Editorial for Special Issue "Perspectives of Immunotherapy in Tumors of the Gastrointestinal Tract"

After transforming the therapeutic perspective of many solid neoplasms, immunotherapy is finally making its way in the setting of gastro-intestinal (GI) primary cancers [...]

The first confirmed superoutburst of the dwarf nova GALEX J215818.5+241924

In 2011 October an optical transient was reported in Pegasus as a possible nova. The object had an ultraviolet counterpart, GALEX J215818.5+241924. In this paper we present follow-up photometry of the object which revealed the presence of superhumps, with peak-to-peak amplitude of up to 0.22 magnitudes, diagnostic of it being a member of the SU UMa family of dwarf novae. The outburst amplitude was 4.6 magnitudes and it lasted at least 10 days, with a maximum brightness of magnitude 14.3. We determined the mean superhump period from our first 5 nights of observations as Psh = 0.06728(21) d. However analysis of the O-C residuals showed a dramatic evolution in Psh during the outburst. During the first part of the plateau phase the period increased with dPsh/dt = +2.67(15) x 10-4. There was then an abrupt change following which the period decreased with dPsh/dt = -2.08(9)x 10-4. We found a signal in the power spectrum of the photometry which we tentatively interpret as the orbital signal with Porb = 0.06606(35) d. Thus the superhump period excess was epsilon = 0.020(8), such value being consistent with other SU UMa systems of similar orbital period.Comment: Accepted for publication in the Journal of the British Astronomical Association. 10 pages, 3 figures. arXiv admin note: text overlap with arXiv:1005.5378. Have corrected outburst amplitude, reworded the first 2 sentences of the Abstract for clarity and solved some typo

Electrodermal Activity in the Evaluation of Engagement for Telemedicine Applications

Electrodermal Activity (EDA) is a broadly-investigated physiological signal, whose behaviour is connected to nervous system arousal. Such system, indeed, influences the properties of the skin, producing a measurable electrical signal. Among the possible applications of such measurements, several studies have correlated the signal behaviour to engagement during mental and physical tasks, and the subjects' response to specific multimodal stimuli. Also due to the possibility of performing remote assessment and rehabilitation, telemedicine applications are gaining ground in the healthcare system. However, acceptance and engagement, hence continuity of usage, still remain significant obstacles. Therefore, it would be highly beneficial to verify, through objective measures, if these solutions are actually providing a sufficient stimulation to properly engage subjects while playing. This study investigates the possibility of employing EDA in the automatic recognition of different levels of user engagement, while playing a motor-cognitive exergame specifically designed for this purpose. Preliminary results, obtained on a cohort of 25 healthy subjects, seem to confirm that features extracted from EDA analysis are significant and able to train supervised classifiers, achieving high accuracy and precision in the engagement recognition problem

A Preliminary Comparison between Traditional and Gamified Leg Agility Assessment in Parkinsonian Subjects

Parkinson's disease (PD) severity is assessed through a set of standardised tasks defined by clinical scales such as the Unified Parkinson's Disease Rating Scale (UPDRS). In particular, Leg Agility is a well-established test among the motor tasks included in UPDRS, which consists in repeated cycles of knee lifting and lowering, while sitting on a chair. Leg Agility objective evaluation through optical devices is often investigated for telemedicine applications. Moreover, remote rehabilitation for PD subjects through virtual exergaming is becoming a popular approach thanks to its versatility, increased user engagement and the possibility of coupling it with remote monitoring tools. This work investigates if lower-limb exergaming may also be exploited for assessment purposes similar to traditional evaluation. In particular, if there exists a statistical difference between the kinematic description of Leg Agility versus the one of a Bouncing Ball exergame, as provided by an optical (RGB-D) acquisition system suitable for remote monitoring. Preliminary results obtained by the comparison of the two types of assessment in a small group of parkinsonian subjects are presented and discussed

GMH-D: Combining Google MediaPipe and RGB-Depth Cameras for Hand Motor Skills Remote Assessment

Impairment in the execution of simple motor tasks involving hands and fingers could hint at a general worsening of health conditions, particularly in the elderly and in people affected by neurological diseases. The deterioration of hand motor function strongly impacts autonomy in daily activities and, consequently, the perceived quality of life. The early detection of alterations in hand motor skills would allow, for example, to promptly activate treatments and mitigate this discomfort. This preliminary study examines an innovative pipeline based on a single RGB-Depth camera and Google MediaPipe Hands, that is suitable for the remote assessment of hand motor skills through simple tasks commonly used in clinical practice. The study includes several phases. First, the quality of hand tracking is evaluated by comparing reconstructed and real hand 3D trajectories. The proposed solution is then tested on a cohort of healthy volunteers to estimate specific kinematic features for each task. Finally, these features are used to train supervised classifiers and distinguish between “normal” and “altered” performance by simulating typical motor behaviour of real impaired subjects. The preliminary results show the ability of the proposed solution to automatically highlight alterations in hand performance, providing an easy-to-use and non-invasive tool suitable for remote monitoring of hand motor skills

CMB Polarization Systematics, Cosmological Birefringence and the Gravitational Waves Background

Cosmic Microwave Background experiments must achieve very accurate calibration of their polarization reference frame to avoid biasing the cosmological parameters. In particular, a wrong or inaccurate calibration might mimic the presence of a gravitational wave background, or a signal from cosmological birefringence, a phenomenon characteristic of several non-standard, symmetry breaking theories of electrodynamics that allow for \textit{in vacuo} rotation if the polarization direction of the photon. Noteworthly, several authors have claimed that the BOOMERanG 2003 (B2K) published polarized power spectra of the CMB may hint at cosmological birefringence. Such analyses, however, do not take into account the reported calibration uncertainties of the BOOMERanG focal plane. We develop a formalism to include this effect and apply it to the BOOMERanG dataset, finding a cosmological rotation angle $\alpha=-4.3^\circ\pm4.1^\circ$. We also investigate the expected performances of future space borne experiment, finding that an overall miscalibration larger then $1^\circ$ for Planck and $0.2\circ$ for EPIC, if not properly taken into account, will produce a bias on the constraints on the cosmological parameters and could misleadingly suggest the presence of a GW background.Comment: 10 pages, 3 figure

The 2001 Superoutburst of WZ Sagittae

We report the results of a worldwide campaign to observe WZ Sagittae during its 2001 superoutburst. After a 23-year slumber at V=15.5, the star rose within 2 days to a peak brightness of 8.2, and showed a main eruption lasting 25 days. The return to quiescence was punctuated by 12 small eruptions, of ~1 mag amplitude and 2 day recurrence time; these “echo outbursts” are of uncertain origin, but somewhat resemble the normal outbursts of dwarf novae. After 52 days, the star began a slow decline to quiescence. Periodic waves in the light curve closely followed the pattern seen in the 1978 superoutburst: a strong orbital signal dominated the first 12 days, followed by a powerful common superhump at 0.05721(5) d, 0.92(8)% longer than Porb. The latter endured for at least 90 days, although probably mutating into a “late” superhump with a slightly longer mean period [0.05736(5) d]. The superhump appeared to follow familiar rules for such phenomena in dwarf novae, with components given by linear combinations of two basic frequencies: the orbital frequency ωo and an unseen low frequency Ω, believed to represent the accretion disk’s apsidal precession. Long time series reveal an intricate fine structure, with ~20 incommensurate frequencies. Essentially all components occurred at a frequency nωo–mΩ, with m=1, ..., n. But during its first week, the common superhump showed primary components at nωo–Ω, for n=1, 2, 3, 4, 5, 6, 7, 8, 9 (i.e., m=1 consistently); a month later, the dominant power shifted to components with m=n–1. This may arise from a shift in the disk’s spiral-arm pattern, likely to be the underlying cause of superhumps. The great majority of frequency components are red-shifted from the harmonics of ωo, consistent with the hypothesis of apsidal advance (prograde precession). But a component at 35.42 c/day suggests the possibility of a retrograde precession at a different rate, probably N=0.13±0.02 c/day. The eclipses permit measuring the location and brightness of the mass-transfer hot spot. The disk must be very eccentric and nearly aslarge as the white dwarf’s Roche lobe. The hotspot luminosity exceeds its quiescent value by a factor of up to 60. This indicates that enhanced mass transfer from the secondary plays a major role in the eruption. (Refer to PDF file for exact formulas)

Hand tracking for clinical applications: validation of the Google MediaPipe Hand (GMH) and the depth-enhanced GMH-D frameworks

Accurate 3D tracking of hand and fingers movements poses significant challenges in computer vision. The potential applications span across multiple domains, including human-computer interaction, virtual reality, industry, and medicine. While gesture recognition has achieved remarkable accuracy, quantifying fine movements remains a hurdle, particularly in clinical applications where the assessment of hand dysfunctions and rehabilitation training outcomes necessitate precise measurements. Several novel and lightweight frameworks based on Deep Learning have emerged to address this issue; however, their performance in accurately and reliably measuring fingers movements requires validation against well-established gold standard systems. In this paper, the aim is to validate the handtracking framework implemented by Google MediaPipe Hand (GMH) and an innovative enhanced version, GMH-D, that exploits the depth estimation of an RGB-Depth camera to achieve more accurate tracking of 3D movements. Three dynamic exercises commonly administered by clinicians to assess hand dysfunctions, namely Hand Opening-Closing, Single Finger Tapping and Multiple Finger Tapping are considered. Results demonstrate high temporal and spectral consistency of both frameworks with the gold standard. However, the enhanced GMH-D framework exhibits superior accuracy in spatial measurements compared to the baseline GMH, for both slow and fast movements. Overall, our study contributes to the advancement of hand tracking technology, the establishment of a validation procedure as a good-practice to prove efficacy of deep-learning-based hand-tracking, and proves the effectiveness of GMH-D as a reliable framework for assessing 3D hand movements in clinical applications

Evaluation of Arm Swing Features and Asymmetry during Gait in Parkinson’s Disease Using the Azure Kinect Sensor

Arm swinging is a typical feature of human walking: Continuous and rhythmic movement of the upper limbs is important to ensure postural stability and walking efficiency. However, several factors can interfere with arm swings, making walking more risky and unstable: These include aging, neurological diseases, hemiplegia, and other comorbidities that affect motor control and coordination. Objective assessment of arm swings during walking could play a role in preventing adverse consequences, allowing appropriate treatments and rehabilitation protocols to be activated for recovery and improvement. This paper presents a system for gait analysis based on Microsoft Azure Kinect DK sensor and its body-tracking algorithm: It allows noninvasive full-body tracking, thus enabling simultaneous analysis of different aspects of walking, including arm swing characteristics. Sixteen subjects with Parkinson’s disease and 13 healthy controls were recruited with the aim of evaluating differences in arm swing features and correlating them with traditional gait parameters. Preliminary results show significant differences between the two groups and a strong correlation between the parameters. The study thus highlights the ability of the proposed system to quantify arm swing features, thus offering a simple tool to provide a more comprehensive gait assessment

Efficacy and Safety of Bevacizumab Combined With Fluoropyrimidine Monotherapy for Unfit or Older Patients With Metastatic Colorectal Cancer: A Systematic Review and Meta-Analysis

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