variables. ...................................................................................58 3.5 Población........................................................................................................................61 3.5.1 Muestra. ......................................................................................................................65 3.6 Procedimiento. ...............................................................................................................65 3.7 Instrumento de recolección de información. ..................................................................67 3.8 Técnicas de análisis de datos. .......................................................................................70 4. Consideraciones Éticas. .......................................................................................................71 5. Diagnostico. .........................................................................................................................72 5.1Diagnóstico inicial...........................................................................................................72 5.2 Análisis de los resultados de la encuesta diagnostica. ...................................................73 6. Estructura de la propuesta de intervención. .........................................................................89 6.1 propuesta pedagógica. ....................................................................................................89 6.2 Componente tecnológico................................................................................................96 6.3 Implementación............................................................................................................106 7. Análisis e interpretación de datos......................................................................................111 8. Conclusiones......................................................................................................................129 9. Limitaciones.......................................................................................................................132 10. Impacto, recomendaciones y trabajos futuros..................................................................133 10.1 Impacto. .........................................................................................................................133 10.2 Recomendaciones. .........................................................................................................134 10.3 trabajos futuros...............................................................................................................134 Bibliografía ............................................................................................................................135

Study design Experimental study. Objectives The goal of this study was to develop a 3D-printed pedicle subtraction osteotomy (PSO) guide plate system. A 3D model and postoperative CT data were used to evaluate the accuracy of osteotomy with this system. Summary of background data The key to the success of spinal orthopaedic treatment is an effectively performed osteotomy. A 3D-printed osteotomy plate can be used for preoperative surgical planning. Due to the anatomical complexity of the spinal region, the clinical application of 3D-printed osteotomy plates remains challenging. Methods The CT scans of 10 patients with thoracolumbar spinal deformities were obtained in the DICOM format. The diseased vertebrae and adjacent vertebrae were reconstructed and reduced by computer-aided design (CAD) software, and an osteotomy plate was designed for the diseased vertebrae. The 3D-printed spinal model and osteotomy plate were used to simulate the operation for PSO. After the operation, the vertebral body treated by osteotomy underwent a CT scan, and the findings were compared with the preoperative design to evaluate the osteotomy accuracy. Results The new 3D guide plate and spine model were used to successfully simulate 10 cases of PSO, and the comparison of the preoperative and postoperative states indicated that the osteotomy outcomes were excellent. Conclusions The new 3D-printed PSO guide plate system can be used for preoperative osteotomy planning and demonstrates good accuracy. The results can be used to develop 3D-printed plans for PSO in clinical practice.Level of Evidence: 3.

Previously, a joint ictal/inter-ictal SPECT reconstruction was proposed to reconstruct a differential image representing the change of brain SPECT image from an inter-ictal to an ictal study. The so-called joint method yielded better performance for epileptic foci localization than the conventional subtraction method. In this study, we evaluated the performance of different reconstruction settings of the joint reconstruction of ictal/inter-ictal SPECT data, which creates a differential image showing the difference between ictal and inter-ictal images, in lesion detection and localization in epilepsy imaging. Differential images reconstructed from phantom data using the joint and the subtraction methods were compared based on lesion detection performance (channelized Hotelling observer signal-to-noise ratio (SNRCHO) averaged across four lesion-to-background contrast levels) at the optimal iteration. The joint-initial method which was the joint method that was initialized by the subtraction method at optimal iteration was also used to reconstruct differential images. These three methods with respective optimal iteration and the subtraction method with four iterations were applied to epileptic patient datasets. A human observer lesion localization study was performed based on localization receiver operating characteristic (LROC) analysis. From the phantom study, at their respective optimal iteration, the joint method yielded an improvement in lesion detection performance over the subtraction method of 26%, which increased to 145% when using the joint-initial method. From the patient study, the joint-initial method yielded the highest area under the LROC curve as compared with those of the joint and the subtraction methods with optimal iteration and with 4 iterations (0.44 vs 0.41, 0.39 and 0.36, respectively). In lesion detection and localization, the joint method at optimal iteration outperformed the subtraction method at optimal iteration and at iteration typically used in clinical practice. Furthermore, initialization by the subtraction method improved the performance of the joint method.

The data quality of simultaneously acquired electroencephalography and functional magnetic resonance imaging (EEG-fMRI) can be strongly affected by motion. Recent work has shown that the quality of fMRI data can be improved by using a Moiré-Phase-Tracker (MPT)-camera system for prospective motion correction. The use of the head position acquired by the MPT-camera-system has also been shown to correct motion-induced voltages, ballistocardiogram (BCG) and gradient artefact residuals separately. In this work we show the concept of an integrated framework based on the general linear model to provide a unified motion informed model of in-MRI artefacts. This model (retrospective EEG motion educated gradient artefact suppression, REEG-MEGAS) is capable of correcting voltage-induced, BCG and gradient artefact residuals of EEG data acquired simultaneously with prospective motion corrected fMRI. In our results, we have verified that applying REEG-MEGAS correction to EEG data acquired during subject motion improves the data quality in terms of motion induced voltages and also GA residuals in comparison to standard Artefact Averaging Subtraction and Retrospective EEG Motion Artefact Suppression. Besides that, we provide preliminary evidence that although adding more regressors to a model may slightly affect the power of physiological signals such as the alpha-rhythm, its application may increase the overall quality of a dataset, particularly when strongly affected by motion. This was verified by analysing the EEG traces, power spectra density and the topographic distribution from two healthy subjects. We also have verified that the correction by REEG-MEGAS improves higher frequency artefact correction by decreasing the power of Gradient Artefact harmonics. Our method showed promising results for decreasing the power of artefacts for frequencies up to 250 Hz. Additionally, REEG-MEGAS is a hybrid framework that can be implemented for real time prospective motion correction of EEG and fMRI data. Among other EEG-fMRI applications, the approach described here may benefit applications such as EEG-fMRI neurofeedback and brain computer interface, which strongly rely on the prospective acquisition and application of motion artefact removal.

Background In osteoporotic vertebral fractures (OVF) involving neurological symptoms and severe kyphosis, vertebral osteotomies are necessary but are associated with a high risk of complications. Methods We performed a retrospective study. In 14 patients (mean age, 69.3 years old) with unstable thoracolumbar fractures associated with severe kyphosis, a posterior instrumentation with polymethylmethacrylate-augmented screws and a modified pedicle subtraction osteotomy (PSO) at the fracture level were performed to stabilize the spine and correct the kyphosis. The underlying principle behind the osteotomy9s technique was to exaggerate the defect caused by the fracture and shorten the spine: (1) completion of a wide laminoforaminotomy, (2) use of successive reamers rotated in the pedicle at a 25° angle in the axial plane to obtain its complete decancellation, (3) insertion of the reamers in a more medial orientation (55°) to collapse the posterior wall, and (4) breakage of the lateral wall. Radiographic and clinical outcomes were analyzed pre- and postoperatively. Complications were reported. Results Functional scores improved after surgery. Oswestry disability index and visual analog scale scores decreased significantly (33 and 4 points, respectively). Patient satisfaction rate reached 93%. Average postoperative regional vertebral kyphosis was decreased to 3.79°. No dural tear or neurological injuries were observed. Blood loss of 920 mL (±350 mL) and two mechanical complications were reported. Conclusions OVF can lead to severe deformities. In osteoporotic bones, the use of sequential reamers can simplify the PSO technique, allowing for the shortening and stabilization of the spine without manipulating the dural sac. The risk of neurological injuries and blood loss is decreased. Level of Evidence 4.

Purpose Tumor size and depth of invasion (DOI) are mandatory assessments for tumor classification in tongue cancer but are often non-assessable on CT due to dental artifacts. This study investigated whether subtraction iodine imaging (SII) would improve tumor delineation and measurability. Materials and methods Fifty-seven consecutive patients with tongue cancer, who underwent scanning with a 320-row area detector CT with contrast administration and were treated with surgical resection, were retrospectively evaluated. CT was reconstructed with single-energy projection-based metallic artifact reduction (sCT). SII was generated by subtracting the pre-contrast volume scans from the post-contrast volume scans using a high-resolution deformable registration algorithm. MRI scans were also evaluated for comparing the ability of measurements. Two radiologists visually graded the tumor delineation using a 5-point scale. Tumor size and DOI were measured wherever possible. The tumor delineation score was compared using the Wilcoxon signed-rank method. Spearman’s correlations between imaging and pathological measurements were calculated. Intraclass correlation coefficients of measurements between readers were estimated. Results The tumor delineation score was greater on sCT-plus-SII than on sCT alone (medians: 3 and 1, respectively; p Conclusions SII improves detectability and measurability of tumor size and DOI in patients with oral tongue squamous cell carcinoma, thus increasing the diagnostic potential. SII may also be beneficial for cases unevaluable on MRI due to artifacts or for patients with contraindications to MRI.

Purpose Dynamic contrast-enhanced MRI (DCE-MRI) registration is a challenging task because of the effect of remarkable intensity changes caused by contrast agent injections. Unrealistic deformation usually occurs by using traditional intensity-based algorithms. To alleviate the effect of contrast agent on registration, we proposed a DCE-MRI registration strategy and investigated the registration performance on the clinical DCE-MRI time series of liver. Method We reconstructed the time-intensity curves of the contrast agent through sparse representation with a predefined dictionary whose columns were the time-intensity curves with high correlations with respect to a preselected contrast agent curve. After reshaping 1D-reconstructed contrast agent time-intensity curves into a 4D contrast agent time series, we aligned the original time series to the reconstructed contrast agent time series through traditional free-form deformation (FFD) registration scheme combined with a residual complexity (RC) similarity and an iterative registration strategy. This study included the DCE-MRI time series of 20 patients with liver cancer. Results Qualitatively, the time-cut images and subtraction images of different registration methods did not obviously differ. Quantitatively, the mean (standard deviation) of temporal intensity smoothness of all the patients achieved 54.910 (18.819), 54.609 (18.859), and 53.391 (19.031) in FFD RC, RDDR, Zhou et al.'s method and the proposed method, respectively. The mean (standard deviation) of changes in the lesion volume were 0.985 (0.041), 0.983 (0.041), 0.981 (0.046), and 0.989 (0.036) in FFD RC, RDDR, Zhou et al.'s method and the proposed method. Conclusion Our proposed method would be an effective registration strategy for DCE-MRI time series, and its performance was comparable with that of three advanced registration methods.

Background: Evaluating the tumor response to neoadjuvant chemotherapy is key to planning further therapy of breast cancer. Our study aimed to evaluate the effectiveness of low-energy and subtraction contrast-enhanced spectral mammography (CESM) images in the detection of complete response (CR) for neoadjuvant chemotherapy (NAC) in breast cancer. Methods: A total of 63 female patients were qualified for our retrospective analysis. Low-energy and subtraction CESM images just before the beginning of NAC and as a follow-up examination 2 weeks before the end of chemotherapy were compared with one another and assessed for compliance with the postoperative histopathological examination (HP). The response to preoperative chemotherapy was evaluated based on the RECIST 1.1 criteria (Response Evaluation Criteria in Solid Tumors). Results: Low-energy images tend to overestimate residual lesions (6.28 mm) and subtraction images tend to underestimate them (2.75 mm). The sensitivity of low-energy images in forecasting CR amounted to 33.33%, while the specificity was 92.86%. In the case of subtraction CESM, the sensitivity amounted to 85.71% and the specificity to 71.42%. Conclusions: CESM is characterized by high sensitivity in the assessment of CR after NAC. The use of only morphological assessment is insufficient. CESM correlates well with the size of residual lesions on histopathological examination but tends to underestimate the dimensions.

The paper proposes a new method for implementing the parallel multidigit subtraction. The paper provides an analysis on the basis of which it is possible to predict carry signs between words and between groups of words into which multidigit numbers are split on the substracting. The analysis is presented in the form of a lemma. The paper presents an iterative bitwise operation for correcting carry signs for each word in a group of words. An algorithm for implementation the substraction operation using k processors is proposed.

Photon subtraction is useful to produce nonclassical states of light addressed to applications in photonic quantum technologies. After a very accelerated development, this technique makes possible obtaining either single photons or optical cats on demand. However, it lacks theoretical formulation enabling precise predictions for the produced fields. Based on the representation generated by the two-mode $SU(2)$ coherent states, we introduce a model of entangled light beams leading to the subtraction of photons in one of the modes, conditioned to the detection of any photon in the other mode. We show that photon subtraction does not produce nonclassical fields from classical fields. It is also derived a compact expression for the output field from which the calculation of conditional probabilities is straightforward for any input state. Examples include the analysis of squeezed-vacuum and odd-squeezed states. We also show that injecting optical cats into a beam splitter gives rise to entangled states in the Bell representation., Comment: 22 pages, 6 figures

The cosine addition formula on a semigroup S is the functional equation $$g(xy) = g(x)g(y) - f(x)f(y)$$ for all $$x,y \in S$$ . We find its general solution for $$g,f \colon S \to \mathbb{C}$$ , using the recently found general solution of the sine addition formula $$f(xy) = f(x)g(y) + g(x)f(y)$$ on semigroups. A simpler proof of this latter result is also included, with some details added to the solution. We also solve the cosine subtraction formula $$g(x\sigma(y)) = g(x)g(y) + f(x)f(y)$$ on monoids, where $$\sigma$$ is an automorphic involution. The solutions of these functional equations are described mostly in terms of additive and multiplicative functions, but for some semigroups there exist points where f and/or g can take arbitrary values. The continuous solutions on topological semigroups are also found.

Wire ropes (WRs) are widely used in various areas, such as tourist cables, mining, and elevators. Thus, it is very important to detect broken wires (BWs) to prevent safety issues. To guarantee the structural health of WRs, this paper proposes the use of induction thermography (IT) to detect the BWs. An image segmentation algorithm based on scale morphology is proposed to eliminate the background influence of non-uniform heating and visualize the BWs. Further, the area of the BW region, after the image binarization, subtraction, and filtering, is extracted as a feature to quantify the number of BWs. Results show that the proposed methods can effectively visualize and quantify the broken region within 1 BWs.

Intuitionistic fuzzy values, each characterized by a membership degree and a nonmembership degree, are the basic components of intuitionistic fuzzy sets. Arithmetic operations on intuitionistic fuzzy values/sets are of importance in practical problem solving. In this paper, the subtraction and division operations over intuitionistic fuzzy values/sets are derived from the Hamming distance between them by the optimization method. Compared with the existing operations, the developed operations are complete, that is, any two intuitionistic fuzzy values/sets can be performed by these two operations. Then, fundamental properties of the modified arithmetic operations are extensively investigated for intuitionistic fuzzy values/sets. Finally, the continuity and the derivative operation of intuitionistic fuzzy functions are introduced based on the proposed operations, which provides a novel basis for the intuitionistic fuzzy differential calculus .

Background The ability of the patient specific 3D printed neurovascular phantoms to accurately replicate the anatomy and hemodynamics of the chronic neurovascular diseases has been demonstrated by many studies. Acute occurrences, however, may still require further development and investigation and therefore we studied acute ischemic stroke (AIS). The efficacy of endovascular procedures such as mechanical thrombectomy (MT) for the treatment of large vessel occlusion (LVO), can be improved by testing the performance of thrombectomy devices and techniques using patient specific 3D printed neurovascular models. Methods 3D printed phantoms were connected to a flow loop with physiologically relevant flow conditions, including input flow rate and fluid temperature. A simulated blood clot was introduced into the model and placed in the proximal Middle Cerebral Artery (MCA) region. Clot location, composition, length, and arterial angulation were varied and MTs were simulated using stent retrievers. Device placement relative to the clot and the outcome of the thrombectomy were recorded for each situation. Digital subtraction angiograms (DSA) were captured before and after LVO simulation. Recanalization outcome was evaluated using DSA as either ‘no recanalization’ or ‘recanalization’. Forty-two 3DP neurovascular phantom benchtop experiments were performed. Results Clot angulation within the MCA region had the most significant impact on the MT outcome, with a p-value of 0.016. Other factors such as clot location, clot composition, and clot length correlated weakly with the MT outcome. Conclusions This project allowed us to gain knowledge of how such characteristics influence thrombectomy success and can be used in making clinical decisions when planning the procedure and selecting specific thrombectomy tools and approaches.

Objective: The objective of this study was to compare the biomechanical differences of different rod configurations following anterior column realignment (ACR) and pedicle subtraction osteotomy (PSO) for an optimal correction technique and rod configuration that would minimize the risk of rod failure.Methods: A validated spinopelvic (L1-pelvis) finite element model was used to simulate ACR at the L3–4 level. The ACR procedure was followed by dual-rod fixation, and for 4-rod constructs, either medial/lateral accessory rods (connected to primary rods) or satellite rods (directly connected to ACR level screws). The range of motion (ROM), maximum von Mises stress on the rods, and factor of safety (FOS) were calculated for the ACR models and compared to the existing literature of different PSO rod configurations.Results: All of the 4-rod ACR constructs showed a reduction in ROM and maximum von Mises stress compared to the dual-rod ACR construct. Additionally, all of the 4-rod ACR constructs showed greater percentage reduction in ROM and maximum von Mises stress compared to the PSO 4-rod configurations. The ACR satellite rod construct had the maximum stress reduction i.e., 47.3% compared to dual-rod construct and showed the highest FOS (4.76). These findings are consistent with existing literature that supports the use of satellite rods to reduce the occurrence of rod fracture.Conclusion: Our findings suggest that the ACR satellite rod construct may be the most beneficial in reducing the risk of rod failure compared to all other PSO and ACR constructs.

The achievement of the pathologic complete response (pCR) has been considered a metric for the success of neoadjuvant chemotherapy (NAC) and a powerful surrogate indicator of the risk of recurrence and long-term survival. This study aimed to develop a multimodal deep learning model that combined clinical information and pretreatment MR images for predicting pCR to NAC in patients with breast cancer. The retrospective study cohort consisted of 536 patients with invasive breast cancer who underwent pre-operative NAC. We developed a deep learning model to fuse high-dimensional MR image features and the clinical information for the pretreatment prediction of pCR to NAC in breast cancer. The proposed deep learning model trained on all datasets as clinical information, T1-weighted subtraction images, and T2-weighted images shows better performance with area under the curve (AUC) of 0.888 as compared to the model using only clinical information (AUC = 0.827, P

Adaptive subtraction is a well-established routine technique in seismic data processing that relies on being able to match, in some sense, one dataset to another. It is a necessary part of many processing steps such as de-noising and de-multiple. The same matching methods are also used for advanced imaging steps such as non-stationary estimation of the Hessian as part of image-domain least-squares migration. Predictions of noise are often not as accurate as we would like because there are often shortcomings in the prediction method and because pragmatic acquisition compromises are made. The ubiquity of adaptive subtraction in the seismic processing workflow means there is always motivation to improve its performance. In this work, we propose a deep-learning approach for the adaptive subtraction of predicted multiple models from the input recorded data. It turns out that it is straightforward to use deep-learning networks to perform adaptive subtraction and as a result, benefit from the power of complex non-linear filters. Inspired by the idea of a convolutional autoencoder, we have developed a supervised convolutional autoencoder for adaptive subtraction. We demonstrate the proposed approach on synthetic and field data examples and compare the results using conventional adaptive subtraction methods to illustrate the effectiveness of our approach.

Objective: To systematically evaluate the efficacy and safety of Loquat Qingfei Yin (LQFY) in the treatment of acne. Methods: Using computer retrieval, comprehensive collection of the full text database of Chinese journals till December 2020 (CNKI), Wanfang Data Knowledge Service Platform (Wanfang), Viper Database (VIP), PubMed, Cochrane Library, Medline were included in the LQFY addition or subtraction treatment of acne randomized controlled trial (RCT). Screening of the literatures included in the Note Express 3.2.0. Assessment of the risk of bias in trials using Cochrane collaboration tools, and used Rev Man 5.3 to evaluate the curative effect. Results: 25 RCT, all in Chinese, there were 2257 cases. Of the 1216 cases who were treated, control group was 1041 cases. A random effect model was used for Meta analysis. The results showed that the effective rate of the treatment group was significantly higher than that of the control group, Differences were statistically significant (P=0.94, I2=0%), RR=2.87, CI [2.25,95 per cent 3.67], P

Introduction With intra-arterial digital subtraction angiography (DSA) considered as the gold standard, we compared the diagnostic value of computed tomography angiography (CTA) and computed tomography-digital subtraction angiography (CT-DSA in hemodialysis (HD) patients suspected of having lower limb peripheral artery disease (PAD). Methods In this retrospective study, we enrolled 220 HD patients with suspected PAD. CT-DSA images were obtained by subtracting unenhanced images from enhanced images. The research team calculated the area under the curve (AUC), sensitivity, specificity, positive and negative predictive value (PPV, NPV), and recorded the diagnostic accuracy between the CTA and CT-DSA images using the DSA as gold standard. Visual evaluation of calcifications in the peripheral arteries were also compared between CTA and CT-DSA images. Results At the above-knee level, the CTA AUC [95% confidence interval (CI)] was 0.68 (CI 0.64–0.72), sensitivity and specificity were 60 and 81%, PPV and NPV were 85 and 53%, and accuracy was 67%. Below the knee, these values were 0.66 (CI 0.62–0.70), 71 and 79%, 79 and 47%, and 66%. For CT-DSA, above-knee, the AUC [95% CI] was 0.88 (CI 0.85–0.91), sensitivity and specificity were 84 and 92%, PPV and NPV were 89 and 97%, and accuracy was 93%. Below the knee, these values were 0.95 (CI 0.93–0.97), 95 and 93%, 96 and 83%, and 93%. The scores for the visualization of calcification in the peripheral arteries was significantly higher for CT-DSA than CTA (p Conclusions CT-DSA helps to assess stenotic PAD with high calcification in the lower extremities of HD patients. Implications for practice On CT-DSA images, the severity of vascular calcification can be assessed for HD patients suspected of PAD of the lower extremities.

Rapid detection of distortions formed in the welds of metal has high importance to prevent disasters. Radiography images of the weld have an unlimited number of small defects with diverse shapes. Visual inspection of the weld is a complicated, time-consuming task; and depends on the observers' experience. Many computer-aided detection techniques have emerged as an alternative tool for segmenting the flaws of the weld, but none of them could segment alone all types of weld defects. In this paper, we attempt a possible solution and a novel image-based approach to solve the problem of weld defect detection using a data set of X-ray images. We aim to subtract the background and all horizontal defects and segment the non-horizontal flaws. For that, we apply some morphological operations and wiener filter to enhance the image quality; we use two novel filters to segment the non-horizontal defects; finally, we perform a post-processing operation. Our method depends on two convolution processes between the designed filters and the original image to achieve the segmentation process. We tested our approach on a universally available database of 68 images of the weld. Our method achieved high segmentation accuracy with zero errors. We highlighted the academic advancement of our technique by comparing its performance with other methods. Our efficient approach is effortless, applicable in practical segmentation processes of the defects of the weld. In the future, we will dedicate our work to the segmentation of horizontal defects by altering the shape of the two filters. Our method achieves satisfying accuracy; so, it is promising for weld defect detection. The particular contribution of our technique is that it can segment alone all types of weld defects, contrary to traditional weld defect detection methods. The computing time is optimized compared to other algorithms.

Objective To investigate the feasibility of subtraction coronary computed tomographic (CT) angiography (SubCCTA) to decline calcium artifacts and improve diagnostic accuracy in the presence of coronary calcification and analyze the factors that influence SubCCTA. Methods A total of 294 patients suspected of having coronary artery diseases underwent coronary computed tomographic angiography (CCTA) and SubCCTA. Coronary stenoses were blindly evaluated by two experienced radiologists, which were compared with invasive coronary angiography (ICA). Multiple statistical indexes were adopted to analyze the value of SubCCTA for the diagnosis of calcium stenoses. Results The diagnosable rate of SubCCTA was 67.2% (n=197), and the non-diagnosable rate was 32.8% (n=97). Using SubCCTA, the false positive rate decreased from 56.5% to 17.4%, and the corresponding diagnostic accuracy was increased from 83.6% to 92.9%. Univariate logistic regression analysis showed that height (OR=1.029, 95% CI=1.001-1.058), weight (OR=1.025, 95% CI=1.004-1.046), left ventricular size (OR=1.018, 95% CI=1.007-1.030), cardiothoracic ratio (OR=39.917, 95% CI=1.244-1281.098), the average heart rate (OR=0.866, 95% CI=0.836-0.896) and heart rate range (OR=0.882, 95% CI=0.853-0.912) might be the factors influencing SubCCTA. Conclusion This study suggested that SubCCTA could help improve diagnostic accuracy in the presence of calcium plaques. Moreover, several factors were discovered for the first time to possibly influence SubCCTA, which will be helpful in improving the subtracted image quality.

As one of the mathematics objects, the basic facts of mathematics are the primary material that students must master. The facts of addition and subtraction should have been taught in the first level and mastered by the end of the second level. The multiplication and division facts should have been taught at the third level and could be mastered at the fourth level. The primary fact mastery phase consists of a counting phase, a reasoning phase, and a mastering/advanced phase. Mathematics as science should also be accepted by all students regardless of their characteristics, background, or physical needs. They must have the opportunity to learn and be supported to learn mathematics, one of which is a child with special needs slow learner. This research aims to describe the mastery of basic math facts in slow learner children. This is qualitative research, with research subjects totaling three slow learner students of Melana Junior Hight School, Semarang. Subjects are selected by purposive sampling. Data are collected through tests. Time triangulation is used for data validation. Data collection is carried out three times with a gap of 2-3 weeks. The data analysis technique in this research is data reduction, data presentation, and concluding. The research results conclude that the slow learner children are not yet proficient in mastering the basic facts of mathematics. There are slow learner children who can reach the reasoning stage in mastering basic facts, but more are still in the counting stage. Slow learner children who have good basic fact skills have better grades in mathematics. The addition facts are the most effortless facts to master, while the division facts are the most difficult facts to master. Some students can master multiplication facts better than subtraction facts, but some can master subtraction facts more than multiplication facts.

In 2013, the Federal Aviation Administration and Volpe National Transportation System Center conducted a series of acoustic measurements with a propeller driven aircraft operating in the regions near Houston, Texas. The recorded data on octave band sound levels, aircraft locations, temperature and wind speed profiles were used in the current study to quantify the uncertainties for predicting the propagation effects of aircraft noise. Use of the Aviation Environmental Design Tool (AEDT) was explored for its accuracy and validity in real world scenarios offered by the dataset. The sound exposure level (SEL) data for each section of a flight path was used instead of the time history data for reducing the directivity effect of the sound source due to the change in its relative positions with the receivers. A subtraction-based method was introduced to analyze the propagation effect in which the SELs between two receiver locations were compared. The use of the subtraction method reduces the possible influences of the sound power variations along the flight paths. The measured data for a spiral and a level flight event were presented and the AEDT predictions on the propagation effects were examined in this paper.

A computer-generated moire profilometry based on flat image demodulation is proposed. A sinusoidal fringe pattern and its background light are modulated by two-frequency carrier fringes, respectively, to combine a composite grating. While this composite grating is projected onto the measured object, the composite deformed pattern can be captured by CCD camera. So the sinusoidal deformed pattern and its corresponding flat image can be demodulated from the composite deformed pattern. And the AC component of sinusoidal deformed pattern is calculated by the subtraction between the demodulated sinusoidal deformed pattern and the flat image. Compared with normal computer-generated moire profilometry, a more intact AC component can be obtained directly no matter how severe the frequency aliasing condition is. Meanwhile, the three-dimensional (3D) shape of object can be reconstructed only using this composite deformed pattern which shows the application in real-time measurement. Experimental results show the feasibility and validity of the proposed method.