New York University Abu Dhabi

We consider a pair $({\mathfrak {A}},{{\mathcal {B}}})$ where ${\mathfrak {A}}$ is an algebra over a base field ${\mathbb F}$, and ${{\mathcal {B}}}=\{e_{i}\}_{i \in I}$ a basis of ${\mathfrak {A}}$ satisfying the following property: for any $i,j \in I$ we have $e_ie_j \in {\mathbb {F}} e_k$ for some $k \in I$. We show that ${\mathfrak {A}}$ decomposes as ${\mathfrak {A}}={\mathfrak {s}} \oplus {\mathfrak {d}}$ where ${\mathfrak {s}}$ is a semisimple ideal of ${\mathfrak {A}}$, (a direct sum of simple ideals), and ${\mathfrak {d}}$ is the direct sum of non-simple indecomposable ideals of ${\mathfrak {A}}$. Moreover, this decomposition is unique. We show that the ideals ${\mathfrak {s}}$ and ${\mathfrak {d}}$ are characterized by a new linear property. An interpretation of this result in terms of graph theory is also provided.

Within the framework of differential Galois theory, we provide a solution to the factorization problem of piecewise constant matrix functions that arise from Fuchsian systems of differential equations. We calculate the partial indices of these matrix functions using the methods of the Riemann-Hilbert monodromy problem. This allows us to determine the explicit form of the factorization and understand the behavior of these matrix functions in relation to the underlying Fuchsian system of differential equations.

Worldwide technological advancements have introduced machines for various tasks, from simple spice mixing to heavy drilling. Many of these devices produce multifarious sounds which are often over tolerable limits, catering to noise pollution. This rising threat affects biodiversity and human health, with visible impacts like the disappearance of birds and health complications. Artificial Intelligence (AI) has been employed to detect sound pollutants, aiding in soundscape mapping for better urban planning and biodiversity protection. However, data scarcity remains a challenge for training machine learning models. We present SPolDB, a comprehensive sound pollution dataset with 54 classes from indoor and outdoor sources, featuring over 133,000 clips of varying lengths. The dataset was composed using recordings in the natural ambiance as well as sourcing audio clips of real-world scenarios. Baseline results are reported using an established handcrafted feature-based approach (Mel Frequency Cepstral Coefficient + Random Forest/Multi-layered Perceptron) and deep learning approach. The highest balanced accuracy (to mitigate bias introduced by class imbalance) of 82.9% was obtained on the test set ($20\%$ data for each class) leveraging a customized lightweight Convolutional Neural Network architecture named XZ-Net along with Mel Spectrogram.

This study advances microfluidic probe (MFP) technology through the development of a 3D-printed Microfluidic Mixing Probe (MMP), which integrates a built-in pre-mixer network of channels and features a lined array of paired injection and aspiration apertures. By combining the concepts of hydrodynamic flow confinements (HFCs) and “Christmas-tree” concentration gradient generation, the MMP can produce multiple concentration-varying flow dipoles, ranging from 0 to 100%, within an open microfluidic environment. This innovation overcomes previous limitations of MFPs, which only produced homogeneous bioreagents, by utilizing the pre-mixer to create distinct concentration of injected biochemicals. Experimental results with fluorescent dyes and the chemotherapeutic agent Cisplatin on MCF-7 cells confirmed the MMP’s ability to generate precise, discrete concentration gradients with the formed flow dipoles, consistent with numerical models. The MMP’s ability to localize drug exposure across cell cultures without cross-contamination opens new avenues for drug testing, personalized medicine, and molecular biology. It enables precise control over gradient delivery, dosage, and timing, which are key factors in enhancing drug evaluation processes.

In the gravitation n-body Problem, a homothetic orbit is a special solution of the Newton’s Equations of motion, in which each body moves along a straight line through the center of mass and forming at any time a central configuration. In 2020, Portaluri et al. proved that under a spectral gap condition on the limiting central configuration, known in literature as non-spiraling or [BS]-condition, the Morse index of an asymptotic colliding motion is finite. Later Ou et al. proved this result for other classes of unbounded motions, e.g. doubly asymptotic motions (e.g. doubly homothetic motions). In this paper, we prove that for a homothetic motion, irrespective of how large the index of the limiting central configuration and how large the energy level is, the following alternative holds: if the non-spiraling condition holds then the Morse index is 0 otherwise it is infinite.

Smart meters provide fine-grained power usage profiles of consumers to various utility providers, thus facilitating multiple grid functionalities such as load monitoring, real-time pricing, demand response, etc. However, information leakage from such usage profiles reveals consumers’ private day-to-day life patterns and their home presence/absence, as the state-of-the-art metering strategies lack adequate security and privacy measures. Since Smart grid communication infrastructure supports low bandwidth, it prohibits the usage of computation-intensive cryptographic solutions. Among different privacy-preserving smart meter streaming methods, data manipulation techniques can easily be implemented in smart meters and do not require installing any storage devices or alternative energy sources. For this purpose, Differential Privacy (DP) is widely adopted in the literature due to its solid mathematical foundation. However, the effect of such manipulations on the Real Time Pricing (RTP) control is worth exploring since pricing signals operate in a closed-loop between consumers and utilities. This brings up the privacy-utility trade-off problem between the user's achieved privacy and the performance of the pricing loop of Smart grids, an area where the characterization between privacy and pricing control performance is not yet established. We analytically highlight such privacy-utility trade-off in the closed-loop RTP systems in terms of achieved privacy and the overall generation scheduling errors. We utilize the notion of w -event privacy and present a real-time pricing aware differential privacy scheme that promises strong user privacy and guarantees pricing signal stabilization irrespective of the privacy level of the DP mechanism. Finally, we show the efficiency and robustness of our scheme by performing extensive experimental validation on MATLAB and, subsequently, on an in-house smart meter test bed.

The Drosophila visual system is a powerful model to study the development of neural circuits. Lobula columnar neurons-LCNs are visual output neurons that encode visual features relevant to natural behavior. There are ~20 classes of LCNs forming non-overlapping synaptic optic glomeruli in the brain. To address their origin, we used single-cell mRNA sequencing to define the transcriptome of LCN subtypes and identified lines that are expressed throughout their development. We show that LCNs originate from stem cells in four distinct brain regions exhibiting different modes of neurogenesis, including the ventral and dorsal tips of the outer proliferation center, the ventral superficial inner proliferation center and the central brain. We show that this convergence of similar neurons illustrates the complexity of generating neuronal diversity, and likely reflects the evolutionary origin of each subtype that detects a specific visual feature and might influence behaviors specific to each species.

Photomechanical crystals act as light‐driven material‐machines that can convert the energy carried by photons into kinetic energy via shape deformation or displacement, and this capability holds a paramount significance for the development of photoactuated devices. This transformation is usually attributed to anisotropic expansion or contraction of the unit cell engendered by light‐induced structural modifications that lead to accumulation and release of stress that generates a momentum, resulting in readily observable mechanical effects. Among the available photochemical processes, the photoinduced [2+2] and [4+4] reactions are known for their robustness, predictability, amenability to control with molecular and supramolecular engineering approaches, and efficiency that has already been elevated to a proof‐of‐concept smart devices based on organic crystals. This review article presents a summary of the recent research progress on photomechanical properties of organic and metal‐organic crystals where the mechanical effects are based on [2+2] and [4+4] cycloaddition reactions. It consolidates the current understating of the chemical strategies and structure–property correlations, and highlights the advantages and drawbacks of this class of adaptive crystals within the broader field of crystal adaptronics.

A bstract This paper presents measurements of top-antitop quark pair ( $t\overline{t}$ t t ¯ ) production in association with additional b -jets. The analysis utilises 140 fb − 1 of proton–proton collision data collected with the ATLAS detector at the Large Hadron Collider at a centre-of-mass energy of 13 TeV. Fiducial cross-sections are extracted in a final state featuring one electron and one muon, with at least three or four b -jets. Results are presented at the particle level for both integrated cross-sections and normalised differential cross-sections, as functions of global event properties, jet kinematics, and b -jet pair properties. Observable quantities characterising b -jets originating from the top quark decay and additional b -jets are also measured at the particle level, after correcting for detector effects. The measured integrated fiducial cross-sections are consistent with $t\overline{t}b\overline{b}$ t t ¯ b b ¯ predictions from various next-to-leading-order matrix element calculations matched to a parton shower within the uncertainties of the predictions. State-of-the-art theoretical predictions are compared with the differential measurements; none of them simultaneously describes all observables. Differences between any two predictions are smaller than the measurement uncertainties for most observables.

Pulsed dynamic nuclear polarization (DNP) enhances the nuclear magnetic resonance sensitivity by coherently transferring electron spin polarization to dipolar coupled nuclear spins. Recently, many new pulsed DNP techniques such as NOVEL, TOP, XiX, TPPM, and BEAM have been introduced. Despite significant progress, numerous challenges remain unsolved. The electron–electron (e–e) interactions in these sequences can severely disrupt the efficiency of electron–nuclear (e–n) polarization transfer. In order to tackle this issue, we propose the magic-NOVEL DNP method, utilizing Lee–Goldburg decoupling to counteract e–e coupling effects. Our theoretical analysis and quantum mechanical simulations reveal that magic-NOVEL significantly improves the transfer efficiency of DNP, even at shorter e–e distances. This method offers a new perspective for advancing pulsed DNP techniques in systems with dense electron spin baths. Furthermore, we demonstrate the effectiveness of phase-modulated Lee–Goldburg sequences in improving pulsed DNP transfer.

Research on health systems resilience during the Coronavirus Disease-2019 pandemic frequently used the Global Health Security Index (GHSI), a composite index scoring countries’ health security and related capabilities. Conflicting results raised questions regarding the validity of the GHSI as a reliable index. This study attempted to better characterize when and to what extent countries’ progress towards Global Health Security (GHS) augments health systems resilience. We used longitudinal data from 191 countries and a difference-in-difference (DiD) causal inference strategy to quantify the effect of countries’ GHS capacity as measured by the GHSI on their coverage rates for essential childhood immunizations, a previously established proxy for health systems resilience. Using a sliding scale of cutoff values with step increments of one, we divided countries into treatment and control groups and determined the lowest GHSI score at which a safeguarding effect was observed. All analyses were adjusted for potential confounders. World Bank governance indicators were employed for robustness tests. While countries with overall GHSI scores of 57 and above prevented declines in childhood immunization coverage rates from 2020–2022 (coef: 0.91; 95% CI: 0.41–1.41), this safeguarding effect was strongest in 2021 (coef: 1.23; 95% CI: 0.05–2.41). Coefficient sizes for overall GHSI scores were smaller compared to several GHSI sub-components, including countries’ environmental risks (coef: 4.28; 95% CI: 2.56–5.99) and emergency preparedness and response planning (coef: 1.82; 95% CI: 0.54–3.11). Our findings indicate that GHS was positively associated with health systems resilience during the pandemic (2020) and the following two years (2021–2022), that GHS may have had the most significant protective effects in 2021 as compared with 2020 and 2022, and that countries’ underlying characteristics, including governance quality, bolstered health systems resilience during the pandemic.

Urinary catheters serve as critical medical devices in clinical practice. However, the currently used urinary catheters lack efficient antibacterial and lubricating properties, often leading to discomfort with patients and even severe urinary infections. Herein, a new strategy of supramolecular assembly and disassembly of chitosan (Cs) is developed that enables efficient antibacterial lubricous and biodegradable hydrogel urinary catheters. Sodium lauryl sulfonate (SLS) is employed to induce supramolecular assembly on the surface of Cs film strips in an aqueous solution, resulting in the formation of hollow hydrogel catheters of Cs@SLS. Subsequent disassembly in a strong alkaline solution eliminates the SLS component, yielding neat Cs hydrogel catheters. The mechanical strength of these catheters reaches 16 MPa, exceeding that of similar devices made of plastics. The Cs hydrogel catheters are endowed with high antibacterial activity, capable of inhibiting the growth of Staphylococcus aureus (S. aureus), Escherichia coli (E. coli) and Proteus mirabilis(P. mirabilis) on its surface, while these bacteria are found to proliferate rapidly on plastic catheters within 24 h. They also demonstrate excellent lubricity, with a friction coefficient approaching zero, and thus about 13 times lower than that of plastic catheters. In vivo tests further confirm the biodegradability of the catheters, highlighting their strong potential for clinical applications.

(1) Background: Electrostatics plays a capital role in protein–protein and protein–ligand interactions. Implicit solvent models are widely used to describe electrostatics and complementarity at interfaces. Electrostatic complementarity at the interface is not trivial, involving surface potentials rather than the charges of surfacial contacting atoms. (2) Results: The program bluues_cplx, here used in conjunction with the software NanoShaper to compute molecular surfaces, has been used to compute the electrostatic properties of 756 protein–protein and 189 protein–ligand complexes along with the corresponding isolated molecules. (3) Methods: The software we make available here uses Generalized Born (GB) radii, computed by a molecular surface integral, to output several descriptors of electrostatics at protein (and in general, molecular) interfaces. We illustrate the usage of the software by analyzing a dataset of protein–protein and protein–ligand complexes, thus extending and refining previous analyses of electrostatic complementarity at protein interfaces. (4) Conclusions: The complete analysis of a molecular complex is performed in tens of seconds on a PC, and the results include the list of surfacial contacting atoms, their charges and Pearson correlation coefficient, the list of contacting surface points with the electrostatic potential (computed for the isolated molecules) and Pearson correlation coefficient, the electrostatic and hydrophobic free energy with different contributions for the isolated molecules, their complex and the difference for all terms. The software is readily usable for any molecular complex in solution.

Parasitic helminths are a major global health threat, infecting nearly one-fifth of the human population and causing significant losses in livestock and crops. Resistance to the few anthelmintic drugs is increasing. Here, we report a set of avocado fatty alcohols/acetates (AFAs) that exhibit nematocidal activity against four veterinary parasitic nematode species: Brugia pahangi, Teladorsagia circumcincta and Heligmosomoides polygyrus, as well as a multidrug resistant strain (UGA) of Haemonchus contortus. AFA shows significant efficacy in H. polygyrus infected mice. In C. elegans, AFA exposure affects all developmental stages, causing paralysis, impaired mitochondrial respiration, increased reactive oxygen species production and mitochondrial damage. In embryos, AFAs penetrate the eggshell and induce rapid developmental arrest. Genetic and biochemical tests reveal that AFAs inhibit POD-2, encoding an acetyl CoA carboxylase, the rate-limiting enzyme in lipid biosynthesis. These results uncover a new anthelmintic class affecting lipid metabolism.

A comprehensive investigation of the entanglement characteristics is carried out on tripartite spin-1/2 systems, examining prototypical tripartite states, the thermal Heisenberg model, and the transverse field Ising model. The entanglement is computed using the Rényi relative entropy. In the traditional Rényi relative entropy, the generalization parameter $\alpha$ can take values only in the range $0 \le \alpha \le 2$ due to the requirements of joint convexity of the measure. To use the Rényi relative entropy over a wider range of $\alpha$, we use the sandwiched form which is jointly convex in the regime $0.5 \le \alpha \le \infty$. In prototypical tripartite states, we find that GHZ states are monogamous, but surprisingly so are W states. On the other hand, star states exhibit polygamy, due to the higher level of purity of the bipartite subsystems. For spin models, we study the dependence of entanglement on various parameters such as temperature, spin-spin interaction, and anisotropy, and identify regions where entanglement is the largest. The Rényi parameter $\alpha$ scales the amount of entanglement in the system. The entanglement measure based on the traditional and the sandwiched Rényi relative entropies obey the Araki-Lieb-Thirring inequality. In the Heisenberg models, namely the XYZ, XXZ, and XY models, the system is always monogamous. However, in the transverse field Ising model, the state is initially polygamous and becomes monogamous with temperature and coupling.

This paper proposes a motion-artifact-tolerant multi-channel biopotential-recording IC. A simple counter-based digital-assisted loop (DAL), implemented entirely with digital circuits, is proposed to track motion artifacts. The DAL effectively tracks motion artifacts without signal loss for amplitudes up to 120 mV with a 10 Hz bandwidth and can accommodate even larger motion artifacts, up to 240 mV, with a 5 Hz bandwidth, demonstrating its robustness across various conditions and motion artifact ranges. The IC includes four analog front-end (AFE) channels, and they share the following programmable gain amplifier (PGA) and analog-to-digital converter (ADC) in a time-multiplexed manner. It supports a programmable gain from 20 dB to 54 dB. Furthermore, the chopper with an analog DC-servo loop (DSL) is added to cancel out electrode DC offsets (EDO) and achieve a low noise level by removing the 1/f noise. The proposed IC fabricated in a 0.18-μm CMOS technology process achieves an input-referred noise (IRN) of 0.71 μVrms over a bandwidth of 0.5 to 500 Hz and a signal-to-noise-and-distortion ratio (SNDR) of 63.34 dB. It consumes 5.74 μW of power and occupies an area of 0.40 mm ² per channel. As a result, the proposed IC can record various biopotential signals thanks to its artifact-tolerant and low-noise characteristics.

This paper presents a 72-channel resistive-sensor interface integrated circuit (IC). The proposed IC consists of 8 sensor oscillator units and a reference clock generator. The sensor oscillator (S-OSC) units generate pulses with pulse widths dependent on the sensor input values, and the pulses are oversampled by the reference clock using frequency dividers. The time-domain signals are fed to the time-to-digital converters (TDCs) and converted to digital values. Each S-OSC unit is time-multiplexed to measure the resistance values from 9 sensors. Multiple phases from a highly energy-efficient phase-locked loop (PLL) are used for the TDCs, resulting in a signal-to-quantization-noise ratio (SQNR) that exceeds the intrinsic signal-to-noise ratio (SNR) of the sensor oscillators. This results in an effective number of bits (ENOB) of 9.3 bits at 310 pJ per channel. The maximum ENOB that can be achieved with a division ratio (N) of 256 is 14.1 bits and can be adjusted by changing N. Using this time-domain interface approach, the IC converts the sensor resistances directly into time, extending its measurement capabilities to 10 MΩ. The proposed IC, designed and fabricated in a 180-nm CMOS process with an active area of 0.015 mm², consumes only 15.07 μW per channel, resulting in a channel-specific Walden figure of merit (FoM) of 0.48 pJ per conversion step. In addition, by tuning N, the IC achieves an outstanding Schreier FoM of 159.8 dB in high-resolution scenarios.</p

This paper presents a new potentiostat circuit architecture for interfaces with amperometric electrochemical biosensors. The proposed architecture, which is based on a digital low-dropout regulator (DLDO) structure, successfully eliminates the need for transimpedance amplifier (TIA), control amplifier, and other passive elements unlike other typical potentiostat topologies. It can regulate the required electrode voltages and measure the sensor currents ( I_SENSE ) at the same time by using a simple implementation with clocked comparators, digital loop filters, and current-steering DACs. Three different configurations of the proposed potentiostat are discussed including single-side regulated (SSR) potentiostat, dual-side regulated (DSR) potentiostat, and differential sensing DSR potentiostat with a background working electrode. These proposed potentiostats were designed and fabricated in a 180 nm CMOS process, occupying an active silicon areas of 0.0645 mm ² , 0.1653 mm ² , and 0.266 mm ² , respectively. Validation results demonstrate that the proposed potentiostats operate on a wide sampling frequency range from 100 Hz to 100 MHz and supply voltage range from 1 V to 1.8 V. The proposed DSR potentiostat achieves a minimal power consumption of 3.7 nW over the entire dynamic range of 129.5 dB.