Degrees Deviation Research Articles

CONSTRUCTION OF ANY ANGLE WITHOUT PROTRACTOR

Geometry is one of the foremost significant chapters in mathematics. The construction of angles is one of the important topics of geometry. In geometry, the term construction refers to the precise sketching of shapes, lines, or angles using mathematical instruments. To construct angles, all you'll need is a compass, a ruler, and a pencil, as well as a protractor to measure the angles you've constructed. As there are no numbers involved, this is the simplest type of geometric building. We can only draw some special angles without using a protractor, such as 30, 60, 90, 120, 180, and non-special angles with 1 degree deviation from the needed angles, such as 83, 72, 68, and so on. In our lower secondary school, the method of constructing special angles is commonly taught. We can, however, draw any angle between 0 and 360 degrees using the approach we devised, with no variation from the needed angle. Construction of angle is essential in math because it may be applied to the construction of other geometric shapes, particularly triangles. Keywords: Angle; Intersection Points; Reference Arc; Primary arc

Deep learning method to automatically diagnose periodontal bone loss and periodontitis stage in dental panoramic radiograph.

Artificial intelligence (AI) could be used as an automatically diagnosis method for dental disease due to its accuracy and efficiency. This research proposed a novel convolutional neural network (CNN)-based deep learning (DL) ensemble model for tooth position detection, tooth outline segmentation, tooth tissue segmentation, periodontal bone loss and periodontitis stage prediction using dental panoramic radiographs. The dental panoramic radiographs of 320 patients during the period January 2020 to December 2023 were collected in our dataset. All images were de-identified without private information. In total, 8462 teeth were included. The algorithms that DL ensemble model adopted include YOLOv8, Mask R-CNN, and TransUNet. The prediction results of DL method were compared with diagnosis of periodontists. The periodontal bone loss degree deviation between the DL method and ground truth drawn by the three periodontists was 5.28%. The overall PCC value of the DL method and the periodontists' diagnoses was 0.832 (P <​ 0.001). ​The ICC value was 0.806 (P <​ 0.001). The total diagnostic accuracy of the DL method was 89.45%. The proposed DL ensemble model in this study shows high accuracy and efficiency in radiographic detection and a valuable adjunct to periodontal diagnosis. The method has strong potential to enhance clinical professional performance and build more efficient dental health services. The DL method not only could help dentists for rapid and accurate auxiliary diagnosis and prevent medical negligence, but also could be used as a useful learning resource for inexperienced dentists and dental students.

Angular deformation of the tail in a young foal

SummaryA 1‐week‐old Warmblood female foal was presented for evaluation of an angular deviation of the tail to the left. The foal was able to defaecate normally. Manual straightening of the tail was possible but not completely to its normal position. Radiology revealed a growth deformity of coccygeal vertebrae 6 and 7 (CoV). Spontaneous correction of the tail angle was not expected, and surgical correction was advised. At that moment, the owner decided to wait and the operation was postponed until further notice. After 10 weeks, surgical correction of the angular deviation was undertaken by transphyseal screw placement with hemicircumferential periosteal transection and elevation on the left side of both vertebrae as well as inserting a temporary external fixator in which the end was distracted. Three weeks after surgery, the pins were removed. At the follow‐up examination 12 months after initial surgery, the deviation was nearly corrected and reduced to ca. 10 degrees deviation, and the owner was satisfied with the obtained result. No loss of sensory or motor function had occurred.

Impact of freeway slope photovoltaic panels on drivers: A study based on driving simulator

Aiming at the impact of freeway slope photovoltaic construction on driving safety, a driving simulator experiment was carried out. By designing eight slope photovoltaic schemes under varying sunlight conditions and road alignment parameters, we recruited 35 drivers to collect detailed driving behavior data. Seven driving indicators were selected to develop an evaluation index system. Statistical analysis was conducted to compare driver behavioral performance under eight slope photovoltaic schemes. The findings reveal that the installation of photovoltaic panels on freeway slopes significantly affects driving behavior. Specifically, the driver's speed and degree of steering wheel angle decreased significantly, while acceleration increased significantly on straight alignment. The standard deviation of driver speed, acceleration and standard deviation of acceleration significantly reduced, while the degree of steering wheel angle and the depth of the gas pedal significantly increased when photovoltaic panels were laid on the side slopes on curved road sections. In addition, different curve radius, the impact of photovoltaic panels on acceleration and degree of steering wheel turning angle were different. There is a significant effect of installing side slope photovoltaic panels on driver acceleration, standard deviation of acceleration and degree of steering wheel turning angle in curved sections with different curve radius. Under different sunlight conditions, the impact of photovoltaic panels on the degree of steering wheel angle were also different. The actual setup needs to take into account the impact of different road alignments on drivers. The is study provided theoretical support for the installation of freeway slope photovoltaic panels.

Experimental investigation of SRS polarization pulling in depleted pump regime for various pump SOPs

This article presents an experimental investigation of polarization pulling based on stimulated Raman scattering induced by a continuous, fully polarized pump wave in an optical fibre. By means of probe wave states of polarization aggregation, degree of polarization and gain analysis, an assessment of all-optical polarization control, repolarization and amplification in a standard single mode fibre in depleted pump regime is presented. Polarization pulling is proved to be dependent on fibre length, pump power, and pump state of polarization, with respect to pump depletion effect, acting oppositely to the polarization pulling effect. Authors evaluate results aiming to obtain a configuration of stimulated Raman scattering parameters, which allows for the most effective polarization pulling, with respect to statistical stability of the process measured by standard deviation of polarization degree and polarization-dependent gain of the probe wave. The highest polarization attraction efficiency was obtained for 15 km, 0.97 W and the horizontal polarization state of the pump wave.

Financial risk contagion based on dynamic multi-layer network between banks and firms

Banks and firms play pivotal roles within the financial system and serve as primary channels for systemic risk contagion. While progress has been made in understanding risk contagion within financial network systems, many studies tend to overlook the intricate interplay of multi-channel risk transmission and the dynamic evolution of network structures. Leveraging complex network theory, we have developed a dynamic multi-layer financial network risk transmission model that encompasses traditional bank–firm lending relationships and incorporates dynamic short-term loans. Through our analysis of various parameters such as loan recovery ratios, cross-shareholding ratios, network structures, short-term loan ratios, and attack strategies, we have made significant observations: In scenarios where both the interbank lending network and cross-shareholding network among firms exhibit random network structure, the financial network presents the highest level of risk. Excessive deviations in network average degrees, either too high or too low, can also heighten network vulnerability. An increase in the recovery ratio of interbank loans and the cross-shareholding ratio among firms corresponds to an escalation in systemic risk. Nodes with higher lending assets, more liquid assets, greater total assets, or higher out-degrees within the network become significant contributors to an elevated network bankruptcy rate when subjected to targeted attacks. Notably, the dynamic short-term loan network significantly amplifies systemic risks, with this amplification effect intensifying as the scale of short-term loans increases. From both macro and micro perspectives, our findings furnish regulatory authorities with novel analytical tools and insights to effectively mitigate and manage systemic risks in the financial sector.

Abstract WP137: A CT Perfusion Based Computational Modeling for Improved Risk Stratification of Haemodynamically Significant ICAD

Aim: In endovascular ICAD treatment, an individualized patient-specific treatment pathway may be very helpful. Patient selection for endovascular treatment based on anatomical markers has not been shown to be effective in past clinical trials. This pilot study combines CT perfusion (CTP) analysis and computational fluid dynamics to identify hemodynamically significant patients for a reliable pathway for intervention planning. Methods: We assessed patients from two stroke centers with 50-99% ICAD lesions. Using a novel technique, CTP scans generated acute vascular territory maps for major cerebral arteries (ACA,MCA,PCA) with perfusion Time-to-peak (TTP) maps. Patient-specific blood flow simulations using physiology-informed boundary conditions calculated stenotic pressure ratios for both the patient’s acute and a population-based healthy scenario. The changes in affected territory volumes and pressure ratio between healthy and acute conditions and the acute TTP delays were presented to an expert reader who stratified cases into three clinical groups (A) non-hemodynamic, (B) hemodynamically hazardous with insufficient collateral support and (C) hemodynamically stable due to collateralisation. These results were compared against patient outcomes of recurrent ischemic events attributed to the target stenosis using the commonly used 70% threshold. Results: (95%CI in brackets) Patients (n=47, age: 73±11Y, 23F/24M) were stratified across the three categories A) 30, B) 15, C) 2. Of the patient groups with follow-up (n=31), categorisation of hemodynamic ICAD against recurrent ipsilateral stroke in territory (n=8) yielded a sensitivity of 75% [34-97] and specificity of 91% [72-98]. Mean±standard deviation of stenosis degree (SD) 55±14% for patients across each cohort was A) 50±11%, B) 70±9%, C) 70%. This is compared to using 70% stenosis threshold for dichotomising patients against risk of recurrent stroke, which yielded a sensitivity of 62.5% [24-91], and specificity of 87% [66-97]. Conclusions: We report on a CTP derived method for stratifying hemodynamically significant ICAD. The methodology has potential in both in assessing symptomatic chronic ICAD and identifying cohorts who would benefit from endovascular intervention.

IoU_MDA: An Occluded Object Detection Algorithm Based on Fuzzy Sample Anchor Box IoU Matching Degree Deviation Aware

IoU_MDA: An Occluded Object Detection Algorithm Based on Fuzzy Sample Anchor Box IoU Matching Degree Deviation Aware

One out of ten independent components shows flipped polarity with poorer data quality: EEG database study.

Independent component analysis (ICA) is widely used today for scalp-recorded EEG analysis. One of the limitations of ICA-based analysis is polarity indeterminacy. It is not easy to find detailed documentations that explains engineering solutions of how the polarity indeterminacy is addressed in a given implementation. We investigated how it is implemented in the case of EEGLAB and also the relation between the outcome of the polarity determination and classification of independent components (ICs) in terms of the estimated nature of the sources (brain, muscle, eye, etc.) using an open database of n = 212 EEG dataset of resting state recordings. We found that (1) about 91% of ICs showed positive-dominant IC scalp topographies; (2) positive-dominant ICs were more associated with brain-originated signals; (3) positive-dominant ICs showed more radial (peaked at 10-30 degrees deviations from the radial axis) dipolar projection pattern with less residual variance from fitting the equivalent current dipole. In conclusion, using the EEGLAB's default ICA algorithm, one out of 10 ICs results in flipping its polarity to negative, which is associated with non-radial dipole orientation with higher residual variance. Thus, we determined EEGLAB biases toward positive polarity in decomposing high-quality brain ICs.

A three-parameter interval number group decision-making method based on kernel and greyness degree

A decision method based on kernel and greyness degree is proposed for group decision-making problems in which attribute values are represented by three-parameter interval grey numbers, whose kernel and greyness degree are modified. The prospect value of each program’s evaluation information given by decision-makers is solved by using prospect theory. Finally, the reasonable decision-makers weight should make the total weighted prospect value of the scheme the maximum, the deviation between the evaluation information of each decision-maker, the mean value of the evaluation information the minimum, and the greyness degree deviation value of the information which is given by decision makers the minimum. The weight vector of the decision-makers is obtained by solving this model, and the comprehensive prospect value of the solution is used to rank the alternatives. Finally, taking a commercial aircraft parts supplier selection as an example, the rationality of the method is verified.

Convolutional-neural-network-based radiographs evaluation assisting in early diagnosis of the periodontal bone loss via periapical radiograph

Background/PurposeThe preciseness of detecting periodontal bone loss is examiners dependent, and this leads to low reliability. The need for automated assistance systems on dental radiographic images has been increased. To the best of our knowledge, no studies have quantitatively and automatically staged periodontitis using dental periapical radiographs. The purpose of this study was to evaluate periodontal bone loss and periodontitis stage on dental periapical radiographs using deep convolutional neural networks (CNNs). Materials and methods336 periapical radiographic images (teeth: 390) between January 2017 and December 2019 were collected and de-identified. All periapical radiographic image datasets were divided into training dataset (n = 82, teeth: 123) and test dataset (n = 336, teeth: 390). For creating an optimal deep CNN algorithm model, the training datasets were directly used for the segmentation and individual tooth detection. To evaluate the diagnostic power, we calculated the degree of alveolar bone loss deviation between our proposed method and ground truth, the Pearson correlation coefficients (PCC), and the diagnostic accuracy of the proposed method in the test datasets. ResultsThe periodontal bone loss degree deviation between our proposed method and the ground truth drawn by the three periodontists was 6.5 %. In addition, the overall PCC value of our proposed system and the periodontists’ diagnoses was 0.828 (P < 0.01). The total diagnostic accuracy of our proposed method was 72.8 %. The diagnostic accuracy was highest for stage III (97.0 %). ConclusionThis tool helps with diagnosis and prevents omission, and this may be especially helpful for inexperienced younger doctors and doctors in underdeveloped countries. It could also dramatically reduce the workload of clinicians and timely access to periodontist care for people requiring advanced periodontal treatment.

Misperception of Visual Verticality Measured with a Virtual Reality Device in Patients with Fibromyalgia Syndrome: A Cross-Sectional Study

The objective of this study was to analyze the perception of visual verticality (VV) in subjects with Fibromyalgia Syndrome (FMS) and to correlate this with the symptoms of the disease and balance capacity. A cross-sectional study including 54 patients (51 female) was conducted. The evaluation of visual verticality was carried out with a virtual reality device by calculating the Mean Absolute Error (MAE) of degrees deviation in two tests: the Subjective Visual Vertical (SVV) test for the contribution of the vestibular system to the perception of verticality and the Rod and Frame test (RFT) for the contribution of the visual system. In total, 16 subjects (29.6%) presented good VV perception, 6 subjects (11.1%) presented an exclusive alteration of the SVV test, 19 subjects (35.2%) presented an exclusive alteration of the RFT and 13 subjects (24.1%) showed alteration in the two tests. The MAE in the SVV test showed medium correlations with several variables such as the Fibromyalgia Impact Questionnaire (FIQ) (Rho = 0.399, p = 0.003), the Pain Catastrophizing Scale (PCS) (Rho = 0.417, p = 0.002), the Dizziness Handicap Inventory (DHI) (Rho = 0.376, p = 0.005), and the Activities-Specific Balance Confidence Scale (ABC-16) (Rho = −0.367, p = 0.006). The MAE in the RFT showed medium correlations with the Instability Support Reduced (Rho = 0.327, p = 0.016) and Instability Gait Eyes Open (Rho = 0.312, p = 0.022) subscales of the JAEN (Joined Assessment of Equilibrium and Neuro-motor) Scale. Conclusions: Around 70% of the subjects with FMS showed some alteration in the perception of VV; 60% of these patients presented visual system dependence. The SVV test correlates with the impact and health status of FMS, and the RFT correlates with the alteration in the dynamic balance.

SliceLRF: A Local Reference Frame Sliced along the Height on the 3D Surface.

The local reference frame (LRF) plays a vital role in local 3D shape description and matching. Numerous LRF methods have been proposed in recent decades. However, few LRFs can achieve a balance between repeatability and robustness under exposure to a variety of nuisances, including Gaussian noise, mesh resolution variation, clutter, and occlusion. Additionally, most LRFs are heuristic and lack generalizability to different applications and data modalities. In this paper, we first define the degree of distinction to describe the distribution of 2D point clouds and explore the relationship between the relative deviation of the distinction degree and the LRF error through experiments. Based on Gaussian noise and a random sampling analysis, several factors that affect the relative deviation of the distinction degree and result in the LRF error are identified. A scoring criterion is proposed to evaluate the robustness of the point cloud distribution. On this basis, we propose an LRF method (SliceLRF) based on slicing along the Z-axis, which selects the most robust adjacent slices in the point cloud region by scoring criteria for X-axis estimation to improve the repeatability and robustness. SliceLRF is rigorously tested on four public benchmark datasets which have different applications and involve different data modalities. It is also compared with the state-of-the-art LRFs. The experimental results show that the SliceLRF has more comprehensive repeatability and robustness than the other LRFs under exposure to Gaussian noise and random sampling.

Irregularity Measure of Graphs

A simple graph G is said to be regular if its vertices have the same number of neighbors. Otherwise, G is nonregular. So far, various formulas, such as the Albertson index, total Albertson index, and degree deviation, have been introduced to quantify the irregularity of a graph. In this paper, we present sharp lower bounds for these indices in terms of the order, size, maximum degree, minimum degree, and forgotten and Zagreb indices of the underlying graph. We also prove that if G has the minimum value of degree deviation, among all nonregular n , m -graphs, then Δ G − δ G = 1 .

Accuracy of dental implant placement with or without the use of a dynamic navigation assisted system: A randomized clinical trial.

To assess dental implant placement accuracy with a dynamic computer-assisted implant surgery (dCAIS) system and a freehand approach. Secondarily, to compare the patients' perception and quality of life (QoL) with the two approaches. A double-arm randomized clinical trial was conducted. Consecutive partially edentulous patients were randomly allocated to the dCAIS or standard freehand approach groups. Implant placement accuracy was evaluated by overlapping the preoperative and postoperative Cone Beam Computer Tomographs (CBCT) and recording linear deviations at the implant apex and platform (in mm) and angular deviations (in degrees). Questionnaires recorded self-reported satisfaction, pain and QoL during surgery and postoperatively. Thirty patients (22 implants) were enrolled in each group. One patient was lost to follow-up. A significant difference (p < .001) in mean angular deviation was found between the dCAIS (4.02°; 95% CI: 2.85 to 5.19) and the FH (7.97°; 95% CI: 5.36 to 10.58) groups. Linear deviations were significantly lower in the dCAIS group, except for the apex vertical deviation, where no differences were found. Although dCAIS took 14 min longer (95% CI: 6.43 to 21.24; p < .001), patients in both groups considered the surgical time acceptable. Postoperative pain and analgesic consumption during the first postoperative week were similar between groups and self-reported satisfaction was very high. dCAIS systems significantly increase the accuracy of implant placement in partially edentulous patients in comparison with the conventional freehand approach. However, they increase the surgical time significantly and do not seem to improve patient satisfaction or reduce postoperative pain.

Synergy/trade-offs and differential optimization of production, living, and ecological functions in the Yangtze River economic Belt, China

The high-quality development of the Yangtze River Economic Belt (YREB) is a major strategy related to China’s overall national development. Based on the synergy/trade-offs of production, living, and ecological functions (PLEFs) in the YREB from 2000 to 2020, this paper puts forward suggestions for the optimization of territorial space to promote the high-quality development of the YREB. The mechanistic equilibrium model was applied to determine the synergy/trade-off relationship of PLEFs, and the key factors affecting the coordination degree were analyzed with the help of a geographical detector and a geographically weighted regression (GWR) model to further identify the trade-off zones and propose differential optimization strategies. The results showed that the average degree of synergy of PLEFs decreased from 0.18 to 0.08 in YREB during the study period, and the coordination developed to a higher level, forming a local patchwork of coordination “highlands” in space, with a gradient divergence of coordination from west to east. The land-use degree, landscape, slope, traffic, and nightlight index were the dominant factors influencing PLEFs, and their q-values were 0.30, 0.27, 0.20, 0.18 and 0.14 in order, with significant spatial differences in the effects of each factor’s role. Based on the deviation of the coordination degree of PLEFs, three major function-dominated zones were divided, and it was found that the YREB showed an evolutionary trend of ecological function domination (2000) to production function domination (2010) to ecological function domination (2020). The trade-off zones in antagonistic and dysregulated states were further identified, and the study proposed targeted optimization strategies. The findings provide theoretical reference to promote the sustainable use of territorial resources and high-quality regional development in the YREB and the rest of the country.

Ground Improvement of Dhu Al-Kifil Minaret Using Micropile and Cement Grouting

The Minaret of Dhu Al-Kifil Nabi (PBUH), located in the city of Kifil with a height of about 25 meters, is one of the historical monuments of Iraq. The 4.5 degree deviation of this Minaret has become a challenge for authorities in recent years. Various reasons, such as the old age of the building and manipulation of the soil of the minaret bed, damage the structure and have caused it to deviate from the vertical direction and form cracks at its height. A temporary metal retaining structure is currently constructed on the site to maintain the building in its current state. Still, in order to remove it and repair the body and foundation of the Minaret, the designs have been carried out by Iranian engineering groups. After that, its strengthening operations have also finished. In this article, after the introduction of the project, the analytical and numerical results of the bed improvement plan using the combination of inclined and vertical micropiles are presented. Finally, the reliability of the plan in controlling the heterogeneous settlement of the Minaret is assessed.

CONSTRUCTION OF ANY ANGLE WITHOUT PROTRACTOR

Geometry is one of the foremost significant chapters in mathematics. Construction of angles is one of the important aspects of geometry. The term construction in geometry refers to drawing shapes, lines, or angles accurately with the assistance of mathematical instruments. You will simply need a compass, a ruler (straightedge), and a pencil to construct angles, and a protractor to measure the constructed angle. This is the pure form of geometric construction as no numbers are involved in it. We can only draw some special angles without employing a protractor, such as 30, 60, 90, 120, 180, etc. and non-special angles such as 83, 72, 68, etc. with 1or 2 degrees deviation from the required angles. The method of constructing special angles is generally taught in our lower secondary school. However, using the strategy we devised, we will draw any angle between 0 and 360 degrees without any deviation from the required angle. Constructing angles is important in maths as this method can be extended for the construction of other geometric figures as well, primarily triangles. Keywords: Angle, Degree, Intersection Points, Reference Arc, Primary arc

In English

Electrochemical impedance spectroscopy has been used for the characterization of electric double layer capacitors also known as supercapacitors. Specific surface area and pore size distribution for supercapacitor electrode materials and the results of impedance spectroscopy measurements for two types of commercially available nanoporous activated carbons and two graphene-type materials have been studied and compared with the results obtained from cyclic voltammetry and galvanostatic charge-discharge cycling the supercapacitor prototypes in different voltage ranges and at different current densities. It has been found that the results for the characteristics of studied supercapacitor prototypes differ insignificantly if they were obtained by different methods, while all three research methods have shown the advantage of materials with nanoporous activated carbon over materials of the graphene type. Besides, according to the data obtained by measuring impedance at low frequencies the deviations from ideal capacitive behaviour are more significant in case of graphene-type materials. Comparison of the three research methods used in this work shows that the method of impedance spectroscopy makes it possible to obtain the most complete and reliable information on the performance characteristics of the supercapacitor system, since not only the capacitance and resistance values, but their frequency dependence, as well as deviations (in degrees) from the purely capacitive vertical line at Nyquist plots and capacitance dissipation can be determined and taken into consideration.

Identification of ESCC Potential Biomarkers using Biclustering Algorithms

An extensive empirical study is presented in this work to identify potential biomarkers of ESCC by employing fifteen prominent biclustering algorithms on synthetic and real datasets. For systematic analyses, we implement the algorithms on a variety of synthetic datasets and evaluate the quality of biclusters using recovery and relevance scores. The biclustering algorithms showing adequate results on synthetic datasets are implemented on real ESCC microarray dataset of both normal and disease samples separately. Gene enrichment analysis has been carried out to recognize the best possible bicluster(s) of individual algorithms. Our approach exploits the set of best possible biclusters in the downstream analysis towards the identification of the potential biomarkers with reference to a set of established elite genes for ESCC. Our approach depends on Pearson correlation, conversion of floating valued correlation matrix into a binary matrix, degree analysis based on elite genes, deviation of degree in their respective mapping bicluster, significant alteration of gene expression values while transitioning from normal to disease conditions, and gene ontology and pathway analyses. Finally, we detect 9 ESCC potential biomarker genes; SH3GLB1, ARPC2, APPL1, CALM1, FTL, LPAR1, PLAU, PSMB4, and SCP2; which shows the topological as well as biological significance of ESCC elite genes.