Publications

Investigating children’s embodied learning in mixed-reality environments, where they collaboratively simulate scientific processes, requires analyzing complex multimodal data to interpret their learning and coordination behaviors. Learning scientists have developed Interaction Analysis (IA) methodologies for analyzing such data, but this requires researchers to watch hours of videos to extract and interpret students’ learning patterns. Our study aims to simplify researchers’ tasks, using Machine Learning and Multimodal Learning Analytics to support the IA processes. Our study combines machine learning algorithms and multimodal analyses to support and streamline researcher efforts in developing a comprehensive understanding of students’ scientific engagement through their movements, gaze, and affective responses in a simulated scenario. To facilitate an effective researcher-AI partnership, we present an initial case study to determine the feasibility of visually representing students’ states, actions, gaze, affect, and movement on a timeline. Our case study focuses on a specific science scenario where students learn about photosynthesis. The timeline allows us to investigate the alignment of critical learning moments identified by multimodal and interaction analysis, and uncover insights into students’ temporal learning progressions.

Rab GTPases, the highly conserved members of Ras GTPase superfamily are the pivotal regulators of vesicle-mediated trafficking. Rab GTPases, each with a specific subcellular localization, exert tremendous control over various aspects of vesicular transport, identity and dynamics. Several lines of research have established that GDI, GEFs and GAPs are the critical players to orchestrate Rab GTPase activity and function. The importance of post translational modifications in Rab GTPase functional regulation is poorly or not yet been addressed except for prenylation. Our recent study has revealed a novel dephosphorylation dependent regulatory mechanism for Rab7 activity and function. We have shown the importance of PTEN mediated dephosphorylation of Rab7 on highly conserved S72 and Y183 residues, which is essential for its GDI mediated membrane targeting and further activation by GEF. In conclusion, our study highlighted the importance of a phosphorylation/dephosphorylation switch in controlling timely Rab7 localization and activity on endosomes.

Conical intersection (CI) leads to fast electronic energy transfer. However, Hamm and Stock [Phys. Rev. Lett. 109, 173201 (2012)] showed the existence of a vibrational CI and its role in vibrational energy relaxation. In this paper, we further investigate the vibrational energy relaxation using an isolated model Hamiltonian system of four vibrational modes with two distinctively different timescales (two fast modes and two slow modes). We show that the excitation of the slow modes plays a crucial role in the energy relaxation mechanism. We also analyze the system from a mixed quantum-classical (surface hopping method) and a completely classical point of view. Notably, surface hopping and even classical simulations also capture fast energy relaxation, which is a signature of CI’s existence.

Algorithmic bias in educational environments has garnered increasing scrutiny, with numerous studies highlighting its significant impacts. This research contributes to the field by investigating algorithmic biases, i.e., selection, label, and data biases in the assessment of students’ affective states through video analysis in two educational settings: (1) an open-ended science learning environment and (2) an embodied learning context, involving 41 and 12 students, respectively. Utilizing the advanced High-speed emotion recognition library (HSEmotion) and Multi-task Cascaded Convolutional Networks (MTCNN), and contrasting these with the commercially available iMotions platform, our study delves into biases in these systems. We incorporate real student data to better represent classroom demographics. Our findings not only corroborate the existence of algorithmic bias in detecting student emotions but also highlight successful bias mitigation strategies. The research advances the development of equitable educational technologies and supports the emotional well-being of students by demonstrating that targeted interventions can effectively diminish biases.

Herein we report on the investigation of microwave-assisted catalytic transfer hydrogenation (TH) of carbonyl and nitro compounds by employing Ru(II) complexes bimetallic [(p-cymene)2(RuCl)2L1]2X (X = BF4(Cat2); X = PF6(Cat3)) and mononuclear [(p-cymene)(RuCl)L2]BF4(Cat4) (where L1= N,N'-(3,3',5,5'-tetraisopropyl-[1,1'-biphenyl]-4,4'-diyl)bis(1-(pyridin-2-yl)methanimine); L2 = N-(2,6-diisopropyl-phenyl)-1-(pyridin-2-yl)-methanimine). At a low catalyst loading of 0.01 mol% (Cat2/Cat3), a broad substrate scope has been achieved for aromatic as well as aliphatic ketones and aldehydes, with a short reaction time of just 10 minutes. Additionally, chemoselective hydrogenation of nitroaromatic compounds has been achieved under microwave irradiation by Cat2 within 5 minutes. Control experiments demonstrate that microwave heating conditions outperform conventional heating method in terms of improved catalytic activity and reaction efficiency. The bimetallic Cat2 catalyst can be used at a very low loading of 0.001 mol% to achieve the high TONs and TOFs of 7.7 × 104and 2.3 × 105h-1, respectively, for TH reaction. Spectrometry experiments for intermediate trapping have been used to propose a probable mechanism for TH of carbonyl compounds.

Recent advances in quantum information and quantum science have inspired the development of various compact, dynamically structured ansätze that are expected to be realizable in Noisy Intermediate-Scale Quantum (NISQ) devices. However, such ansätze construction strategies hitherto developed involve considerable measurements, and thus, they deviate significantly in the NISQ platform from their ideal structures. Therefore, it is imperative that the usage of quantum resources be minimized while retaining the expressivity and dynamical structure of the ansatz that can adapt itself depending on the degree of correlation. We propose a novel ansatz construction strategy based on the ab initio many-body perturbation theory that requires no pre-circuit measurement and, thus, remains structurally unaffected by any hardware noise. The accuracy and quantum complexity associated with the ansatz are solely dictated by a pre-defined perturbative order, as desired, and, hence, are tunable. Furthermore, the underlying perturbative structure of the ansatz construction pipeline enables us to decompose any high-rank excitation that appears in higher perturbative orders into the product of various low-rank operators, and it thus keeps the execution gate-depth to its minimum. With a number of challenging applications on strongly correlated systems, we demonstrate that our ansatz performs significantly better, both in terms of accuracy, parameter count, and circuit depth, in comparison to the allied unitary coupled cluster based ansätze.

The common tool for assessment of breathing-type debonding in metallic or composite structures is nonlinear guided wave-based technique. The past studies show that with debonding size, the strength of the nonlinearity does not exhibit strictly increasing or decreasing trends, or that the monocity is valid up to a certain size limit of debonding. This paper presents the study of non-linear interaction of guided waves in the debonding interface of a metallic stiffened panel. The study attempts to establish a relationship between the contact energy generated by the contact acoustic nonlinearity (CAN) at the debonding interface and the associated nonlinearity strength for various debonding sizes at various excitation frequencies. A numerical model of the stiffened panels is developed in three-dimensional finite element (FE) and validated with experiments for the study of interaction of nonlinear guided waves. The validated FE model is used to conduct studies on nonlinear interactions in debonding. The outcome of this study contributes to a better understanding of how guided waves can be used to effectively assess the debonding in metallic stiffened panels by considering non-linear interactions at the debonding interface. The study also provides insights into a more accurate and consistent quantification of the debonding using higher harmonic signals and contact energy produced by non-linear interactions.

This manuscript presents a discussion on the algebraic state update step performed during recursive filtering of the differential–algebraic equation (DAE) systems. Existing DAE state estimation approaches follow a two-step state update procedure at each sampling instant. In particular, they first estimate the differential states using the Kalman update, and then update algebraic states by explicitly solving the algebraic equations. Specifically, for the case of DAE systems involving linear algebraic equations though the differential equations are nonlinear, we show that when appropriately initialized, this two-step state update procedure is not needed. It can instead be replaced with a one-step state update procedure that computes the differential and algebraic state estimates simultaneously through the Kalman update. The satisfaction of algebraic equations is guaranteed by this one-step update without it being explicitly enforced. Towards this end, we show that the error covariance matrix of augmented states, when properly initialized, satisfies a null-space property after prediction and update step at each sampling instant. This property ensures that the state estimates obtained using the proposed one-step update approach, satisfy the algebraic equations. This holds for both analytical linearization based extended Kalman filtering and statistical linearization based sigma-point filtering approaches. We also propose a heuristic-based update procedure for state estimation of DAE systems that involve nonlinear algebraic equations. This procedure draws out inferences from the case of DAE systems involving linear algebraic equations and is based on the analysis of algebraic equations residuals obtained from the updated differential and algebraic state estimates with a one-step state update. The efficacy of the proposed state update procedures is demonstrated by performing simulation studies on a benchmark drum boiler system case study. Results demonstrate that the proposed update procedures satisfactorily estimate the differential and algebraic states of a DAE system when compared to the traditional two-step update procedure.

Rab GTPases, the highly conserved members of Ras GTPase superfamily are central players in the vesicular trafficking. They are critically involved in intracellular trafficking pathway, beginning from formation of vesicles on donor membranes, defining trafficking specificity to facilitating vesicle docking on target membranes. Given the dynamic roles of Rabs during different stages of vesicular trafficking, mechanisms for their spatial and temporal regulation are crucial for normal cellular function. Regulation of Rab GTPase activity, localization and function has always been focused in and around the association of GDP dissociation inhibitor (GDI), Guanine nucleotide Exchange Factor (GEFs) and GTPase accelerating protein (GAP) to Rabs. However, several recent studies have highlighted the importance of different post-translational modifications in regulation of Rab activation and function. This review provides a summary of various post translational modifications (PTMs) and their significance to regulate localization and function of different Rabs.

Tumour suppressor phosphatase and tensin homologue deleted on chromosome 10 (PTEN) is a lipid phosphatase that negatively regulates growth factor-induced survival signalling. Here, we demonstrate that PTEN attenuates epidermal growth factor receptor (EGFR) signalling by promoting late endosome maturation by virtue of its protein phosphatase activity. Loss of PTEN impairs the transition of ligand-bound EGFR from early to late endosomes. We unveil Rab7, a critical GTPase for endosome maturation, as a functional PTEN interacting partner. PTEN dephosphorylates Rab7 on two conserved residues S72 and Y183, which are necessary for GDP dissociation inhibitor (GDI)-dependent recruitment of Rab7 on to late endosomes and subsequent maturation. Thus, our findings reveal PTEN-dependent endosome maturation through phosphoregulation of Rab7 as an important route of controlling EGFR signalling.

The tumor suppressor PTEN executes cellular functions predominantly through its phosphatase activity. Here we identified a phosphatase-independent role for PTEN during vesicular trafficking of the glucose transporter GLUT1. PTEN physically interacts with SNX27, a component of the retromer complex that recycles transmembrane receptors such as GLUT1 from endosomes to the plasma membrane. PTEN binding with SNX27 prevents GLUT1 accumulation at the plasma membrane because of defective recycling and thus reduces cellular glucose uptake. Mechanistically, PTEN blocks the association of SNX27 with VPS26 and thereby hinders assembly of a functional retromer complex during the receptor recycling process. Importantly, we found a PTEN somatic mutation (T401I) that is defective in disrupting the association between SNX27 and VPS26, suggesting a critical role for PTEN in controlling optimal GLUT1 levels at the membrane to prevent tumor progression. Together, our results reveal a fundamental role of PTEN in the regulation of the SNX27 retromer pathway, which governs glucose transport and might contribute to PTEN tumor suppressor function. Shinde et al. identify a critical role for the tumor suppressor PTEN in the regulation of glucose uptake by cells. PTEN binds SNX27 and hinders its access to the VPS26 retromer complex, preventing recycling of the glucose transporter GLUT1 to the plasma membrane, which leads to impaired cellular glucose uptake.

Many G protein-coupled receptors (GPCRs) reside within cilia of mammalian cells and must undergo regulated exit from cilia for the appropriate transduction of signals such as hedgehog morphogens. Lysine 63-linked ubiquitin (UbK63) chains mark GPCRs for regulated removal from cilia, but the molecular basis of UbK63 recognition inside cilia remains elusive. Here, we show that the BBSome—the trafficking complex in charge of retrieving GPCRs from cilia—engages the ancestral endosomal sorting factor target of Myb1-like 2 (TOM1L2) to recognize UbK63 chains within cilia of human and mouse cells. TOM1L2 directly binds to UbK63 chains and the BBSome, and targeted disruption of the TOM1L2/BBSome interaction results in the accumulation of TOM1L2, ubiquitin, and the GPCRs SSTR3, Smoothened, and GPR161 inside cilia. Furthermore, the single-cell alga Chlamydomonas also requires its TOM1L2 ortholog in order to clear ubiquitinated proteins from cilia. We conclude that TOM1L2 broadly enables the retrieval of UbK63-tagged proteins by the ciliary trafficking machinery.

While machine learning (ML) has been quite successful in the field of structural health monitoring (SHM), its practical implementation has been limited. This is because ML model training requires data containing a variety of distinct instances of damage captured from a real structure and the experimental generation of such data is challenging. One way to tackle this issue is by generating training data through numerical simulations. However, simulated data cannot capture the bias and variance of experimental uncertainty. To overcome this problem, this work proposes a deep-learning-based domain transformation method for transforming simulated data to the experimental domain. Use of this technique has been demonstrated for debonding location and size predictions of stiffened panels using a vibration-based method. The results are satisfactory for both debonding location and size prediction. This domain transformation method can be used in any field in which experimental data for training machine-learning models is scarce.

Regulated trafficking of G protein–coupled receptors (GPCRs) controls cilium-based signaling pathways. β-Arrestin, a molecular sensor of activated GPCRs, and the BBSome, a complex of Bardet–Biedl syndrome (BBS) proteins, are required for the signal-dependent exit of ciliary GPCRs, but the functional interplay between β-arrestin and the BBSome remains elusive. Here we find that, upon activation, ciliary GPCRs become tagged with ubiquitin chains comprising K63 linkages (UbK63) in a β-arrestin–dependent manner before BBSome-mediated exit. Removal of ubiquitin acceptor residues from the somatostatin receptor 3 (SSTR3) and from the orphan GPCR GPR161 demonstrates that ubiquitination of ciliary GPCRs is required for their regulated exit from cilia. Furthermore, targeting a UbK63-specific deubiquitinase to cilia blocks the exit of GPR161, SSTR3, and Smoothened (SMO) from cilia. Finally, ubiquitinated proteins accumulate in cilia of mammalian photoreceptors and Chlamydomonas cells when BBSome function is compromised. We conclude that Ub chains mark GPCRs and other unwanted ciliary proteins for recognition by the ciliary exit machinery.

The late Maastrichtian witnessed substantial surges in Deccan volcanism, prompting the hypothesis that these voluminous pulses may have instigated repeated episodes of ocean acidification during this period. The Cretaceous-Palaeogene (K/Pg) boundary at Bidart (France) is preceded by a ∼0.5 m thick interval with geochemical and taphonomic vestiges of an ocean acidification event linked with Deccan volcanism. New planktic foraminifera census and morphometric data now confirm biotic stress conditions related to acidification in the Deccan benchmark interval. The absolute abundance data of larger (>150 μm) heavily calcified planktic morphogroups show fluctuating populations throughout zone CF1 (spanning the final ∼225 ky), lowest peaks within the Deccan benchmark, and a demographic collapse (>90%) at the K/Pg boundary. The analyzed species are generally reduced in size, with thinner test walls in this ∼0.5 m interval, indicating the likelihood of calcification stress as a contributor to the overall biotic stress. At the K/Pg boundary, maximum biotic stress is recorded in all the tested faunal proxies. A preliminary graphic correlation of zone CF1 at Bidart with the auxiliary GSSP at Elles (Tunisia) constrains the Deccan benchmark interval of high biotic stress to the final ∼58 ky of the late Maastrichtian, culminating in the K/Pg mass extinction. The volcanogenic Hg peaks coincident with faunal and taphonomic evidence of ocean acidification strengthen the Deccan-related ocean acidification hypothesis.