Tool wear monitoring in milling using aZIBO shape descriptor

En este documento, se lleva a cabo un proceso de monitoreo del desgaste de la herramienta para determinar la condición de desgaste y para asegurar el uso óptimo de las herramientas antes de su reemplazo durante las operaciones de mecanizado de metales. El conjunto de datos se compone de 53 inserciones de corte. Todos ellos fueron preprocesados y el desgaste de los bordes fue segmentado, resultando 212 bordes establecidos. Para describir la forma de desgaste, se usó un descriptor de forma aZIBO y sus resultados se compararon con dos descriptores clásicos, Hu y Flusser. La clasificación se llevó a cabo utilizando kNN con 1, 3, 5, 7, 9 y 11 vecinos y seis distancias: Cosine, Euclidean, IntersetcDist, ChiSquare, SqDist y Cityblock. Se han llevado a cabo dos clasificaciones: una de ellas con tres clases diferentes (baja, media y alta wexar -L, M y H, respectivamente) y la otra con solo dos clases: baja (L) y alta (H). El descriptor aZIBO ofrece mejores resultados que los clásicos, con una tasa de aciertos del 60,84% y un 81,13% utilizando las etiquetas L-M-H y L-H, respectivamente

Locality-Sensitive Hashing for large scale image retrieval

En este artículo proporcionamos una descripción general del hash sensible a la ubicación (LSH) utilizado para la recuperación de imágenes a gran escala y para resolver el problema del vecino más cercano. El objetivo es experimentar con diferentes configuraciones de parámetros de LSH sobre un conjunto de huellas dactilares de video para ver cuál es la mejor en términos de precisión e indexación para que luego, dado un objeto de consulta, devuelva los objetos (vecinos más cercanos) que sean más similares a la consulta. Los parámetros de configuración que ofrecieron mejores resultados fueron un tamaño de cubo de 24 con 15 tablas y tamaños de hash de 15 bits, obteniendo aproximadamente el 50% de las coincidencias correctas con los métodos de recuperación P @ 4 y P @ 6

Staging Parkinson’s Disease According to the MNCD (Motor/Non-motor/Cognition/Dependency) Classification Correlates with Disease Severity and Quality of Life

Background: Recently, a novel simple classification called MNCD, based on 4 axes (Motor; Non-motor; Cognition; Dependency) and 5 stages, has been proposed to classify Parkinson's disease (PD). Objective: Our aim was to apply the MNCD classification in a cohort of PD patients for the first time and also to analyze the correlation with quality of life (QoL) and disease severity. Methods: Data from the baseline visit of PD patients recruited from 35 centers in Spain from the COPPADIS cohort from January 2016 to November 2017 were used to apply the MNCD classification. Three instruments were used to assess QoL: 1) the 39-item Parkinson's disease Questionnaire [PDQ-39]); PQ-10; the EUROHIS-QOL 8-item index (EUROHIS-QOL8). Results: Four hundred and thirty-nine PD patients (62.05 +/- 7.84 years old; 59% males) were included. MNCD stage was: stage 1, 8.4% (N = 37); stage 2, 62% (N = 272); stage 3, 28.2% (N = 124); stage 4-5, 1.4% (N = 6). A more advanced MNCD stage was associated with a higher score on the PDQ39SI (p < 0.0001) and a lower score on the PQ-10 (p < 0.0001) and EUROHIS-QOL8 (p < 0.0001). In many other aspects of the disease, such as disease duration, levodopa equivalent daily dose, motor symptoms, non-motor symptoms, and autonomy for activities of daily living, an association between the stage and severity was observed, with data indicating a progressive worsening related to disease progression throughout the proposed stages. Conclusion: Staging PD according to the MNCD classification correlated with QoL and disease severity. The MNCD could be a proper tool to monitor the progression of PD

Predictors of Loss of Functional Independence in Parkinson’s Disease: Results from the COPPADIS Cohort at 2-Year Follow-Up and Comparison with a Control Group

COPPADIS Study Group.[Background and objective] The aim of this study was to compare the progression of independence in activities of daily living (ADL) in Parkinson’s disease (PD) patients versus a control group, as well as to identify predictors of disability progression and functional dependency (FD).[Patients and Methods] PD patients and control subjects, who were recruited from 35 centers of Spain from the COPPADIS cohort between January 2016 and November 2017 (V0), were included. Patients and subjects were then evaluated again at the 2-year follow-up (V2). Disability was assessed with the Schwab & England Activities of Daily Living Scale (S&E-ADLS) at V0 and V2. FD was defined as an S&E-ADLS score less than 80%.[Results] In the PD group, a significant decrease in the S&E-ADLS score from V0 to V2 (N = 507; from 88.58 ± 10.19 to 84.26 ± 13.38; p < 0.0001; Cohen’s effect size = −0.519) was observed but not in controls (N = 124; from 98.87 ± 6.52 to 99.52 ± 2.15; p = 0.238). When only patients considered functional independent at baseline were included, 55 out of 463 (11.9%) converted to functional dependent at V2. To be a female (OR = 2.908; p = 0.009), have longer disease duration (OR = 1.152; p = 0.002), have a non-tremoric motor phenotype at baseline (OR = 3.574; p = 0.004), have a higher score at baseline in FOGQ (OR = 1.244; p < 0.0001) and BDI-II (OR = 1.080; p = 0.008), have a lower score at baseline in PD-CRS (OR = 0.963; p = 0.008), and have a greater increase in the score from V0 to V2 in UPDRS-IV (OR = 1.168; p = 0.0.29), FOGQ (OR = 1.348; p < 0.0001) and VAFS-Mental (OR = 1.177; p = 0.013) (adjusted R-squared 0.52; Hosmer and Lemeshow test = 0.94) were all found to be independent predictors of FD at V2.[Conclusions] In conclusion, autonomy for ADL worsens in PD patients compared to controls. Cognitive impairment, gait problems, fatigue, depressive symptoms, more advanced disease, and a non-tremor phenotype are independent predictors of FD in the short-term.Fundación Curemos el Parkinson (www.curemoselparkinson.org).Peer reviewe

Staging Parkinson’s Disease Combining Motor and Nonmotor Symptoms Correlates with Disability and Quality of Life

COPPADIS Study Group.[Introduction] In a degenerative disorder such as Parkinson’s disease (PD), it is important to establish clinical stages that allow to know the course of the disease. Our aim was to analyze whether a scale combining Hoehn and Yahr’s motor stage (H&Y) and the nonmotor symptoms burden (NMSB) (assessed by the nonmotor symptoms scale (NMSS)) provides information about the disability and the patient’s quality of life (QoL) with regard to a defined clinical stage.[Materials and Methods] Cross-sectional study in which 603 PD patients from the COPPADIS cohort were classified according to H&Y (1, stage I; 2, stage II; 3, stage III; 4, stage IV/V) and NMSB (A: NMSS = 0–20; B: NMSS = 21–40; C: NMSS = 41–70; D: NMSS ≥ 71) in 16 stages (HY.NMSB, from 1A to 4D). QoL was assessed with the PDQ-39SI, PQ-10, and EUROHIS-QOL8 and disability with the Schwab&England ADL (Activities of Daily Living) scale.[Results] A worse QoL and greater disability were observed at a higher stage of H&Y and NMSB (). Combining both (HY.NMSB), patients in stages 1C and 1D and 2C and 2D had significantly worse QoL and/or less autonomy for ADL than those in stages 2A and 2B and 3A and 3B, respectively (; e.g., PDQ-39SI in 1D [n = 15] vs 2A [n = 101]: 28.6 ± 17.1 vs 7.9 ± 5.8; ).[Conclusion] The HY.NMSB scale is simple and reflects the degree of patient involvement more accurately than the H&Y. Patients with a lower H&Y stage may be more affected if they have a greater NMS burden.Peer reviewe

Predictors of Global Non-Motor Symptoms Burden Progression in Parkinson’s Disease. Results from the COPPADIS Cohort at 2-Year Follow-Up

COPPADIS Study Group.[Background and Objective] Non-motor symptoms (NMS) progress in different ways between Parkinson’s disease (PD) patients. The aim of the present study was to (1) analyze the change in global NMS burden in a PD cohort after a 2-year follow-up, (2) to compare the changes with a control group, and (3) to identify predictors of global NMS burden progression in the PD group.[Material and Methods] PD patients and controls, recruited from 35 centers of Spain from the COPPADIS cohort from January 2016 to November 2017, were followed-up with after 2 years. The Non-Motor Symptoms Scale (NMSS) was administered at baseline (V0) and at 24 months ± 1 month (V2). Linear regression models were used for determining predictive factors of global NMS burden progression (NMSS total score change from V0 to V2 as dependent variable).[Results] After the 2-year follow-up, the mean NMS burden (NMSS total score) significantly increased in PD patients by 18.8% (from 45.08 ± 37.62 to 53.55 ± 42.28; p < 0.0001; N = 501; 60.2% males, mean age 62.59 ± 8.91) compared to no change observed in controls (from 14.74 ± 18.72 to 14.65 ± 21.82; p = 0.428; N = 122; 49.5% males, mean age 60.99 ± 8.32) (p < 0.0001). NMSS total score at baseline (β = −0.52), change from V0 to V2 in PDSS (Parkinson’s Disease Sleep Scale) (β = −0.34), and change from V0 to V2 in NPI (Neuropsychiatric Inventory) (β = 0.25) provided the highest contributions to the model (adjusted R-squared 0.41; Durbin-Watson test = 1.865).[Conclusions] Global NMS burden demonstrates short-term progression in PD patients but not in controls and identifies worsening sleep problems and neuropsychiatric symptoms as significant independent predictors of this NMS progression.This research was funded by Fundación Española de Ayuda a la Investigación en Parkinson y otras Enfermedades Neuro-degenerativas (Curemos el Parkinson; www.curemoselparkinson.org).Peer reviewe

Predictors of clinically significant quality of life impairment in Parkinson’s disease

COPPADIS Study Group.Quality of life (QOL) plays an important role in independent living in Parkinson’s disease (PD) patients, being crucial to know what factors impact QoL throughout the course of the disease. Here we identified predictors of QoL impairment in PD patients from a Spanish cohort. PD patients recruited from 35 centers of Spain from the COPPADIS cohort from January 2016, to November 2017, were followed up during 2 years. Health-related QoL (HRQoL) and global QoL (GQoL) were assessed with the 39-item Parkinson’s disease Questionnaire (PDQ-39) and the EUROHIS-QOL 8-item index (EUROHIS-QOL8), respectively, at baseline (V0) and at 24 months ± 1 month (V2). Clinically significant QoL impairment was defined as presenting an increase (PDQ-39SI) or decrement (EUROHIS-QOL8) at V2 ≥ 10% of the score at baseline (V0). A comparison with a control group was conducted for GQoL. GQoL did not change significantly in PD patients (N = 507; p = 0.686) or in the control group (N = 119; p = 0.192). The mean PDQ-39SI was significantly increased in PD patients (62.7 ± 8.5 years old; 58.8% males; N = 500) by 21.6% (from 16.7 ± 13 to 20.3 ± 16.4; p < 0.0001) at V2. Ninety-three patients (18.6%) presented a clinically significant HRQoL impairment at V2. To be younger (OR = 0.896; 95% CI 0.829–0.968; p = 0.006), to be a female (OR = 4.181; 95% CI 1.422–12.290; p = 0.009), and to have a greater increase in BDI-II (Beck Depression Inventory-II) (OR = 1.139; 95% CI 1.053–1.231; p = 0.001) and NMSS (Non-Motor Symptoms Scale) (OR = 1.052; 95% CI 1.027–1.113; p < 0.0001) total scores from V0 to V2 were associated with clinically significant HRQoL impairment at the 2-year follow-up (Hosmer–Lemeshow test, p = 0.665; R 2 = 0.655). An increase in ≥5 and ≥10 points of BDI-II and NMSS total score at V2 multiplied the probability of presenting clinically significant HRQoL impairment by 5 (OR = 5.453; 95% CI 1.663–17.876; p = 0.005) and 8 (OR = 8.217; 95% CI, 2.975–22.696; p = 0.002), respectively. In conclusion, age, gender, mood, and non-motor impairment were associated with clinically significant HRQoL impairment after the 2-year follow-up in PD patients.Mir P. has received honoraria from AbbVie, Abbott, Allergan, Bial, Merz, UCB and Zambon and have received grants from the Spanish Ministry of Economy and Competitiveness [PI16/01575] co-founded by ISCIII (Subdirección General de Evaluación y Fomento de la Investigación) and by Fondo Europeo de Desarrollo Regional (FEDER), the Consejería de Economía, Innovación, Ciencia y Empleo de la Junta de Andalucía [CVI-02526, CTS-7685], the Consejería de Salud y Bienestar Social de la Junta de Andalucía [PI-0437-2012, PI-0471-2013], the Sociedad Andaluza de Neurología, the Jacques and Gloria Gossweiler Foundation, the Fundación Alicia Koplowitz, the Fundación Mutua Madrileña.Peer reviewe

Falls Predict Acute Hospitalization in Parkinson's Disease

[Background] There is a need for identifying risk factors for hospitalization in Parkinson’s disease (PD) and also interventions to reduce acute hospital admission.[Objective] To analyze the frequency, causes, and predictors of acute hospitalization (AH) in PD patients from a Spanish cohort.[Methods] PD patients recruited from 35 centers of Spain from the COPPADIS-2015 (COhort of Patients with PArkinson’s DIsease in Spain, 2015) cohort from January 2016 to November 2017, were included in the study. In order to identify predictors of AH, Kaplan-Meier estimates of factors considered as potential predictors were obtained and Cox regression performed on time to hospital encounter 1-year after the baseline visit.[Results] Thirty-five out of 605 (5.8%) PD patients (62.5±8.9 years old; 59.8% males) presented an AH during the 1-year follow-up after the baseline visit. Traumatic falls represented the most frequent cause of admission, being 23.7% of all acute hospitalizations. To suffer from motor fluctuations (HR [hazard ratio] 2.461; 95% CI, 1.065–5.678; p = 0.035), a very severe non-motor symptoms burden (HR [hazard ratio] 2.828; 95% CI, 1.319–6.063; p = 0.008), falls (HR 3.966; 95% CI 1.757–8.470; p = 0.001), and dysphagia (HR 2.356; 95% CI 1.124–4.941; p = 0.023) was associated with AH after adjustment to age, gender, disease duration, levodopa equivalent daily dose, total number of non-antiparkinsonian drugs, and UPDRS-IIIOFF. Of the previous variables, only falls (HR 2.998; 95% CI 1.080–8.322; p = 0.035) was an independent predictor of AH.[Conclusion] Falls is an independent predictor of AH in PD patients.Peer reviewe

Tool wear monitoring in milling using aZIBO shape descriptor

Abstract In this paper, a tool wear monitoring process is carried out in order to determine the insert wear condition and to ensure the optimal usage of tools before their replacement during metal machining operations. The dataset is composed of 53 cutting inserts. All of them were pre-processed and their edge wear was segmented resulting in 212 edges set. To describe the wear shape, aZIBO shape descriptor was used and its results were compared with two classical descriptors, Hu and Flusser. The classification was carried out using kNN with 1, 3, 5, 7, 9 and 11 neighbours and six distances: Cosine, Euclidean, IntersetcDist, ChiSquare, SqDist and Cityblock. Two classifications have been carried out: One of them using three different classes (Low, Medium and High wexar -L, M and H, respectively-) and the other one with only two classes: Low (L) and High (H). aZIBO descriptor offers better results than the classical ones obtaining hit rates of 60.84% and and 81.13% using the L-M-H and the L-H labellings, respectively