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Radio-frequency identification technology finds extensive use in various industrial applications, including those involving metallic surfaces. The integration of radio-frequency identification systems with metal surfaces, such as those found in the automotive sector, presents distinct challenges that can notably affect system efficacy due to metal's tendency to reflect electromagnetic waves, thus degrading the functionality of conventional radio-frequency identification tags. This highlights the importance of conducting research into academic publications and patents to grasp the current advancements and challenges in this field, aiming to improve the applications of radio-frequency identification tags technology on metal. Consequently, this research undertakes a concise review of both the literature and patents exploring radio-frequency identification technology's use for on-metal tags, utilizing resources like Google Scholar and Google Patents. The research categorized crucial aspects such as tag flexibility, operating frequency, and geographic origins of the research. Findings highlight China's prominent role in contributing to metal-focused radio-frequency identification tag research, with a considerable volume of articles and patents. In particular, flexible tags and the Ultra-High Frequency range are dominant in both scholarly and patent documents, reflecting their significance in radio-frequency identification technology applications. The research underscores a vibrant area of development within radio-frequency identification technology, with continued innovation driven by specific industrial needs. Despite the noted advances, the presence of a significant percentage of no longer valid patents suggests substantial opportunities for further research and innovation in radio-frequency identification technology for on-metal applications, especially considering the demand for flexible tags and for solutions in systems that offer specialized characteristics or are tailored for specific uses. [ABSTRACT FROM AUTHOR]

Simple Summary: This study aimed to improve the precision of classifying pulmonary lesions as malignant using a new scoring system called 'LIONS PREY' (Lung lesION Score PREdicts malignancY). The new model, developed through the evaluation of a patient cohort from a single center, incorporates eight parameters, including age, nodule size, spiculation, solidity, size dynamics, smoking history, pack years, and cancer history. LIONS PREY demonstrates excellent precision and might facilitate decision making for multidisciplinary teams. Furthermore, it may help patients make informed decisions about surgery. The LIONS PREY app is available for free on Android and iOS devices. Objectives: Classifying radiologic pulmonary lesions as malignant is challenging. Scoring systems like the Mayo model lack precision in predicting the probability of malignancy. We developed the logistic scoring system 'LIONS PREY' (Lung lesION Score PREdicts malignancY), which is superior to existing models in its precision in determining the likelihood of malignancy. Methods: We evaluated all patients that were presented to our multidisciplinary team between January 2013 and December 2020. Availability of pathological results after resection or CT-/EBUS-guided sampling was mandatory for study inclusion. Two groups were formed: Group A (malignant nodule; n = 238) and Group B (benign nodule; n = 148). Initially, 22 potential score parameters were derived from the patients' medical histories. Results: After uni- and multivariate analysis, we identified the following eight parameters that were integrated into a scoring system: (1) age (Group A: 64.5 ± 10.2 years vs. Group B: 61.6 ± 13.8 years; multivariate p-value: 0.054); (2) nodule size (21.8 ± 7.5 mm vs. 18.3 ± 7.9 mm; p = 0.051); (3) spiculation (73.1% vs. 41.9%; p = 0.024); (4) solidity (84.9% vs. 62.8%; p = 0.004); (5) size dynamics (6.4 ± 7.7 mm/3 months vs. 0.2 ± 0.9 mm/3 months; p < 0.0001); (6) smoking history (92.0% vs. 43.9%; p < 0.0001); (7) pack years (35.1 ± 19.1 vs. 21.3 ± 18.8; p = 0.079); and (8) cancer history (34.9% vs. 24.3%; p = 0.052). Our model demonstrated superior precision to that of the Mayo score (p = 0.013) with an overall correct classification of 96.0%, a calibration (observed/expected-ratio) of 1.1, and a discrimination (ROC analysis) of AUC (95% CI) 0.94 (0.92–0.97). Conclusions: Focusing on essential parameters, LIONS PREY can be easily and reproducibly applied based on computed tomography (CT) scans. Multidisciplinary team members could use it to facilitate decision making. Patients may find it easier to consent to surgery knowing the likelihood of pulmonary malignancy. The LIONS PREY app is available for free on Android and iOS devices. [ABSTRACT FROM AUTHOR]

There is a need of simple, inexpensive, and reliable noninvasive testing to predict coronary artery disease (CAD) in patients with chronic kidney disease (CKD), where the prevalence of cardiovascular (CV) events and death is elevated. We analyzed the association between peripheral artery disease (PAD) and CAD in 201 patients with stage 5 CKD on dialysis using a prospective observational cohort. Diagnosis of PAD by both palpation and USD were significantly correlated. In patients with PAD diagnosed by palpation, CAD was observed in 80%, while in those diagnosed by USD, CAD was present in 79.1%. The absence of a pulse by palpation predicted CAD with a sensitivity of 55% and a specificity of 76%; USD showed a sensitivity of 62% and specificity of 60% to predict CAD. The risk of combined serious CV events and death was significantly higher in subjects with PAD diagnosed by palpation, but not by USD. PAD assessed by palpation also correlated with the occurrence of multivessel CAD and with the probability of coronary intervention. Both methods are moderately useful for predicting CAD, but PAD diagnosis by palpation was a better predictor of combined CV events and death and was also associated with CAD severity and likelihood of intervention. [ABSTRACT FROM AUTHOR]

On one side, the capacity of the world's photovoltaic (PV) systems is experiencing unprecedented growth; on the other side, the number of connected devices is rapidly increasing due to the development of advanced communication technologies. These fields are not completely independent, and recent studies show that indoor energy harvesting is a great candidate for answering the energy challenges of future generations of telecommunications, namely 5G and 6G, ideal for internet-of-things (IoT) scenarios, i.e., smart homes, smart cities, and smart factories. The emerging PV technologies have shown amazing capabilities for indoor energy harvesting, displaying high power conversion efficiency, good flexibility, and champion-specific powers. Recently, the excellent dynamic performance of PV devices enabled them to be used as data receivers in optical wireless communication (OWC) scenarios, calling forth an innovative system able to simultaneously harvest energy and receive communication data with a single PV device. This article reviews the recent literature devoted to the exploitation of photovoltaic technologies for simultaneous indoor energy harvesting and OWC data reception. This contribution highlights the strong potential of the approach toward the next generation of Green IoT systems and the current challenges that need to be addressed with regard to the physics of solar cells, from laboratory to large-scale applications. [ABSTRACT FROM AUTHOR]

Background: Injury to the distal tibiofibular syndesmosis (DTFS) is common in patients with trauma to the ankle, but diagnostic accuracy of conventional X-ray and CT is insufficient. A novel dual energy CT (DECT) post-processing algorithm enables color-coded mapping of collagenous structures, which can be utilized to assess the integrity of the DTFS. Methods: Patients were included in this retrospective study if they underwent third-generation dual-source DECT followed by 3T-MRI or ankle joint surgery within 14 days between January 2016 and December 2021. Three radiologists blinded to all patient data independently evaluated grayscale images and, after 8 weeks, grayscale and collagen mapping images for the presence of ligamentous injury or avulsion fractures of the DTFS. MRI and surgery provided the reference standard. Diagnostic accuracy parameters were calculated for all ratings, and a comparison of ROC curve analysis was performed to evaluate the incremental diagnostic value of color-coded images over grayscale images. Results: A total of 49 patients (median age 49 years; 32 males) were evaluated. Application of collagen mapping significantly increased sensitivity (25/30 [83%] vs. 20/30 [67%]), specificity (110/118 [93%] vs. 70/118 [60%]), positive predictive value (25/33 [76%] vs. 20/67 [30%]), negative predictive value (110/115 [96%] vs. 70/80 [88%]), and accuracy (134/147 [91%] vs. 90/147 [61%]) for the detection of injury to the DTFS (all parameters, p < 0.001). Collagen mapping achieved higher diagnostic confidence, image quality, and noise scores compared to grayscale CT (all parameters, p < 0.001). Conclusions: Collagen mapping yields substantially higher diagnostic accuracy and confidence for assessing the integrity of the distal tibiofibular syndesmosis compared to grayscale CT in patients with acute trauma. The application of this algorithm can accelerate the adequate diagnosis and treatment of DTFS injury in clinical routine. [ABSTRACT FROM AUTHOR]

Simple Summary: Portal vein infiltration (PVI) is a complication of HCC with critical impact on further patient management as systemic therapies are recommended once PVI is diagnosed. In our study, we matched 44 patients with HCC who developed PVI in the course of disease with no CT-detectable PVI at initial diagnosis to the same number of patients who never developed PVI during follow-up, but showed the same conventional tumor traits (size and number of lesions, growth type, contrast enhancement pattern, etc.). Using LASSO regression, radiomics feature analysis showed a sensitivity and specificity of 0.78 to detect the occurrence of PVI in the validation set. Therefore, an additional radiomics evaluation at initial diagnosis could help to identify patients benefiting from a closer surveillance. Portal vein infiltration (PVI) is a typical complication of HCC. Once diagnosed, it leads to classification as BCLC C with an enormous impact on patient management, as systemic therapies are henceforth recommended. Our aim was to investigate whether radiomics analysis using imaging at initial diagnosis can predict the occurrence of PVI in the course of disease. Between 2008 and 2018, we retrospectively identified 44 patients with HCC and an in-house, multiphase CT scan at initial diagnosis who presented without CT-detectable PVI but developed it in the course of disease. Accounting for size and number of lesions, growth type, arterial enhancement pattern, Child–Pugh stage, AFP levels, and subsequent therapy, we matched 44 patients with HCC who did not develop PVI to those developing PVI in the course of disease (follow-up ended December 2021). After segmentation of the tumor at initial diagnosis and texture analysis, we used LASSO regression to find radiomics features suitable for PVI detection in this matched set. Using an 80:20 split between training and holdout validation dataset, 17 radiomics features remained in the fitted model. Applying the model to the holdout validation dataset, sensitivity to detect occurrence of PVI was 0.78 and specificity was 0.78. Radiomics feature extraction had the ability to detect aggressive HCC morphology likely to result in future PVI. An additional radiomics evaluation at initial diagnosis might be a useful tool to identify patients with HCC at risk for PVI during follow-up benefiting from a closer surveillance. [ABSTRACT FROM AUTHOR]

This study aims to evaluate the prevalence, distribution and clinical profile of neurological diseases and syndromes from a neurology outpatient clinic in the city of Rio de Janeiro. This is a quantitative, cross-sectional study. 180 medical records of firsttime visits conducted through 18 months were analyzed. Age, gender and comorbidities were collected to identify the sample's profile and the neurological diagnoses found were classified in predefined groups of syndromes according to the ICD-10 classification, which were further stratified according to age and gender. 157 (87,2%) of the patients had a neurological disease, of which the mean age was 51,05 years and 67,5% were women. The most frequent comorbidities were: hypertension (55,6%); dyslipidemia (20,4%); and diabetes (14,6%). The most common neurological diseases were: Sequelae of Cerebrovascular Disease (12,7%); Unspecified Dementia (8,9%); and Migraine without Aura (7,6%). The main neurological syndromes were: Headache (24,8%); Dementia (15,9%); Cerebrovascular Disease (13,4%); Movement Disorders (12,1%); and Radiculopathy (10,8%). The age and gender profile of these syndromes was further described. These data contribute to better understand the distribution of neurological diseases in the neurological outpatient setting. [ABSTRACT FROM AUTHOR]

This work proposes hybrid models combining time-series models (using linear functions) and artificial intelligence (using a nonlinear function) that can be used to provide monthly mean wind speed predictions for the Brazilian northeast region. These might be useful for wind power generation; for example, they could acquire important information on how the local wind potential can be usable for a possible wind power plant through understanding future wind speed values. To create the proposed hybrid models, it was necessary to set the wind speed variable as a dependent variable of exogenous variables (i.e., pressure, temperature, and precipitation). Thus, it was possible to consider the meteorological characteristics of the study regions. It is possible to verify the hybrid models' efficiency in providing perfect adjustments to the observed data. This statement is based on the low values found in the error statistical analysis, i.e., an error of approximately 5.0% and a Nash-Sutcliffe coefficient near to 0.96. These results were certainly important in predicting the wind speed time-series, which was similar to the observed wind speed time-series profile. Great similarities of maximums and minimums between the series were evident and showed the capacity of the models to represent the seasonality characteristics. [ABSTRACT FROM AUTHOR]

Understanding the supramolecular environment of crystal structures is necessary to facilitate designing molecules with desirable properties. A series of 12 novel 1,3,5-tris(1-phenyl-1H-pyrazol-5-yl)benzenes was used to assess the existence of planar stacking columns in supramolecular structures of pyrazoles. This class of molecules with different substituents may assist in understanding how small structural changes affect the supramolecular environment. The obtained compounds did not present the formation of planar stacking interactions between benzenes in solid or liquid states. This supposition was indicated by single crystal diffraction, Density Functional Theory (DFT) and quantum theory of atoms in molecules (QTAIM) calculations, and concentration-dependent liquid-state H nuclear magnetic resonance (NMR). NMR showed that chemical shifts of benzene and pyrazole hydrogens confirm that planar stacking interactions are not formed in solution. The crystalline structures presented different molecular conformations. The molecular structures of 5 and 9b are in a twisted conformation, while compound 7 showed a conformation analogous to a calyx form. [ABSTRACT FROM AUTHOR]

Simple Summary: The novel CRP–albumin–lymphocyte (CALLY) index has been identified as a highly predictive tool for stratification of patients with hepatocellular carcinoma (HCC) who have undergone tumor resection. This study aimed to validate the predictive ability of the CALLY index in patients with HCC treated with transarterial chemoembolization (TACE). The CALLY index was an independent prognostic predictor for overall survival. However, the CALLY index was not superior to other immunonutritive and inflammation scoring systems in predicting the median OS, although all of the individual parameters of the CALLY index were predictive for the median OS. Thus, future studies should re-evaluate the mathematical calculation of the index for patients with HCC undergoing TACE. The novel CRP–albumin–lymphocyte (CALLY) index is an improved immunonutritive scoring system, based on serum C-reactive protein (CRP), serum albumin, and the lymphocyte count. It has shown promise as a prognostic index for patients with hepatocellular carcinoma (HCC) undergoing resections. This study evaluated the prognostic ability of the CALLY index for patients with HCC undergoing transarterial chemoembolization (TACE). We retrospectively identified 280 treatment-naïve patients with HCC that underwent an initial TACE at our institution, between 2010 and 2020. We compared the CALLY index to established risk factors in univariate and multivariate regression analyses for associations with median overall survival (OS). A low CALLY score was associated with low median OS (low vs. high CALLY: 9.0 vs. 24.0 months, p < 0.001). In the multivariate analysis, the CALLY index remained an independent prognostic predictor (p = 0.008). Furthermore, all factors of the CALLY index reached significance in univariate and in-depth multivariate analyses. However, the concordance index (C-index) of the CALLY index (0.60) was similar to the C-indices of established immunonutritive and inflammation scoring systems (range: 0.54 to 0.63). In conclusion, the CALLY index showed promise as a stratification tool for patients with HCC undergoing TACE. Notably, the CALLY index was not superior to other immunonutritive and inflammation scoring systems in predicting the median OS. Thus, future studies should re-evaluate the mathematical calculation of the index, particularly the contributions of individual parameters. [ABSTRACT FROM AUTHOR]

Successful adoption of artificial intelligence (AI) in medical imaging requires medical professionals to understand underlying principles and techniques. However, educational offerings tailored to the need of medical professionals are scarce. To fill this gap, we created the course "AI for Doctors: Medical Imaging". An analysis of participants' opinions on AI and self-perceived skills rated on a five-point Likert scale was conducted before and after the course. The participants' attitude towards AI in medical imaging was very optimistic before and after the course. However, deeper knowledge of AI and the process for validating and deploying it resulted in significantly less overoptimism with respect to perceivable patient benefits through AI (p = 0.020). Self-assessed skill ratings significantly improved after the course, and the appreciation of the course content was very positive. However, we observed a substantial drop-out rate, mostly attributed to the lack of time of medical professionals. There is a high demand for educational offerings regarding AI in medical imaging among medical professionals, and better education may lead to a more realistic appreciation of clinical adoption. However, time constraints imposed by a busy clinical schedule need to be taken into account for successful education of medical professionals. [ABSTRACT FROM AUTHOR]

Simple Summary: Virtual monoenergetic images from dual-energy CT are incrementally used in routine clinical practice. Thus, radiomic analysis will be more often performed on these images in the future. This study characterized the test–retest repeatability and reproducibility of radiomic features from virtual monoenergetic images and their impact on machine-learning-based lesion classification. The results of this study provide a basis to improve radiomic analyses and identify the role of feature stability in classification tasks when using virtual monoenergetic imaging with different scan or reconstruction parameters in multicenter clinical studies. The purpose of this study was to (i) evaluate the test–retest repeatability and reproducibility of radiomic features in virtual monoenergetic images (VMI) from dual-energy CT (DECT) depending on VMI energy (40, 50, 75, 120, 190 keV), radiation dose (5 and 15 mGy), and DECT approach (dual-source and split-filter DECT) in a phantom (ex vivo), and (ii) to assess the impact of VMI energy and feature repeatability on machine-learning-based classification in vivo in 72 patients with 72 hypodense liver lesions. Feature repeatability and reproducibility were determined by concordance–correlation–coefficient (CCC) and dynamic range (DR) ≥0.9. Test–retest repeatability was high within the same VMI energies and scan conditions (percentage of repeatable features ranging from 74% for SFDE mode at 40 keV and 15 mGy to 86% for DSDE at 190 keV and 15 mGy), while reproducibility varied substantially across different VMI energies and DECTs (percentage of reproducible features ranging from 32.8% for SFDE at 5 mGy comparing 40 with 190 keV to 99.2% for DSDE at 15 mGy comparing 40 with 50 keV). No major differences were observed between the two radiation doses (<10%) in all pair-wise comparisons. In vivo, machine learning classification using penalized regression and random forests resulted in the best discrimination of hemangiomas and metastases at low-energy VMI (40 keV), and for cysts at high-energy VMI (120 keV). Feature selection based on feature repeatability did not improve classification performance. Our results demonstrate the high repeatability of radiomics features when keeping scan and reconstruction conditions constant. Reproducibility diminished when using different VMI energies or DECT approaches. The choice of optimal VMI energy improved lesion classification in vivo and should hence be adapted to the specific task. [ABSTRACT FROM AUTHOR]

Dregamine (1), a major monoterpene indole alkaloid isolated from Tabernaemontana elegans, was submitted to chemical transformation of the ketone function, yielding 19 azines (3–21) and 11 semicarbazones (22–32) bearing aliphatic or aromatic substituents. Their structures were assigned mainly by 1D and 2D NMR (COSY, HMQC, and HMBC) experiments. Compounds 3–32 were evaluated as multidrug resistance (MDR) reversers through functional and chemosensitivity assays in a human ABCB1-transfected mouse T-lymphoma cell model, overexpressing P-glycoprotein. A significant increase of P-gp inhibitory activity was observed for most derivatives, mainly those containing azine moieties with aromatic substituents. Compounds with trimethoxyphenyl (17) or naphthyl motifs (18, 19) were among the most active, exhibiting strong inhibition at 0.2 µM. Moreover, most of the derivatives showed selective antiproliferative effects toward resistant cells, having a collateral sensitivity effect. In drug combination assays, all compounds showed to interact synergistically with doxorubicin. Selected compounds (12, 17, 18, 20, and 29) were evaluated in the ATPase activity assay, in which all compounds but 12 behaved as inhibitors. To gather further insights on drug–receptor interactions, in silico studies were also addressed. A QSAR model allowed us to deduce that compounds bearing bulky and lipophilic substituents were stronger P-gp inhibitors. [ABSTRACT FROM AUTHOR]

Simple Summary: The combination of the albumin-bilirubin (ALBI) grading and the Prognostic Nutritional Index (PNI) offers potential as a highly predictive tool for patients with hepatocellular carcinoma (HCC). The present study evaluated this combination firstly for patients undergoing transarterial chemoembolization (TACE). Both the ALBI grade and PNI were strong independent predictors of survival. However, the combination of the two scores allowed for even more precise predictions. In addition, this new ALBI-PNI outperformed several established scoring systems. Thus, the easy-to-calculate ALBI-PNI may be a promising stratification tool for patients with HCC undergoing TACE in daily clinical routine. A combination of albumin-bilirubin (ALBI) grading and the Prognostic Nutritional Index (PNI) was identified recently as a highly predictive tool for patients with hepatocellular carcinoma (HCC) undergoing tumor ablation. The present study evaluated this combination in patients undergoing transarterial chemoembolization (TACE). Between 2010 and 2020, 280 treatment-naïve patients were retrospectively identified. The influence of ALBI grade, PNI and the novel ALBI-PNI on the median overall survival (OS) was assessed. In the next step, the prognostic ability of the combined approach was compared to established scoring systems. Both ALBI grade 2−3 and a low PNI were highly predictive for median OS (ALBI grade 1–3: 39.0 vs. 16.3 vs. 5.4 months, p < 0.001; high vs. low PNI: 21.4 vs. 7.5, p < 0.001). The combination of both resulted in a median OS of 39.0, 20.1, 10.3, and 5.4 months (p < 0.001). With a Concordance Index (C-Index) of 0.69, ALBI-PNI outperformed each individual score (ALBI 0.65, PNI 0.64) and was also better than BCLC, HAP, mHAP-II, and the Six-and-Twelve score (C-Indices 0.66, 0.60, 0.59, and 0.55). Thus, the easy-to-calculate ALBI-PNI may be a promising stratification tool for patients with HCC undergoing TACE, reflecting both immunonutritive status and liver function. [ABSTRACT FROM AUTHOR]

Plants have been used for centuries to treat several illnesses. The Plectranthus genus has a vast variety of species that has allowed the isolation of cytotoxic compounds with notable activities. The abietane diterpenes 6,7-dehydroroyleanone (DeRoy, 1), 7α-acetoxy-6β-hydroxyroyleanone (Roy, 2), and Parvifloron D (ParvD, 3) were obtained from Plectranthus spp. and showed promising biological activities, such as cytotoxicity. The inhibitory effects of the different natural abietanes (1-3) were compared in MFC7, SkBr3, and SUM159 cell lines, as well as SUM159 grown in cancer stem cell-inducing conditions. Based on the royleanones' bioactivity, the derivatives RoyBz (4), RoyBzCl (5), RoyPr2 (6), and DihydroxyRoy (7), previously obtained from 2, were selected for further studies. Protein kinases C (PKCs) are involved in several carcinogenic processes. Thus, PKCs are potential targets for cancer therapy. To date, the portfolio of available PKC modulators remains very limited due to the difficulty of designing isozyme-selective PKC modulators. As such, molecular docking was used to evaluate royleanones 1-6 as predicted isozyme-selective PKC binders. Subtle changes in the binding site of each PKC isoform change the predicted interaction profiles of the ligands. Subtle changes in royleanone substitution patterns, such as a double substitution only with non-substituted phenyls, or hydroxybenzoate at position four that flips the binding mode of ParvD (3), can increase the predicted interactions in certain PKC subtypes. [ABSTRACT FROM AUTHOR]

Registration of point clouds is a central problem in many mapping and monitoring applications, such as outdoor and indoor mapping, high-speed railway track inspection, heritage documentation, building information modeling, and others. However, ensuring the global consistency of the registration is still a challenging task when there are multiple point clouds because the different scans should be transformed into a common coordinate frame. The aim of this paper is the registration of multiple terrestrial laser scanner point clouds. We present a plane-based matching algorithm to find plane-to-plane correspondences using a new parametrization based on complex numbers. The multiplication of complex numbers is based on analysis of the quadrants to avoid the ambiguity in the calculation of the rotation angle formed between normal vectors of adjacent planes. As a matching step may contain several matrix operations, our strategy is applied to reduce the number of mathematical operations. We also design a novel method for global refinement of terrestrial laser scanner data based on plane-to-plane correspondences. The rotation parameters are globally refined using operations of quaternion multiplication, while the translation parameters are refined using the parameters of planes. The global refinement is done non-iteratively. The experimental results show that the proposed plane-based matching algorithm efficiently finds plane correspondences in partial overlapping scans providing approximate values for the global registration, and indicate that an accuracy better than 8 cm can be achieved by using our global fine plane-to-plane registration method. [ABSTRACT FROM AUTHOR]

Advances in micro-electro-mechanical navigation systems and lightweight LIDAR (light detection and ranging) sensors onboard unmanned aerial vehicles (UAVs) provide the feasibility of deriving point clouds with very high and homogeneous point density. However, the deformations caused by numerous sources of errors should be carefully treated. This work presents a rigorous calibration of UAV-based LiDAR systems with refinement of the boresight angles using a point-to-plane approach. Our method is divided into a calibration and a parameter mounting refinement part. It starts with the estimation of the calibration parameters and then refines the boresight angles. The novel contribution of the paper is two-fold. First, we estimate the calibration parameters conditioning the centroid of a plane segmented to lie on its corresponding segmented plane without an additional surveying campaign. Second, we refine the boresight angles using a new point-to-plane model. The proposed method is evaluated by analyzing the accuracy assessment of the adjusted point cloud to point/planar features before and after the proposed method. Compared with the state-of-the-art method, our proposed method achieves better positional accuracy. [ABSTRACT FROM AUTHOR]

This study aims to evaluate the prevalence, distribution and clinical profile of neurological diseases and syndromes from a neurology outpatient clinic in the city of Rio de Janeiro. This is a quantitative, cross-sectional study. 180 medical records of firsttime visits conducted through 18 months were analyzed. Age, gender and comorbidities were collected to identify the sample's profile and the neurological diagnoses found were classified in predefined groups of syndromes according to the ICD-10 classification, which were further stratified according to age and gender. 157 (87,2%) of the patients had a neurological disease, of which the mean age was 51,05 years and 67,5% were women. The most frequent comorbidities were: hypertension (55,6%); dyslipidemia (20,4%); and diabetes (14,6%). The most common neurological diseases were: Sequelae of Cerebrovascular Disease (12,7%); Unspecified Dementia (8,9%); and Migraine without Aura (7,6%). The main neurological syndromes were: Headache (24,8%); Dementia (15,9%); Cerebrovascular Disease (13,4%); Movement Disorders (12,1%); and Radiculopathy (10,8%). The age and gender profile of these syndromes was further described. These data contribute to better understand the distribution of neurological diseases in the neurological outpatient setting., Competing Interests: Conflict of interest: the authors declare no potential conflict of interest.

Understanding the supramolecular environment of crystal structures is necessary to facilitate designing molecules with desirable properties. A series of 12 novel 1,3,5- t ris (1-phenyl-1 H -pyrazol-5-yl)benzenes was used to assess the existence of planar stacking columns in supramolecular structures of pyrazoles. This class of molecules with different substituents may assist in understanding how small structural changes affect the supramolecular environment. The obtained compounds did not present the formation of planar stacking interactions between benzenes in solid or liquid states. This supposition was indicated by single crystal diffraction, Density Functional Theory (DFT) and quantum theory of atoms in molecules (QTAIM) calculations, and concentration-dependent liquid-state ¹H nuclear magnetic resonance (NMR). NMR showed that chemical shifts of benzene and pyrazole hydrogens confirm that planar stacking interactions are not formed in solution. The crystalline structures presented different molecular conformations. The molecular structures of 5 and 9b are in a twisted conformation, while compound 7 showed a conformation analogous to a calyx form., Competing Interests: The authors declare no conflict of interest.