Adaptive Deep Learning through Visual Domain Localization

A commercial robot, trained by its manufacturer to recognize a predefined number and type of objects, might be used in many settings, that will in general differ in their illumination conditions, background, type and degree of clutter, and so on. Recent computer vision works tackle this generalization issue through domain adaptation methods, assuming as source the visual domain where the system is trained and as target the domain of deployment. All approaches assume to have access to images from all classes of the target during training, an unrealistic condition in robotics applications. We address this issue proposing an algorithm that takes into account the specific needs of robot vision. Our intuition is that the nature of the domain shift experienced mostly in robotics is local. We exploit this through the learning of maps that spatially ground the domain and quantify the degree of shift, embedded into an end-to-end deep domain adaptation architecture. By explicitly localizing the roots of the domain shift we significantly reduce the number of parameters of the architecture to tune, we gain the flexibility necessary to deal with subset of categories in the target domain at training time, and we provide a clear feedback on the rationale behind any classification decision, which can be exploited in human-robot interactions. Experiments on two different settings of the iCub World database confirm the suitability of our method for robot vision

Adaptive Deep Learning through Visual Domain Localization

A commercial robot, trained by its manufacturer to recognize a predefined number and type of objects, might be used in many settings, that will in general differ in their illumination conditions, background, type and degree of clutter, and so on. Recent computer vision works tackle this generalization issue through domain adaptation methods, assuming as source the visual domain where the system is trained and as target the domain of deployment. All approaches assume to have access to images from all classes of the target during training, an unrealistic condition in robotics applications. We address this issue proposing an algorithm that takes into account the specific needs of robot vision. Our intuition is that the nature of the domain shift experienced mostly in robotics is local. We exploit this through the learning of maps that spatially ground the domain and quantify the degree of shift, embedded into an end-to-end deep domain adaptation architecture. By explicitly localizing the roots of the domain shift we significantly reduce the number of parameters of the architecture to tune, we gain the flexibility necessary to deal with subset of categories in the target domain at training time, and we provide a clear feedback on the rationale behind any classification decision, which can be exploited in human-robot interactions. Experiments on two different settings of the iCub World database confirm the suitability of our method for robot vision.Comment: Accepted at ICRA 201

The Koukopoulos mixed depression rating scale (KMDRS) and the assessment of mixed symptoms during the perinatal period

Background: Mixed symptoms in depression may underlie bipolar diathesis rather than unipolarity. Uncovering mixed depression (MxD) is crucial for appropriate management, especially in the perinatal period, as it may affect treatment planning and impact future child development. We used a scale specific for identifying MxD and tested its validity in pregnant and postpartum women with depression. Methods: Women developing a major depressive episode (MDE) during their perinatal period extending from pregnancy to one year postpartum from November-2012 through June-2019 were assessed with BPRS-18, EPDS, CGI-S, GAF, HAM-A, HAM-D, Koukopoulos' Mixed Depression Rating Scale (KMDRS), TEMPS, and YMRS. They were classified, based on KMDRS criteria, as with mixed (MxD) or without (nonMxD) mixed symptoms. We conducted ROC analysis and performed factor analysis of the KMDRS. Results: Of 45 included, MxD (N = 19) were biased towards diagnosis of bipolar disorder and nonMxD (N = 26) towards major depressive disorder. Other sociodemographic variables did not differ significantly between MxD and nonMxD. MxD scored higher on total YMRS, BPRS, and KMDRS, and on KMDRS-6 Subjective Feelings of Irritability and KMDRS-12 Suicidal Impulsiveness items. The KMDRS correlated in the entire sample, in MxD and nonMxD, with the YMRS and the BPRS, while correlating with the HAM-D in nonMxD only. The KMDRS showed acceptable AUC distribution, with a 68% sensitivity and 58% specificity. Best-fit was three-factor-structure, explaining 54.66% of cumulative variance. Limitations: Small sample and cross-sectional design. Conclusions: The KMDRS is fit for investigating MxD along with the YMRS and the BPRS in perinatal women with a MDE

Perinatal Mood and Anxiety Disorders in Women Undergoing Medically Assisted Reproduction

Background: Women taking advantage of medically assisted reproduction (MAR) techniques may differ from spontaneously conceiving women (nonMAR) in risk of depression and/or anxiety. We aimed to investigate possible differences between MAR and nonMAR through the use of the Edinburgh Postnatal Depression Scale in a sample of Italian-speaking women at their third trimester of pregnancy. Methods: We administered the Edinburgh Postnatal Depression Scale (EPDS) to two groups of pregnant women, MAR and nonMAR, at the third trimester of pregnancy (T0), one month after delivery (T1), and three months after delivery (T2) from February 2013 to December 2019. EPDS total scores cutoffs were ≥9 for risk of depression, 9–11 mild depression, ≥12 major depression, and the EPDS-3A cluster ≥4 was a proxy for anxiety. Results: Included were 1303 nonMAR women and 92 MAR, an expected disproportion. NonMAR and MAR women did not differ on depression or anxiety at any assessment timepoint. MAR women were older than nonMAR, consumed more alcohol and medical drugs, and displayed more complications during pregnancy. Scoring over the threshold on depression risk was associated with foreign nationality, unemployment, psychiatric history of the patient, family or partner, psychiatric problems in past pregnancies, hyperemesis, premenstrual syndrome (PMS), and stressful life events in the last year at baseline, and, for some of them, at other timepoints. In contrast, MAR past or current was associated with having suprathreshold depression at the first-month postpartum follow-up. Conclusions: Taken together, our data show that women opting for MAR do not differ from spontaneously conceiving women regarding psychiatric outcomes but do differ on some sociodemographic and clinical variables

The Attentional Boost Effect in Young and Adult Euthymic Bipolar Patients and Healthy Controls

In the Attentional Boost Effect (ABE), stimuli encoded with to-be-responded targets are later recognized more accurately than stimuli encoded with to-be-ignored distractors. While this effect is robust in young adults, evidence regarding healthy older adults and clinical populations is sparse. The present study investigated whether a significant ABE is present in bipolar patients (BP), who, even in the euthymic phase, suffer from attentional deficits, and whether the effect is modulated by age. Young and adult euthymic BP and healthy controls (HC) presented with a sequence of pictures paired with target or distractor squares were asked to pay attention to the pictures and press the spacebar when a target square appeared. After a 15-min interval, their memory of the pictures was tested in a recognition task. The performance in the detection task was lower in BP than in HC, in both age groups. More importantly, neither young nor adult BP exhibited a significant ABE; for HC, a robust ABE was only found in young participants. The results suggest that the increase in the attentional demands of the detection task in BP and in adult HC draws resources away from the encoding of target-associated stimuli, resulting in elimination of the ABE. Clinical implications are discussed

Efficacy of Supra-HFR in Removing FGF23 and Cytokines: A Single Session Analysis

Background/Aim: Supra hemodiafiltration with reinfusion of the endogenous ultrafiltrate (Supra-HFR) is a dialysis technique used to improve uremic toxin removal in the range of the middle molecular weight molecules. Supra-HFR does not require the preparation and online infusion of high purity dialysis water because it allows the production of an endogenous ultrafiltrate that undergoes detoxification through an adsorbing resin. Patients and Methods: We investigated the ability of Supra-HFR to remove fibroblast growth factor 23 (FGF23), interleukin 6 (IL-6), tumor necrosis factor alpha (TNFalpha), interleukin 8 (IL-8), and transforming growth factor alpha (TGF-alpha) after a single session dialysis in nine patients affected by end stage renal disease (ESRD). The same patients underwent a single session of online hemodiafiltration (OLHDF) to evaluate possible differences in FGF23 and IL-6 levels. Results: A significant reduction in FGF23 was observed with both Supra-HFR (p=0.001) and OL-HDF. As for TNF-alpha and TGF-alpha, which were measured using Supra-HFR only, their percentage values were significantly lower at the end of dialysi

Impact of Single Hemodialysis Treatment on immune Cell Subpopulations

: Hemodialysis (HD) is known to trigger a chronic inflammatory status, affecting the innate and acquired immune response. This study was aimed at a comparative analysis of immune cell subsets, proliferation, and apoptosis in subjects receiving chronic HD treatment with respect to a healthy control. Regardless of the dialysis filter used, we observed a reshaping of the acquired immune component both with respect to healthy patients and between the various sessions of dialysis treatment, with an impairment of CD3 cells, along with an increase in CD4 and CD8 cell populations producing pro-inflammatory factors such as IL-17 and IFN-gamma. The population of B cells, monocytes and NK cells were not impaired by the dialysis procedure. These results confirmed the high impact of the HD treatment on the patient's immune system, underlying the imbalance of T cell counterparts

Psychometric Properties of the Perinatal Anxiety Screening Scale Administered to Italian Women in the Perinatal Period

Literature stressed the importance of using valid, reliable measures to assess anxiety in the perinatal period, like the self-rated Perinatal Anxiety Screening Scale (PASS). We aimed to examine the psychometric properties of the Italian PASS version in a sample of Italian women undergoing mental health screening during their third trimester of pregnancy and its diagnostic accuracy in a control perinatal sample of psychiatric outpatients. Sample comprised 289 women aged 33.17 ± 5.08, range 19–46 years, undergoing fetal monitoring during their third trimester of pregnancy, with 49 of them retested 6 months postpartum. Controls were 60 antenatal or postnatal psychiatric outpatients aged 35.71 ± 5.02, range 22–50 years. Groups were assessed through identical self- and clinician-rating scales. Confirmatory Factor Analysis (CFA), Principal Component Analysis (PCA), Pearson's correlations and receiver operating characteristic were conducted for PASS. PCA and CPA confirmed four-factor structure with slight differences from the original version. Construct validity and test-retest reliability were supported. Cut-off was 26. The PASS correlated with principal anxiety scales. Despite small sample size, findings confirm reliability and validity of the Italian PASS version in assessing anxiety symptoms in the perinatal period. Its incorporation in perinatal care will improve future mother and child psychological health

Depressive Symptoms during Pregnancy. Prevalence and Correlates with Affective Temperaments and Psychosocial Factors

Pregnancy is a unique experience in women's life, requiring a great ability of adaptation and self-reorganization; vulnerable women may be at increased risk of developing depressive symptoms. This study aimed to examine the incidence of depressive symptomatology during pregnancy and to evaluate the role of affective temperament traits and psychosocial risk factors in predicting them. We recruited 193 pregnant women, collected data regarding sociodemographic, family and personal clinical variables, social support and stressful life events and administered the Mood Disorder Questionnaire (MDQ), the Patient Health Questionnaire-9 (PHQ-9), and the Temperament Evaluation of Memphis, Pisa, Paris and San Diego-Autoquestionnaire (TEMPS-A). In our sample, prevalence of depressive symptomatology was 41.45% and prevalence of depression was 9.85% (6.75% mild and 3.10% moderate depression). We have chosen a cutoff >4 on PHQ-9 to identify mild depressive symptoms which may predict subsequent depression. Statistically significant differences between the two groups were found in the following factors: gestational age, occupation, partner, medical conditions, psychiatric disorders, family psychiatric history, stressful life events, and TEMPS-A mean scores. In our sample mean scores on all affective temperaments but the hyperthymic, were significantly lower in the control group. Only depressive and hyperthymic temperaments were found to be, respectively, risk and protective factors for depressive symptomatology. The current study confirms the high prevalence and complex aetiology of depressive symptomatology during pregnancy and suggests that affective temperament assessment seems to be a useful adjunctive instrument to predict depressive symptomatology during pregnancy and postpartum

DEPRESSIVE SYMPTOMS, TEMPERAMENT/CHARACTER, AND ATTENTION DEFICIT/HYPERACTIVITY DISORDER TRAITS IN MEDICAL STUDENTS SEEKING COUNSELIN

Background: To investigate depressive symptoms, temperament, and attention deficit/hyperactivity disorder traits in medical students, comparing those who sought psychological counseling with those who did not seek it. Subjects and methods: We assessed 49 students seeking counseling (mean age=24.4 years, SD=4.07) and 49 noncounseling controls (mean age=21.7 years, SD=2.6). Participants were assessed for depressive symptoms with the Beck Depression Inventory- II, for temperament/character dimensions using the Temperament and Character Inventory-Revised, and for attention deficit/hyperactivity symptoms using the Adult ADHD Self-Report Scale. Results: Counseling-seeking students were more likely to have attention deficit/hyperactivity symptoms, scored higher on the Beck Depression Inventory-II and on the Temperament and Character Inventory-Revised Harm avoidance, and lower on the Temperament and Character Inventory-Revised Self-Directedness, compared to controls. Conclusions: Medical students applying for counseling should be carefully assessed for depressive symptoms, attention deficit/hyperactivity symptoms, and temperament characteristics; depressive and attention deficit/hyperactivity symptoms could be the focus of counseling interventions