Advancements in robotic surgery: innovations, challenges and future prospects.

The use of robots has revolutionized healthcare, wherein further innovations have led to improved precision and accuracy. Conceived in the late 1960s, robot-assisted surgeries have evolved to become an integral part of various surgical specialties. Modern robotic surgical systems are equipped with highly dexterous arms and miniaturized instruments that reduce tremors and enable delicate maneuvers. Implementation of advanced materials and designs along with the integration of imaging and visualization technologies have enhanced surgical accuracy and made robots safer and more adaptable to various procedures. Further, the haptic feedback system allows surgeons to determine the consistency of the tissues they are operating upon, without physical contact, thereby preventing injuries due to the application of excess force. With the implementation of teleoperation, surgeons can now overcome geographical limitations and provide specialized healthcare remotely. The use of artificial intelligence (AI) and machine learning (ML) aids in surgical decision-making by improving the recognition of minute and complex anatomical structures. All these advancements have led to faster recovery and fewer complications in patients. However, the substantial cost of robotic systems, their maintenance, the size of the systems and proper surgeon training pose major challenges. Nevertheless, with future advancements such as AI-driven automation, nanorobots, microscopic incision surgeries, semi-automated telerobotic systems, and the impact of 5G connectivity on remote surgery, the growth curve of robotic surgery points to innovation and stands as a testament to the persistent pursuit of progress in healthcare.

Homeopathic Medicines Used as Prophylaxis in Kolkata during the COVID-19 Pandemic: A Community-Based, Cluster-Randomized Trial.

INTRODUCTION: There is some evidence that homeopathic treatment has been used successfully in previous epidemics, and currently some countries are testing homeoprophylaxis for the coronavirus disease 2019 (COVID-19) pandemic. There is a strong tradition of homeopathic treatment in India: therefore, we decided to compare three different homeopathic medicines against placebo in prevention of COVID-19 infections. METHODS: In this double-blind, cluster-randomized, placebo-controlled, four parallel arms, community-based, clinical trial, a 20,000-person sample of the population residing in Ward Number 57 of the Tangra area, Kolkata, was randomized in a 1:1:1:1 ratio of clusters to receive one of three homeopathic medicines (Bryonia alba 30cH, Gelsemium sempervirens 30cH, Phosphorus 30cH) or identical-looking placebo, for 3 (children) or 6 (adults) days. All the participants, who were aged 5 to 75 years, received ascorbic acid (vitamin C) tablets of 500 mg, once per day for 6 days. In addition, instructions on healthy diet and general hygienic measures, including hand washing, social distancing and proper use of mask and gloves, were given to all the participants. RESULTS: No new confirmed COVID-19 cases were diagnosed in the target population during the follow-up timeframe of 1 month-December 20, 2020 to January 19, 2021-thus making the trial inconclusive. The Phosphorus group had the least exposure to COVID-19 compared with the other groups. In comparison with placebo, the occurrence of unconfirmed COVID-19 cases was significantly less in the Phosphorus group (week 1: odds ratio [OR], 0.1; 95% confidence interval [CI], 0.06 to 0.16; week 2: OR, 0.004; 95% CI, 0.0002 to 0.06; week 3: OR, 0.007; 95% CI, 0.0004 to 0.11; week 4: OR, 0.009; 95% CI, 0.0006 to 0.14), but not in the Bryonia or Gelsemium groups. CONCLUSION: Overall, the trial was inconclusive. The possible effect exerted by Phosphorus necessitates further investigation. TRIAL REGISTRATION: CTRI/2020/11/029265.

Engineered swift equilibration for arbitrary geometries.

Engineered swift equilibration (ESE) is a class of driving protocols that enforce an equilibrium distribution with respect to external control parameters at the beginning and end of rapid state transformations of open, classical nonequilibrium systems. ESE protocols have previously been derived and experimentally realized for Brownian particles in simple, one-dimensional, time-varying trapping potentials; one recent study considered ESE in two-dimensional Euclidean configuration space. Here we extend the ESE framework to generic, overdamped Brownian systems in arbitrary curved configuration space and illustrate our results with specific examples not amenable to previous techniques. Our approach may be used to impose the necessary dynamics to control the full temporal configurational distribution in a wide variety of experimentally realizable settings.

Phase separation and large deviations of lattice active matter.

Off-lattice active Brownian particles form clusters and undergo phase separation even in the absence of attractions or velocity-alignment mechanisms. Arguments that explain this phenomenon appeal only to the ability of particles to move persistently in a direction that fluctuates, but existing lattice models of hard particles that account for this behavior do not exhibit phase separation. Here we present a lattice model of active matter that exhibits motility-induced phase separation in the absence of velocity alignment. Using direct and rare-event sampling of dynamical trajectories, we show that clustering and phase separation are accompanied by pronounced fluctuations of static and dynamic order parameters. This model provides a complement to off-lattice models for the study of motility-induced phase separation.

Statistical mechanics of transport processes in active fluids: Equations of hydrodynamics.

The equations of hydrodynamics including mass, linear momentum, angular momentum, and energy are derived by coarse-graining the microscopic equations of motion for systems consisting of rotary dumbbells driven by internal torques. In deriving the balance of linear momentum, we find that the symmetry of the stress tensor is broken due to the presence of non-zero torques on individual particles. The broken symmetry of the stress tensor induces internal spin in the fluid and leads us to consider the balance of internal angular momentum in addition to the usual moment of momentum. In the absence of spin, the moment of momentum is the same as the total angular momentum. In deriving the form of the balance of total angular momentum, we find the microscopic expressions for the couple stress tensor that drives the spin field. We show that the couple stress contains contributions from both intermolecular interactions and the active forces. The presence of spin leads to the idea of balance of moment of inertia due to the constant exchange of particles in a small neighborhood around a macroscopic point. We derive the associated balance of moment of inertia at the macroscale and identify the moment of inertia flux that induces its transport. Finally, we obtain the balances of total and internal energy of the active fluid and identify the sources of heat and heat fluxes in the system.

Transient Dissipation and Structural Costs of Physical Information Transduction.

A central result that arose in applying information theory to the stochastic thermodynamics of nonlinear dynamical systems is the information-processing second law (IPSL): the physical entropy of the Universe can decrease if compensated by the Shannon-Kolmogorov-Sinai entropy change of appropriate information-carrying degrees of freedom. In particular, the asymptotic-rate IPSL precisely delineates the thermodynamic functioning of autonomous Maxwellian demons and information engines. How do these systems begin to function as engines, Landauer erasers, and error correctors? We identify a minimal, and thus inescapable, transient dissipation of physical information processing, which is not captured by asymptotic rates, but is critical to adaptive thermodynamic processes such as those found in biological systems. A component of transient dissipation, we also identify an implementation-dependent cost that varies from one physical substrate to another for the same information processing task. Applying these results to producing structured patterns from a structureless information reservoir, we show that "retrodictive" generators achieve the minimal costs. The results establish the thermodynamic toll imposed by a physical system's structure as it comes to optimally transduce information.

Correlation-powered information engines and the thermodynamics of self-correction.

Information engines can use structured environments as a resource to generate work by randomizing ordered inputs and leveraging the increased Shannon entropy to transfer energy from a thermal reservoir to a work reservoir. We give a broadly applicable expression for the work production of an information engine, generally modeled as a memoryful channel that communicates inputs to outputs as it interacts with an evolving environment. The expression establishes that an information engine must have more than one memory state in order to leverage input environment correlations. To emphasize this functioning, we designed an information engine powered solely by temporal correlations and not by statistical biases, as employed by previous engines. Key to this is the engine's ability to synchronize-the engine automatically returns to a desired dynamical phase when thrown into an unwanted, dissipative phase by corruptions in the input-that is, by unanticipated environmental fluctuations. This self-correcting mechanism is robust up to a critical level of corruption, beyond which the system fails to act as an engine. We give explicit analytical expressions for both work and critical corruption level and summarize engine performance via a thermodynamic-function phase diagram over engine control parameters. The results reveal a thermodynamic mechanism based on nonergodicity that underlies error correction as it operates to support resilient engineered and biological systems.

Entropy Production and Fluctuation Theorems for Active Matter.

Active biological systems reside far from equilibrium, dissipating heat even in their steady state, thus requiring an extension of conventional equilibrium thermodynamics and statistical mechanics. In this Letter, we have extended the emerging framework of stochastic thermodynamics to active matter. In particular, for the active Ornstein-Uhlenbeck model, we have provided consistent definitions of thermodynamic quantities such as work, energy, heat, entropy, and entropy production at the level of single, stochastic trajectories and derived related fluctuation relations. We have developed a generalization of the Clausius inequality, which is valid even in the presence of the non-Hamiltonian dynamics underlying active matter systems. We have illustrated our results with explicit numerical studies.

Nonequilibrium work energy relation for non-Hamiltonian dynamics.

Recent years have witnessed major advances in our understanding of nonequilibrium processes. The Jarzynski equality, for example, provides a link between equilibrium free energy differences and finite-time nonequilibrium dynamics. We propose a generalization of this relation to non-Hamiltonian dynamics, relevant for active matter systems, continuous feedback, and computer simulation. Surprisingly, this relation allows us to calculate the free energy difference between the desired initial and final equilibrium states using arbitrary dynamics. As a practical matter, this dissociation between the dynamics and the initial and final states promises to facilitate a range of techniques for free energy estimation in a single universal expression.

Maxwell's refrigerator: an exactly solvable model.

We describe a simple and solvable model of a device that-like the "neat-fingered being" in Maxwell's famous thought experiment-transfers energy from a cold system to a hot system by rectifying thermal fluctuations. In order to accomplish this task, our device requires a memory register to which it can write information: the increase in the Shannon entropy of the memory compensates the decrease in the thermodynamic entropy arising from the flow of heat against a thermal gradient. We construct the nonequilibrium phase diagram for this device, and find that it can alternatively act as an eraser of information. We discuss our model in the context of the second law of thermodynamics.

Directed motion of periodically driven molecular motors: a graph-theoretical approach.

We propose a numerical algorithm for calculation of quantized directed motion of a stochastic system of interacting particles induced by periodic changes of control parameters on the graph of microstates. As a main application, we consider models of catenane molecular motors, which demonstrated the possibility of a similar control of directed motion of molecular components. We show that our algorithm allows one to calculate the motion of a system in the space of its microstates even when the considered phase space is combinatorially large (~1 × 10(6) microscopic states). Several general observations are made about the structure of the phase diagram of the systems studied, which may be used for rational design and efficient control of new generations of molecular motors.

Nonequilibrium heat capacity.

Development of steady state thermodynamics and statistical mechanics depends crucially on our ability to extend the notions of equilibrium thermodynamics to nonequilibrium steady states (NESS). The present paper considers the extension of heat capacity. A modified definition is proposed which continues to maintain the same relation to steady state Shannon entropy as in equilibrium, thus providing a thermodynamically consistent treatment of NESS heat capacity.

Hybrid models of molecular machines and the no-pumping theorem.

Synthetic nanoscale complexes capable of mechanical movement are often studied theoretically using discrete-state models that involve instantaneous transitions between metastable states. A number of general results have been derived within this framework, including a "no-pumping theorem" that restricts the possibility of generating directed motion by the periodic variation of external parameters. Motivated by recent experiments using time-resolved vibrational spectroscopy [Panman et al., Science 328, 1255 (2010)], we introduce a more detailed and realistic class of models in which transitions between metastable states occur by finite-time, diffusive processes rather than sudden jumps. We show that the no-pumping theorem remains valid within this framework.

Work and information processing in a solvable model of Maxwell's demon.

We describe a minimal model of an autonomous Maxwell demon, a device that delivers work by rectifying thermal fluctuations while simultaneously writing information to a memory register. We solve exactly for the steady-state behavior of our model, and we construct its phase diagram. We find that our device can also act as a "Landauer eraser", using externally supplied work to remove information from the memory register. By exposing an explicit, transparent mechanism of operation, our model offers a simple paradigm for investigating the thermodynamics of information processing by small systems.