Laying the Foundation for a Solar America: The Million Solar Roofs Initiative

As the U.S. Department of Energy's Solar Energy Technology Program embarks on the next phase of its technology acceptance efforts under the Solar America Initiative, there is merit to examining the program's previous market transformation effort, the Million Solar Roofs Initiative. Its goal was to transform markets for distributed solar technologies by facilitating the installation of solar systems

Mutant p53 sustains serine-glycine synthesis and essential amino acids intake promoting breast cancer growth

: Reprogramming of amino acid metabolism, sustained by oncogenic signaling, is crucial for cancer cell survival under nutrient limitation. Here we discovered that missense mutant p53 oncoproteins stimulate de novo serine/glycine synthesis and essential amino acids intake, promoting breast cancer growth. Mechanistically, mutant p53, unlike the wild-type counterpart, induces the expression of serine-synthesis-pathway enzymes and L-type amino acid transporter 1 (LAT1)/CD98 heavy chain heterodimer. This effect is exacerbated by amino acid shortage, representing a mutant p53-dependent metabolic adaptive response. When cells suffer amino acids scarcity, mutant p53 protein is stabilized and induces metabolic alterations and an amino acid transcriptional program that sustain cancer cell proliferation. In patient-derived tumor organoids, pharmacological targeting of either serine-synthesis-pathway and LAT1-mediated transport synergizes with amino acid shortage in blunting mutant p53-dependent growth. These findings reveal vulnerabilities potentially exploitable for tackling breast tumors bearing missense TP53 mutations

Steganalysis of 3D objects using statistics of local feature sets

3D steganalysis aims to identify subtle invisible changes produced in graphical objects through digital watermarking or steganography. Sets of statistical representations of 3D features, extracted from both cover and stego 3D mesh objects, are used as inputs into machine learning classifiers in order to decide whether any information was hidden in the given graphical object. The features proposed in this paper include those representing the local object curvature, vertex normals, the local geometry representation in the spherical coordinate system. The effectiveness of these features is tested in various combinations with other features used for 3D steganalysis. The relevance of each feature for 3D steganalysis is assessed using the Pearson correlation coefficient. Six different 3D watermarking and steganographic methods are used for creating the stego-objects used in the evaluation study

Model-free Consensus Maximization for Non-Rigid Shapes

Many computer vision methods use consensus maximization to relate measurements containing outliers with the correct transformation model. In the context of rigid shapes, this is typically done using Random Sampling and Consensus (RANSAC) by estimating an analytical model that agrees with the largest number of measurements (inliers). However, small parameter models may not be always available. In this paper, we formulate the model-free consensus maximization as an Integer Program in a graph using `rules' on measurements. We then provide a method to solve it optimally using the Branch and Bound (BnB) paradigm. We focus its application on non-rigid shapes, where we apply the method to remove outlier 3D correspondences and achieve performance superior to the state of the art. Our method works with outlier ratio as high as 80\%. We further derive a similar formulation for 3D template to image matching, achieving similar or better performance compared to the state of the art.Comment: ECCV1

The Italian Consensus Conference on FAI Syndrome in Athletes (Cotignola Agreement)

Background. Femoro-acetabular impingement (FAI) is an important topic in literature because of its strong relationship with sport populations. Methods. Sixty-five experts participated in "this Consensus Conference (CC)". They discussed, voted and approved a consensus document on the FAI syndrome in athletes. Results. The CC experts approved document provided suggestions concerning: 1) Epidemiology of FAI; 2) Clinical evaluation; 3) Radiological evaluation; 4) Conserva-tive treatment; 5) Surgical criteria; 6) Surgical techniques; 7) Post-surgical rehabilita-tion; 8) Outcome evaluation; 9) FAI-associated clinical frameworks. Conclusions. The CC offers a multidisciplinary approach to the diagnosis and treat-ment of FAI syndrome in athletes taking into account all the different steps needed to approach this pathology in sport populations

Visual recovery after perinatal stroke evidenced by functional and diffusion MRI: case report

BACKGROUND: After perinatal brain injury, clinico-anatomic correlations of functional deficits and brain plasticity remain difficult to evaluate clinically in the young infant. Thus, new non-invasive methods capable of early functional diagnosis are needed in young infants. CASE PRESENTATION: The visual system recovery in an infant with perinatal stroke is assessed by combining diffusion tensor imaging (DTI) and event-related functional MRI (ER-fMRI). All experiments were done at 1.5T. A first DTI experiment was performed at 12 months of age. At 20 months of age, a second DTI experiment was performed and combined with an ER-fMRI experiment with visual stimuli (2 Hz visual flash). At 20 months of age, ER-fMRI showed significant negative activation in the visual cortex of the injured left hemisphere that was not previously observed in the same infant. DTI maps suggest recovery of the optic radiation in the vicinity of the lesion. Optic radiations in the injured hemisphere are more prominent in DTI at 20 months of age than in DTI at 12 months of age. CONCLUSION: Our data indicate that functional cortical recovery is supported by structural modifications that concern major pathways of the visual system. These neuroimaging findings might contribute to elaborate a pertinent strategy in terms of diagnosis and rehabilitation

A Scale Independent Selection Process for 3D Object Recognition in Cluttered Scenes

During the last years a wide range of algorithms and devices have been made available to easily acquire range images. The increasing abundance of depth data boosts the need for reliable and unsupervised analysis techniques, spanning from part registration to automated segmentation. In this context, we focus on the recognition of known objects in cluttered and incomplete 3D scans. Locating and fitting a model to a scene are very important tasks in many scenarios such as industrial inspection, scene understanding, medical imaging and even gaming. For this reason, these problems have been addressed extensively in the literature. Several of the proposed methods adopt local descriptor-based approaches, while a number of hurdles still hinder the use of global techniques. In this paper we offer a different perspective on the topic: We adopt an evolutionary selection algorithm that seeks global agreement among surface points, while operating at a local level. The approach effectively extends the scope of local descriptors by actively selecting correspondences that satisfy global consistency constraints, allowing us to attack a more challenging scenario where model and scene have different, unknown scales. This leads to a novel and very effective pipeline for 3D object recognition, which is validated with an extensive set of experiment

Evidence of a landlocked reproducing population of the marine pejerrey Odontesthes argentinensis (Actinopterygii; Atherinopsidae)

In South America, the order Atheriniformes includes the monophyletic genus<em>Odontesthes</em> with 20 species that inhabit freshwater, estuarine and coastal environments. Pejerrey Odontesthes argentinensis is widely distributed in coastal and estuarineareas of the Atlantic Ocean and is known to foray into estuaries of river systems, particularly in conditions of elevated salinity. However, to our knowledge, a landlockedself-sustaining population has never been recorded. In this study, we examined the pejerrey population of Salada de Pedro Luro Lake (south-east of BuenosAires Province, Argentina) to clarify its taxonomic identity. An integrative taxonomic analysis based on traditional meristic, landmark-based morphometrics and genetictechniques suggests that the Salada de Pedro Luro pejerrey population represents a novel case of physiological and morphological adaptation of a marine pejerrey speciesto a landlocked environment and emphasises the environmental plasticity of this group of fishe

A case-control study to identify risk factors associated with avian influenza subtype H9N2 on commercial poultry farms in Pakistan

A 1:1 matched case-control study was conducted to identify risk factors for avian influenza subtype H9N2 infection on commercial poultry farms in 16 districts of Punjab, and 1 administrative unit of Pakistan. One hundred and thirty-three laboratory confirmed positive case farms were matched on the date of sample submission with 133 negative control farms. The association between a series of farm-level characteristics and the presence or absence of H9N2 was assessed by univariable analysis. Characteristics associated with H9N2 risk that passed the initial screening were included in a multivariable conditional logistic regression model. Manual and automated approaches were used, which produced similar models. Key risk factors from all approaches included selling of eggs/birds directly to live bird retail stalls, being near case/infected farms, a previous history of infectious bursal disease (IBD) on the farm and having cover on the water storage tanks. The findings of current study are in line with results of many other studies conducted in various countries to identify similar risk factors for AI subtype H9N2 infection. Enhancing protective measures and controlling risks identified in this study could reduce spread of AI subtype H9N2 and other AI viruses between poultry farms in Pakistan