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Impaired motor function is a defining characteristic of Parkinson’s disease (PD). Galvanic vestibular stimulation (GVS) has been proposed as a potential non-invasive intervention to enhance motor performance; however, its efficacy depends on both stimulation parameters and electrode configuration. In this study, we examined the effects of two-pole and three-pole GVS configurations, utilising different stimulation parameters, on motor performance in individuals with PD. Twelve participants with PD were administered eight distinct subthreshold amplitude-modulated GVS stimuli, along with sham stimulation, while performing a visuomotor target tracking task. Analysis of tracking error demonstrated substantial inter-individual variability in response to different stimuli and electrode configurations. While the three-pole configuration yielded superior motor performance in some cases, the two-pole configuration was more effective in others. The most effective overall stimulus across all subjects, characterised by an envelope frequency of 30 Hz and a carrier frequency of 110 Hz, improved motor performance by 25% relative to the sham stimulus. Moreover, tailoring the stimulation parameters to the individual further enhanced performance by an additional 24%. These findings suggest that GVS can yield significant motor improvements in individuals with PD. Furthermore, individualised optimisation of stimulation parameters, including the selection of the appropriate electrode configuration, may further enhance therapeutic efficacy.

ObjectivesThe COVID-19 pandemic has profound negative impacts on people’s lives, but little is known on its effect on household food insecurity (HFI) in poor setting resources. This study assessed changes in HFI during the pandemic and examined the interlinkages between HFI with child feeding practices and coping strategies.DesignA longitudinal survey in December 2019 (in-person) and August 2020 (by phone).SettingCommunity-based individuals from 26 blocks in 2 districts in Uttar Pradesh, India.ParticipantsMothers with children <2 years (n=569).Main outcomes and analysesWe measured HFI by using the HFI Access Scale and examined the changes in HFI during the pandemic using the Wilcoxon matched-pairs signed-rank tests. We then assessed child feeding practices and coping strategies by HFI status using multivariable regression models.ResultsHFI increased sharply from 21% in December 2019 to 80% in August 2020, with 62% households changing the status from food secure to insecure over this period. Children in newly or consistently food-insecure households were less likely to consume a diverse diet (adjusted OR, AOR 0.57, 95% CI 0.34 to 0.95 and AOR 0.51, 95% CI 0.23 to 1.12, respectively) compared with those in food-secure households. Households with consistent food insecurity were more likely to engage in coping strategies such as reducing other essential non-food expenditures (AOR 2.2, 95% CI 1.09 to 4.24), borrowing money to buy food (AOR 4.3, 95% CI 2.31 to 7.95) or selling jewellery (AOR 5.0, 95% CI 1.74 to 14.27) to obtain foods. Similar findings were observed for newly food-insecure households.ConclusionsThe COVID-19 pandemic and its lockdown measures posed a significant risk to HFI which in turn had implications for child feeding practices and coping strategies. Our findings highlight the need for further investment in targeted social protection strategies and safety nets as part of multisectoral solutions to improve HFI during and after COVID-19.

Automatic Speech Recognition (ASR) engines are extremely susceptible to noise. There is an increasing prevalence of voice-assisted devices which need to recognize speech accurately in a variety of complex listening environments. These include the presence of background noise, reverberation, and multiple talkers. The human auditory system, on the other hand, is very good at understanding speech even in extremely challenging environments. It might therefore, be useful to use our knowledge of human hearing to develop techniques that lead to robust speech recognition. This entails applying techniques that have their basis in human auditory processing towards automatic speech recognition (ASR). In this thesis, we discuss a number of techniques that address the problem of robust recognition of binaural signals in the presence of reverberation and multiple talkers since they pose a significant problem in terms of ASR engine performance. The techniques discussed here roughly follow the manner in which the auditory system achieves noise robustness. The fundamental idea behind all the techniques proposed is that sounds emanating from the same sound source exhibit some degree of coherence. We aim to use this property to achieve better isolation of the target signal leading to better speech recognition accuracy. Three techniques are proposed. The Interaural Cross-correlation-basedWeighting (ICW) algorithm looks for coherence across sensors using signal envelopes in order to isolate signals coming from the same location. To reduce the effect of reverberation, steady-state suppression is applied as an initial step. The ICW algorithm combined with steady-state suppression leads to significant improvements in ASR accuracy. The Coherence-to-Diffuse Ratio-based Weighting (CDRW) algorithm uses a model-based technique to evaluate the ratio of coherent energy to diffuse energy in a given signal. This leads to significantly better performance in ASR. The third technique is the Cross-Correlation across Frequency (CCF) algorithm, which looks for coherence in frequency for signal separation. The CCF algorithm also effectively smooths the signal. This algorithm has been tested in conjunction with steady-state suppression and ITD-based analysis. The CCF algorithm leads to improvements in ASR especially in the presence of moderate to high reverberation when the system is trained on clean speech. All algorithmswere tested using DNN-based acoustical models obtained with the Kaldi speech recognition toolkit, using both clean and multistyle training data.

Adolescent wellbeing is critical to breaking the intergenerational cycle of poverty and one in five of the world's adolescents live in India. We explored predictors of learning skills and depression in Indian adolescents. Data on adolescents aged 10-19y (three groups: 5,840 unmarried males, 8,953 unmarried females, 4,933 married females) were available from the state-representative Understanding the Lives of Adolescents and Young Adults survey in Uttar Pradesh and Bihar. Multivariable logistic regression models adjusted for cluster sampling design and state fixed effects were used to examine factors (demographic, health/nutrition, social, and environmental) associated with three outcomes: reading proficiency, math proficiency, and depressive symptoms. Learning skills were poor (28-61% lacked basic reading and math skills depending on adolescent group and outcome) and depression was common (8-26%). Better learning skills were predicted by greater household wealth (AOR 1.72-2.55 depending on group) and household head education (AOR 1.03-1.07 per year), being in school (AOR 4.19-18.65), parental support (AOR 1.11-1.39), having gender equal attitudes (AOR 1.56-2.67), number of food groups consumed at least weekly (unmarried females: AOR 1.11), and having an improved latrine (AOR 1.33-1.51). Poorer learning skills were predicted by family substance use (AOR 0.68-0.74), underweight (males: AOR 0.74), witnessing parental violence (AOR 0.66-0.78). Depressive symptoms were predicted by witnessing parental violence (AOR 1.51-1.92) and experiencing sexual abuse (AOR 2.30-6.16). Factors across multiple life dimensions are associated with learning skills and depression in Indian adolescents. Adolescent-focused policies and programs should consider health/nutrition, social, and environmental aspects of life in vulnerable individuals.

The COVID‐19 pandemic is expected to have profound effects on healthcare systems, but little evidence exists on service provision, utilisation, or adaptations. This study aimed to (1) examine the changes to health and nutrition service delivery and utilisation in urban Bangladesh during and after enforcement of COVID‐19 restrictions and (2) identify adaptations and potential solutions to strengthen delivery and uptake. We conducted longitudinal surveys with health care providers (n = 45), pregnant women (n = 40), and mothers of children <2 years (n = 387) in February 2020 (in‐person) and September 2020 (by phone). We used Wilcoxon matched‐pairs signed‐rank tests to compare the changes before and during the pandemic. Services delivery for women and children which require proximity were severely affected; weight and height measurements fell by 20–29 percentage points (pp) for pregnant women and 37–57 pp for children, and child immunisations fell by 38 pp. Declines in service utilisation were large, including drops in facility visitations (35 pp among pregnant women and 67 pp among mothers), health and nutrition counselling (up to 73 pp), child weight measurements (50 pp), and immunisations (61 pp). The primary method of adaptation was provision of services over phone (37% for antenatal care services, 44%–49% for counselling). Despite adaptations to service provision, continued availability of routine maternal and child health services did not translate into service utilisation. Further investments are needed to provide timely and accurate information on COVID‐19 to the general public, improve COVID‐19 training and provide incentives for health care providers and ensure availability of personal protective equipment for providers and beneficiaries.

The present study examines the link between parents\" and children's implicit theories of intelligence. Dweck and colleagues have identified two types of implicit theories of intelligence: with an \"entity\" theory, an individual views intelligence as a fixed trait and tends to avoid challenges; with an \"incremental\" theory, an individual views intelligence as a malleable trait and tends to persist through challenges (Dweck & Leggett, 1986). Such implicit theories may matter especially for children from economically disadvantaged families. Research has shown that these children not only face disproportionate academic challenges but also are more likely to lack persistence in the face of challenges (Herbers et al., 2012).The motivation of this study stems from the question of what might influence responses to academic challenges for economically disadvantaged children before they face the failure and comparison processes associated with formal schooling. Ames and Archer (1987) demonstrated the influence of parent implicit theories of intelligence on aspects of parenting. The present study aims to expand upon what is understood about the relationship between parent and child intelligence theories. Specifically, the study examines parents\" implicit theories of intelligence as a predictor of preschool children's approaches to challenge. The hypothesis is that the extent to which parents rate intelligence as being fixed rather than malleable will statistically predict the extent to which their children show behaviors reflective of emergent entity theories of intelligence.The study included 373 children attending a Head Start preschool. Trained research assistants guided parents to complete questionnaires about family demographics and implicit theories of intelligence and administered to children a puzzle task designed to tap responses to challenge that signal emergent implicit theories of intelligence. Results of a hierarchical linear regression analysis suggested that parents' implicit theories of intelligence statistically predicted children's responses to challenge.Results suggest the importance of parent views of intelligence for predicting their children's emergent theories of intelligence as early as preschool years. Implications concern understanding the mechanisms of effect that link parent and child implicit theories of intelligence and promoting positive academic outcomes for economically disadvantaged children.

Subjective evaluations are critical for assessing the perceptual realism of sounds in audio-synthesis driven technologies like augmented and virtual reality. However, they are challenging to set up, fatiguing for users, and expensive. In this work, we tackle the problem of capturing the perceptual characteristics of localizing sounds. Specifically, we propose a framework for building a general purpose quality metric to assess spatial localization differences between two binaural recordings. We model localization similarity by utilizing activation-level distances from deep networks trained for direction of arrival (DOA) estimation. Our proposed metric (DPLM) outperforms baseline metrics on correlation with subjective ratings on a diverse set of datasets, even without the benefit of any human-labeled training data.

Modeling studies estimated severe impacts of potential service delivery disruptions due to COVID-19 pandemic on maternal and child nutrition outcomes. Although anecdotal evidence exists on disruptions, little is known about the actual state of service delivery at scale. We studied disruptions and restorations, challenges and adaptations in health and nutrition service delivery by frontline workers (FLWs) in India during COVID-19 in 2020. We conducted phone surveys with 5500 FLWs (among them 3118 Anganwadi Workers) in seven states between August-October 2020, asking about service delivery during April 2020 (T1) and in August-October (T2), and analyzed changes between T1 and T2. We also analyzed health systems administrative data from 704 districts on disruptions and restoration of services between pre-pandemic (December 2019, T0), T1 and T2. In April 2020 (T1), village centers, fixed day events, child growth monitoring, and immunization were provided by <50% of FLWs in several states. Food supplementation was least disrupted. In T2, center-based services were restored by over a third in most states. Administrative data highlights geographic variability in both disruptions and restorations. Most districts had restored service delivery for pregnant women and children by T2 but had not yet reached T0 levels. Adaptations included home delivery (60 to 96%), coordinating with other FLWs (7 to 49%), and use of phones for counseling (~2 to 65%). Personal fears, long distances, limited personal protective equipment, and antagonistic behavior of beneficiaries were reported challenges. Services to mothers and children were disrupted during stringent lockdown but restored thereafter, albeit not to pre-pandemic levels. Rapid policy guidance and adaptations by FLWs enabled restoration but little remains known about uptake by client populations. As COVID-19 continues to surge in India, focused attention to ensuring essential services is critical to mitigate these major indirect impacts of the pandemic.