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Unsupervised learning represents one of the most interesting challenges in computer vision today. The task has an immense practical value with many applications in artificial intelligence and emerging technologies, as large quantities of unlabeled images and videos can be collected at low cost. In this paper, we address the unsupervised learning problem in the context of segmenting the main foreground objects in single images. We propose an unsupervised learning system, which has two pathways, the teacher and the student, respectively. The system is designed to learn over several generations of teachers and students. At every generation the teacher performs unsupervised object discovery in videos or collections of images and an automatic selection module picks up good frame segmentations and passes them to the student pathway for training. At every generation multiple students are trained, with different deep network architectures to ensure a better diversity. The students at one iteration help in training a better selection module, forming together a more powerful teacher pathway at the next iteration. In experiments, we show that the improvement in the selection power, the training of multiple students and the increase in unlabeled data significantly improve segmentation accuracy from one generation to the next. Our method achieves top results on three current datasets for object discovery in video, unsupervised image segmentation and saliency detection. At test time, the proposed system is fast, being one to two orders of magnitude faster than published unsupervised methods. We also test the strength of our unsupervised features within a well known transfer learning setup and achieve competitive performance, proving that our unsupervised approach can be reliably used in a variety of computer vision tasks.

Heterozygous gain-of-kinase function variants in LRRK2 (leucine-rich repeat kinase 2) cause 1–2% of all cases of Parkinson’s disease (PD) albeit with incomplete and age-dependent penetrance. All pathogenic LRRK2 mutations reside within the two catalytic domains of LRRK2—either in its kinase domain (e.g. G2019S) with modest effect or its ROC-COR GTPase domain (e.g. R1441G/H) with large effect on LRRK2 kinase activity. We have previously reported assays to interrogate LRRK2 kinase pathway activity in human bio-samples measuring phosphorylation of its endogenous substrate Rab10, that mirrors LRRK2 kinase activation status. Here, we isolated neutrophils from fresh peripheral blood from 101 participants including 42 LRRK2 mutation carriers (21 with the G2019S and 21 with the R1441G mutations), 27 patients with idiopathic PD, and 32 controls. Using a dual approach, LRRK2 dependent Rab10 phosphorylation at Threonine 73 (pRab10Thr73) was measured by quantitative multiplexed immunoblotting for pRab10Thr73/total Rab10 as well as targeted mass-spectrometry for absolute pRab10Thr73 occupancy. We found a significant over fourfold increase in pRab10Thr73 phosphorylation in carriers of the LRRK2 R1441G mutation irrespective of clinical disease status. The effect of the LRRK2 G2019S mutation did not reach statistical significance. Furthermore, we show that LRRK2 phosphorylation at Serine 935 is not a marker for LRRK2 kinase activity in human neutrophils. When analysing pRab10Thr73 phosphorylation in post-mortem brain samples, we observed overall high variability irrespective of clinical and LRRK2 mutation status and attributed this mainly to the adverse effect of the peri- and post-mortem period on the stability of posttranslational modifications such as protein phosphorylation. Overall, in vivo LRRK2 dependent pRab10Thr73 phosphorylation in human peripheral blood neutrophils is a specific, robust and promising biomarker for significant LRRK2 kinase hyperactivation, as with the LRRK2 R1441G mutation. Additional readouts and/or assays may be needed to increase sensitivity to detect modest LRRK2 kinase activation, as with the LRRK2 G2019S mutation. Our assays could be useful for patient stratification and target engagement studies for LRRK2 kinase inhibitors.

Cognitive and visual impairment are common in Huntington’s Disease (HD) and may precede motor diagnosis. We investigate the early presence of visual cognitive deficits in 181 participants, including HD carriers (40 pre-manifest, 30 early manifest, 27 manifest, and 6 reduced penetrance) and 78 healthy controls (HC). Significant differences in visual memory were observed between reduced penetrance and pre-manifest groups ( p  = .003), with pre-manifest showing worse performance. Age, education, CAG repeats, motor status, executive function, and verbal fluency, accounted for up to 72.8% of the variance in general and visual cognitive functions, with motor status having the strongest impact on visual domains in HD carriers. In pre-manifest HD, visual cognitive domains were primarily influenced by executive function, verbal fluency, age, and CAG repeats, while in early and manifest stages motor status and verbal fluency becomes more influential. ROC analyses showed that especially visuospatial abilities, visual memory, and visual attention (AUC = 0.927, 0.878, 0.874, respectively) effectively differentiated HC and pre-manifest from early and manifest HD. Early assessment of visual cognitive domains, particularly visual memory, could be an early marker of cognitive decline in HD. Our findings highlight the different profiles of impairment in visual cognition across HD carriers.

Parkinson’s disease (PD) is a neurodegenerative disorder primarily characterized by motor symptoms, with emerging evidence suggesting retinal pathology, particularly in the ganglion cell-inner plexiform layer (GCIPL), detectable via optical coherence tomography (OCT). This study aimed to characterize early retinal dynamics in PD using OCT. We conducted a prospective one-year longitudinal multicenter study involving 53 early-stage PD patients with a disease duration of 5 years or less and 52 controls. The participants underwent retinal spectral-domain OCT, primary visual function and cognitive examinations. We examined baseline retinal measures and short-term longitudinal differences between groups via linear mixed effects models. In PD patients, the baseline GCIPL thickness in central regions was increased by up to 4 μm, and the rate of thinning in the parafoveal GCIPL was − 0.61 [0.29] µm/year faster over a one-year follow-up period than in controls in the 2- to 3-mm ring ( p  = 0.039). In PD patients, greater central GCIPL thickness was associated with poorer contrast sensitivity and reduced performance on the Farnsworth D15 color vision test. It also predicted subsequent thinning in both the GCIPL (2- to 3-mm ring) and the inner nuclear layer (2- to 5-mm rings). However, this increased thickness was not linked to prevalent or progressive motor or cognitive manifestations. In conclusion, this study provides the first detailed topographical description of early retinal dynamics in PD patients, revealing increased central GCIPL thickness and accelerated parafoveal GCIPL thinning in PD. However, the macular region shows complex and variable dynamics among PD patients, but these changes precede detectable progression in clinical scales.

Elevated urine bis(monoacylglycerol)phosphate (BMP) levels have been found in gain-of-kinase function LRRK2 G2019S mutation carriers. Here, we have expanded urine BMP analysis to other Parkinson’s disease (PD) associated mutations and found them to be consistently elevated in carriers of LRRK2 G2019S and R1441G/C as well as VPS35 D620N mutations. Urine BMP levels are promising biomarkers for patient stratification and potentially target engagement in clinical trials of emerging targeted PD therapies.

Parkinson´s disease (PD) is a common neurodegenerative movement disorder and leucine-rich repeat kinase 2 (LRRK2) is a promising therapeutic target for disease intervention. However, the ability to stratify patients who will benefit from such treatment modalities based on shared etiology is critical for the success of disease-modifying therapies. Ciliary and centrosomal alterations are commonly associated with pathogenic LRRK2 kinase activity and can be detected in many cell types. We previously found centrosomal deficits in immortalized lymphocytes from G2019S-LRRK2 PD patients. Here, to investigate whether such deficits may serve as a potential blood biomarker for PD which is susceptible to LRKK2 inhibitor treatment, we characterized patient-derived cells from distinct PD cohorts. We report centrosomal alterations in peripheral cells from a subset of early-stage idiopathic PD patients which is mitigated by LRRK2 kinase inhibition, supporting a role for aberrant LRRK2 activity in idiopathic PD. Centrosomal defects are detected in R1441G-LRRK2 and G2019S-LRRK2 PD patients and in non-manifesting LRRK2 mutation carriers, indicating that they accumulate prior to a clinical PD diagnosis. They are present in immortalized cells as well as in primary lymphocytes from peripheral blood. These findings indicate that analysis of centrosomal defects as a blood-based patient stratification biomarker may help nominate idiopathic PD patients who will benefit from LRRK2-related therapeutics.

BackgroundHD is an autosomal dominant, hereditary, and neurodegenerative disease that presents neurological, psychiatric, and cognitive impairment, with visual cognition being one of the affected areas.AimsThis study aims to analyze the visual cognition profile of asymptomatic and symptomatic carriers of Huntington’s disease (HD), compared with healthy controls (HC), and to evaluate the differences between asymptomatic and symptomatic patients with different years of progression of HD.MethodsWe evaluated 99 participants, 51 HD carriers [17 asymptomatic, 13 symptomatic ( < 5 years of evolution), 21 symptomatic ( > 5 years of evolution)] and 48 HC matched by sex and educational level. Motor function was rated with UHDRS scale, the general cognitive status was assessed with MoCA test, and a comprehensive battery of visual cognitive instruments was used. The following visual cognitive domains were assessed: visual memory, visuospatial skills and visuoconstructive abilities. One- way ANOVA and Tukey’s test for post hoc analysis were performed to analyze and compare the cognitive performance between the four groups.ResultsStatistically significant differences were found in the motor function (F(3.1)=14.129; p < .001) and in the general cognitive status (F(6.1)=9.63; p < .001) between groups. Specifically, we found significant differences in visual memory and visuospatial and visuoconstructive abilities between asymptomatic and both symptomatic subgroups of HD patients (p=.058), and also between the two groups of symptomatic patients with different years of evolution of HD (p=.014).ConclusionsFindings suggest that both symptomatic and asymptomatic HD patients present an increased visual cognitive impairment compared to HC. This impairment worsens with HD progression.

This paper aims to improve the efficiency and safety of autonomous agricultural vehicles (AAVs) in complex agricultural settings by integrating sensor technology and deep reinforcement learning techniques. The traditional fixed-route transport is expensive and prone to vehicle collisions. Advanced AAVs equipped with multiple sensors were employed for collecting and processing sensor data, were employed for collecting and processing sensor data. This algorithm can effectively identify moving AAVs, static obstacles and other relevant targets in agricultural environments. A deep reinforcement learning model was built by using Deep Q-Networks and neural networks and a simulation environment was created with the purpose of validating the path planning and obstacle avoidance capabilities of the proposed model.

Starting with ANAF's \"glory\" period, that is in the Ciolos Government, each year, the Ministry of Public Finance boasts that it has collected more taxes and charges than was foreseen: for example in 2017 in November, it has already cashed as foreseen for the budget year 2017 (7% over what was planned). These data are real, but with what price? ANAF has begun to verify the firms, and the present study examines macroeconomic data on the number of checks in the period 2014-2016, and for the same period we will also examine these data for Harghita County, where wages are almost the lowest in the whole country. Thus, it can be determined whether the macroeconomic trends are comparable to the Harghita County trends or not, and which will be the risk of being checked in Romania by ANAF - depending on where a company is registered.