A modified Schwinger's formula for the Casimir effect

After briefly reviewing how the (proper-time) Schwinger's formula works for computing the Casimir energy in the case of "scalar electrodynamics" where the boundary conditions are dictated by two perfectly conducting parallel plates with separation "a" in the Z-axis, we propose a slightly modification in the previous approach based on an analytical continuation method. As we will see, for the case at hand our formula does not need the use of Poisson summation to get a (renormalized) finite result.Comment: 6 pages, DFTUZ/93/14 (a short version will appear in the Letters in Math. Phys.

Schwinger's Method for the Massive Casimir Effect

We apply to the massive scalar field a method recently proposed by Schwinger to calculate the Casimir effect. The method is applied with two different regularization schemes: the Schwinger original one by means of Poisson formula and another one by means of analytical continuation.Comment: plain TeX, 6 pages, DFTUZ-93-2

Frequency of sleep bruxism behaviors in healthy young adults over a four-night recording span in the home environment

Objectives: This study aimed to assess frequency and multiple-night variability of sleep bruxism (SB) as well as sleep-time masticatory muscle activities (sMMA) in the home environment in healthy young adults using a portable device that provides electrocardiographic (ECG) and surface electromyographic (EMG) recordings from the masticatory muscles. Methods: The study was performed on 27 subjects (11 males, 16 females; mean age 28.3 ± 1.7 years) selected from a sample of healthy young students. Evaluation was carried out for four nights to record data on masticatory muscle activities using a compact portable device that previously showed an excellent agreement with polysomnography (PSG) for the detection of SB events. The number of SB episodes per sleep hour (bruxism index), and the number of tonic, phasic and mixed sMMA events per hour were assessed. A descriptive evaluation of the frequency of each condition was performed on all individuals, and gender comparison was investigated. Results: Mean sleep duration over the four recording nights was 7 ± 1.3 h. The average SB index was 3.6 ± 1.2. Most of the sMMA were tonic (49.9%) and phasic (44.1%). An ANOVA test showed the absence of significant differences between the four nights. No significant gender differences were detected for the SB index, phasic or tonic contractions; conversely, gender differences were detected for mixed sMMA events (p < 0.05). Conclusion: This investigation supports the concept that sMMA events are quite frequent in healthy adults. Differences over the four-night recording span were not significant. These data could be compared to subjects with underlying conditions that may lead to an additive bruxism activity and possible clinical consequences

Social learning and amygdala disruptions in Nf1 mice are rescued by blocking p21-activated kinase

Children with Neurofibromatosis type 1 (NF1) are increasingly recognized to have high prevalence of social difficulties and autism spectrum disorders (ASD). We demonstrated selective social learning deficit in mice with deletion of a single Nf1 gene (Nf1+/−), along with greater activation of mitogen activated protein kinase pathway in neurons from amygdala and frontal cortex, structures relevant to social behaviors. The Nf1+/− mice showed aberrant amygdala glutamate/GABA neurotransmissiondeficits in long-term potentiationand specific disruptions in expression of two proteins associated with glutamate and GABA neurotransmission: a disintegrin and metalloprotease domain 22 (ADAM22) and heat shock protein 70 (HSP70), respectively. All of these amygdala disruptions were normalized by co-deletion of p21 protein-activated kinase (Pak1) gene. We also rescued the social behavior deficits in Nf1+/− mice with pharmacological blockade of Pak1 directly in the amygdala. These findings provide novel insights and therapeutic targets for NF1 and ASD patients

Pilot Study of a New Mandibular Advancement Device

This study was conducted to determine the efficacy of a customized mandibular advancement device (MAD) in the treatment of obstructive sleep apnea (OSA). Eight patients (M = 3; F = 5; mean age = 56.3 ± 9.4) with a diagnosis of OSA confirmed by polysomnography (PSG) were re-cruited on the basis of the following inclusion criteria: apnea-hypopnea index (AHI) > 5, age between 18 and 75 years, body mass index (BMI) < 25, and PSG data available at baseline (T0). All were treated with the new NOA® MAD by OrthoApnea (NOA® ) for at least 3 months; PSG with NOA in situ was performed after 3 months of treatment (T1). The following parameters were calculated at T0 and T1: AHI, supine AHI, oxygen desaturation index (ODI), percentage of recording time spent with oxygen saturation <90% (SpO2 < 90%), and mean oxygen desaturation (MeanSpO2%). Data were submitted for statistical analysis. The baseline values were AHI = 21.33 ± 14.79, supine AHI = 35.64 ± 12.80, ODI = 17.51 ± 13.5, SpO2 < 90% = 7.82 ± 17.08, and MeanSpO2% = 93.45 ± 1.86. Four patients had mild OSA (5 > AHI < 15), one moderate OSA (15 > AHI < 30), and three severe OSA (AHI > 30). After treatment with NOA®, statistically significant improvements in AHI (8.6 ± 4.21) and supine AHI (11.21 ± 7.26) were recorded. OrthoApnea NOA® could be an effective alternative in the treatment of OSA: the device improved the PSG parameters assessed

Neuroprotective peptide ADNF-9 in fetal brain of C57BL/6 mice exposed prenatally to alcohol

<p>Abstract</p> <p>Background</p> <p>A derived peptide from activity-dependent neurotrophic factor (ADNF-9) has been shown to be neuroprotective in the fetal alcohol exposure model. We investigated the neuroprotective effects of ADNF-9 against alcohol-induced apoptosis using TUNEL staining. We further characterize in this study the proteomic architecture underlying the role of ADNF-9 against ethanol teratogenesis during early fetal brain development using liquid chromatography in conjunction with tandem mass spectrometry (LC-MS/MS).</p> <p>Methods</p> <p>Pregnant C57BL/6 mice were exposed from embryonic days 7-13 (E7-E13) to a 25% ethanol-derived calorie [25% EDC, Alcohol (ALC)] diet, a 25% EDC diet simultaneously administered i.p. ADNF-9 (ALC/ADNF-9), or a pair-fed (PF) liquid diet. At E13, fetal brains were collected from 5 dams from each group, weighed, and frozen for LC-MS/MS procedure. Other fetal brains were fixed for TUNEL staining.</p> <p>Results</p> <p>Administration of ADNF-9 prevented alcohol-induced reduction in fetal brain weight and alcohol-induced increases in cell death. Moreover, individual fetal brains were analyzed by LC-MS/MS. Statistical differences in the amounts of proteins between the ALC and ALC/ADNF-9 groups resulted in a distinct data-clustering. Significant upregulation of several important proteins involved in brain development were found in the ALC/ADNF-9 group as compared to the ALC group.</p> <p>Conclusion</p> <p>These findings provide information on potential mechanisms underlying the neuroprotective effects of ADNF-9 in the fetal alcohol exposure model.</p

Normalization Perturbation: A Simple Domain Generalization Method for Real-World Domain Shifts

Improving model's generalizability against domain shifts is crucial,especially for safety-critical applications such as autonomous driving.Real-world domain styles can vary substantially due to environment changes andsensor noises, but deep models only know the training domain style. Such domainstyle gap impedes model generalization on diverse real-world domains. Ourproposed Normalization Perturbation (NP) can effectively overcome this domainstyle overfitting problem. We observe that this problem is mainly caused by thebiased distribution of low-level features learned in shallow CNN layers. Thus,we propose to perturb the channel statistics of source domain features tosynthesize various latent styles, so that the trained deep model can perceivediverse potential domains and generalizes well even without observations oftarget domain data in training. We further explore the style-sensitive channelsfor effective style synthesis. Normalization Perturbation only relies on asingle source domain and is surprisingly effective and extremely easy toimplement. Extensive experiments verify the effectiveness of our method forgeneralizing models under real-world domain shifts.<br

UniDepthV2: Universal Monocular Metric Depth Estimation Made Simpler

Accurate monocular metric depth estimation (MMDE) is crucial to solvingdownstream tasks in 3D perception and modeling. However, the remarkableaccuracy of recent MMDE methods is confined to their training domains. Thesemethods fail to generalize to unseen domains even in the presence of moderatedomain gaps, which hinders their practical applicability. We propose a newmodel, UniDepthV2, capable of reconstructing metric 3D scenes from solelysingle images across domains. Departing from the existing MMDE paradigm,UniDepthV2 directly predicts metric 3D points from the input image at inferencetime without any additional information, striving for a universal and flexibleMMDE solution. In particular, UniDepthV2 implements a self-promptable cameramodule predicting a dense camera representation to condition depth features.Our model exploits a pseudo-spherical output representation, which disentanglesthe camera and depth representations. In addition, we propose a geometricinvariance loss that promotes the invariance of camera-prompted depth features.UniDepthV2 improves its predecessor UniDepth model via a new edge-guided losswhich enhances the localization and sharpness of edges in the metric depthoutputs, a revisited, simplified and more efficient architectural design, andan additional uncertainty-level output which enables downstream tasks requiringconfidence. Thorough evaluations on ten depth datasets in a zero-shot regimeconsistently demonstrate the superior performance and generalization ofUniDepthV2. Code and models are available athttps://github.com/lpiccinelli-eth/UniDepth<br

Uni{K}3{D}: {U}niversal Camera Monocular 3{D} Estimation

Monocular 3D estimation is crucial for visual perception. However, currentmethods fall short by relying on oversimplified assumptions, such as pinholecamera models or rectified images. These limitations severely restrict theirgeneral applicability, causing poor performance in real-world scenarios withfisheye or panoramic images and resulting in substantial context loss. Toaddress this, we present UniK3D, the first generalizable method for monocular3D estimation able to model any camera. Our method introduces a spherical 3Drepresentation which allows for better disentanglement of camera and scenegeometry and enables accurate metric 3D reconstruction for unconstrained cameramodels. Our camera component features a novel, model-independent representationof the pencil of rays, achieved through a learned superposition of sphericalharmonics. We also introduce an angular loss, which, together with the cameramodule design, prevents the contraction of the 3D outputs for wide-viewcameras. A comprehensive zero-shot evaluation on 13 diverse datasetsdemonstrates the state-of-the-art performance of UniK3D across 3D, depth, andcamera metrics, with substantial gains in challenging large-field-of-view andpanoramic settings, while maintaining top accuracy in conventional pinholesmall-field-of-view domains. Code and models are available atgithub.com/lpiccinelli-eth/unik3d .<br