[Eales' disease]. / La maladie de Eales.

The syndrome of recurrent vitreous hemorrhages in young men was described for the first time by Henry Eales in 1880. The association with a clinical manifestation of ocular inflammation was reported 5years later. Eales disease affects young adults who present with ischemic retinal vasculitis, with the peripheral retina most commonly affected. Most cases have been reported in South Asia. Although the etiology of this abnormality is unknown, it may be related to an immune sensitivity to Mycobacterium tuberculosis antigens. Its pathogenesis is related to extensive ischemia that affects the retina, secondary to an obliterative retinal vasculopathy with release of angiogenic factors of the VEGF type. Involvement of the retina is the hallmark of the disease, which manifests as follows: periphlebitis, retinal capillary ischemia most often affecting the periphery with secondary proliferative retinopathy and retinal and/or papillary neovascularization, recurrent vitreous hemorrhages and tractional retinal detachment. These complications are potentially blinding. The natural history of Eales disease varies, with temporary or permanent remission in some cases and continuous progression in others. Progression is often bilateral, which necessitates regular follow-up. The treatment of Eales disease depends on the stage of the disease and is not well defined. Observation only, pars plana vitrectomy surgery and/or intravitreal injections of anti-VEGF are recommended in cases of vitreous hemorrhage, associated with corticosteroids when retinal vasculitis is present. Laser pan-retinal photocoagulation is necessary when neovascularization is present.

Adaptive eigenvalue decomposition algorithm for passive acoustic source localization

To find the position of an acoustic source in a room, the relative delay between two (or more) microphone signals for the direct sound must be determined. The generalized cross-correlation method is the most popular technique to do so and is well explained in a landmark paper by Knapp and Carter. In this paper, a new approach is proposed that is based on eigenvalue decomposition. Indeed, the eigenvector corresponding to the minimum eigenvalue of the covariance matrix of the microphone signals contains the impulse responses between the source and the microphone signals (and therefore all the information we need for time delay estimation). In experiments, the proposed algorithm performs well and is very accurate.