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Randomly barcoded transposon mutant libraries are powerful tools for studying gene function and organization, assessing gene essentiality and pathways, discovering potential therapeutic targets, and understanding the physiology of gut bacteria and their interactions with the host. However, construction of high-quality libraries with uniform representation can be challenging. In this review, we survey various strategies for barcoded library construction, including transposition systems, methods of transposon delivery, optimal library size, and transconjugant selection schemes. We discuss the advantages and limitations of each approach, as well as factors to consider when selecting a strategy. In addition, we highlight experimental and computational advances in arraying condensed libraries from mutant pools. We focus on examples of successful library construction in gut bacteria and their application to gene function studies and drug discovery. Given the need for understanding gene function and organization in gut bacteria, we provide a comprehensive guide for researchers to construct randomly barcoded transposon mutant libraries.

Sensor data and agro-hydrological modeling have been combined to improve irrigation management. Crop water models simulating crop growth and production in response to the soil-water environment need to be parsimonious in terms of structure, inputs and parameters to be applied in data scarce regions. Irrigation management using soil moisture sensors requires them to be site-calibrated, low-cost, and maintainable. Therefore, there is a need for parsimonious crop modeling combined with low-cost soil moisture sensing without losing predictive capability. This study calibrated the low-cost capacitance-based Spectrum Inc. SM100 soil moisture sensor using multiple least squares and machine learning models, with both laboratory and field data. The best calibration technique, field-based piece-wise linear regression (calibration r2 = 0.76, RMSE = 3.13 %, validation r2 = 0.67, RMSE = 4.57 %), was used to study the effect of sensor calibration on the performance of the FAO AquaCrop Open Source (AquaCrop-OS) model by calibrating its soil hydraulic parameters. This approach was tested during the wheat cropping season in 2018, in Kanpur (India), in the Indo-Gangetic plains, resulting in some best practices regarding sensor calibration being recommended. The soil moisture sensor was calibrated best in field conditions against a secondary standard sensor (UGT GmbH. SMT100) taken as a reference (r2 = 0.67, RMSE = 4.57 %), followed by laboratory calibration against gravimetric soil moisture using the dry-down (r2 = 0.66, RMSE = 5.26 %) and wet-up curves respectively (r2 = 0.62, RMSE = 6.29 %). Moreover, model overfitting with machine learning algorithms led to poor field validation performance. The soil moisture simulation of AquaCrop-OS improved significantly by incorporating raw reference sensor and calibrated low-cost sensor data. There were non-significant impacts on biomass simulation, but water productivity improved sign, Water Resources

Searches for dark matter with liquid xenon time projection chamber experiments have traditionally focused on the region of the parameter space that is characteristic of weakly interacting massive particles, ranging from a few GeV/$c^2$ to a few TeV/$c^2$. Models of dark matter with a mass much heavier than this are well motivated by early production mechanisms different from the standard thermal freeze-out, but they have generally been less explored experimentally. In this work, we present a re-analysis of the first science run (SR1) of the LZ experiment, with an exposure of $0.9$ tonne$\times$year, to search for ultraheavy particle dark matter. The signal topology consists of multiple energy deposits in the active region of the detector forming a straight line, from which the velocity of the incoming particle can be reconstructed on an event-by-event basis. Zero events with this topology were observed after applying the data selection calibrated on a simulated sample of signal-like events. New experimental constraints are derived, which rule out previously unexplored regions of the dark matter parameter space of spin-independent interactions beyond a mass of 10$^{17}$ GeV/$c^2$., Comment: 9 pages, 7 figures

Studies of mast cell biology are dependent on relevant and validated in vitro models. Here, we present detailed information concerning the phenotype of both freshly isolated human skin mast cells (MCs) and of in vitro cultures of these cells that were obtained by analyzing their total transcriptome. Transcript levels of MC-related granule proteins and transcription factors were found to be remarkably stable over a 3-week culture period. Relatively modest changes were also seen for important cell surface receptors including the high-affinity receptor for IgE, FCER1A, the low-affinity receptor for IgG, FCGR2A, and the receptor for stem cell factor, KIT. FCGR2A was the only Fc receptor for IgG expressed by these cells. The IgE receptor increased by 2-5-fold and an approximately 10-fold reduction in the expression of FCGR2A was observed most likely due to the cytokines, SCF and IL-4, used for expanding the cells. Comparisons of the present transcriptome against previously reported transcriptomes of mouse peritoneal MCs and mouse bone marrow-derived MCs (BMMCs) revealed both similarities and major differences. Strikingly, cathepsin G was the most highly expressed granule protease in human skin MCs, in contrast to the almost total absence of this protease in both mouse MCs. Transcript levels for the majority of cell surface receptors were also very low compared to the granule proteases in both mouse and human MCs, with a difference of almost two orders of magnitude. An almost total absence of T-cell granzymes was observed in human skin MCs, indicating that granzymes have no or only a minor role in human MC biology. Ex vivo skin MCs expressed high levels of selective immediate early genes and transcripts of heat shock proteins. In validation experiments, we determined that this expression was an inherent property of the cells and not the result of the isolation process. Three to four weeks in culture results in an induction of cell growth-related genes accompanying their e, De två sista författarna delar sistaförfattarskapet.

Due to the pandemic situation, there has been an increase in the need for health and immunity to recover from diseases such as COVID-19. Chickpea husk, rice bran, rice bran (broken rice) by-products are processed using different cooking methods. soaking, boiling, cooking and natural air drying. Promote health and wellness. Although the detox industry is growing, there is little clinical evidence to support the use of these foods, what they involve, whether they are effective and whether they present any dangers. Although the detox industry is booming, there is very little clinical evidence to support the use of theses diets Some clinical studies show that commercial detox diets can improve liver detoxification and remove POPs from the body; however, these studies are affected by methodological flaws and small samples. The general acceptance of these non-standard conditions determined by sensory tests during the storage period is satisfactory. without compromising the quality and improving the quality of food products for consumers. According to the estimate data it can be concluded that the selected byproduct can be utilized as significant plant-based source to formulate value-added functional product without affecting it sensory quality and to enhance nutritional status of consumers.

Dactylogyrus labei is a dactylogyrid monogenean parasite originally described by Musselius and Gusev (1976) from Labeo rohita (Hamilton, 1822) (Teleostei: Cyprinidae) in two alternative forms: a typical from Lucknow, north India and an atypical from Kalyani, east India. Fresh specimens of D. labei were collected from Mizoram in northeast India, and examined morphologically using high-resolution digital image processing and analysis. The recovered monogeneans most closely resembled the atypical form of D. labei, with only minor differences, indicating conspecificity. The atypical form of D. labei is distinguished from other species of the genus by the following combination of characters: the dorsal bar wing-shaped, with a fine membrane on the anterior margin and a fenestration in the middle; the ventral bar casing nail-shaped with two small antero-lateral processes (3-rayed); the male copulatory tube loosely S-shaped, slender, with an inflated initial part; the accessory piece proximally tubular, distally a complex of multi-layered sheath guiding the copulatory tube, and the vagina tubular, with one small loop and vaginal pore surrounded with a flap-like structure. This study expands the geographical distribution of D. labei while improving its morphological descriptions.

The Artemis exploration zone is a topographically complex impact-cratered terrain. Steep undulating slopes pose a challenge for walking extravehicular activities (EVAs) anticipated for the Artemis III and subsequent missions. Using 5 m/pixel Lunar Orbiter Laser Altimeter (LOLA) measurements of the surface, an automated Python pipeline was developed to calculate traverse paths that minimize metabolic workload. The tool combines a Monte Carlo method with a minimum-cost path algorithm that assesses cumulative slope over distances between a lander and stations, as well as between stations. To illustrate the functionality of the tool, optimized paths to permanently shadowed regions (PSRs) are calculated around potential landing sites 001, nearby location 001(6), and 004, all within the Artemis III ‘Connecting Ridge’ candidate landing region. We identified 521 PSRs and computed (1) traverse paths to accessible PSRs within 2 km of the landing sites, and (2) optimized descents from host crater rims into each PSR. Slopes are limited to 15° and previously identified boulders are avoided. Surface temperature, astronaut body illumination, regolith bearing capacity, and astronaut-to-lander direct view are simultaneously evaluated. Travel times are estimated using Apollo 12 and 14 walking EVA data. A total of 20 and 19 PSRs are accessible from sites 001 and 001(6), respectively, four of which maintain slopes <10°. Site 004 provides access to 11 PSRs, albeit with higher EVA workloads. From the crater rims, 94 % of PSRs can be accessed. All round-trip traverses from potential landing sites can be performed in under 2 h with a constant walk. Traverses and descents to PSRs are compiled in an atlas to support Artemis mission planning.

The oxidative potential (OP) of particulate matter (PM) is a major driver of PM-associated health effects. In India, the emission sources defining PM-OP, and their local/regional nature, are yet to be established. Here, to address this gap we determine the geographical origin, sources of PM, and its OP at five Indo-Gangetic Plain sites inside and outside Delhi. Our findings reveal that although uniformly high PM concentrations are recorded across the entire region, local emission sources and formation processes dominate PM pollution. Specifically, ammonium chloride, and organic aerosols (OA) from traffic exhaust, residential heating, and oxidation of unsaturated vapors from fossil fuels are the dominant PM sources inside Delhi. Ammonium sulfate and nitrate, and secondary OA from biomass burning vapors, are produced outside Delhi. Nevertheless, PM-OP is overwhelmingly driven by OA from incomplete combustion of biomass and fossil fuels, including traffic. These findings suggest that addressing local inefficient combustion processes can effectively mitigate PM health exposure in northern India.

Controlled ROS generation contributes to defense systemic signaling and stress acclimation in plants. Recently, Fichman et al. reported that HPCA1 senses HO and controls the production of ROS by RBOHD, then regulates downstream Ca signaling cascades and thus mediates biotic and abiotic stress resilience in plants. Further, a better understanding of the mechanism of membrane depolarization signaling is needed as it does not involve HPCA1 in response to high light stress. But there are some questions regarding the utter involvement of HPCA1 in sensing of cellular HO and subsequent cell-to-cell systemic signaling during stress conditions.

Diabetes, a persistent metabolic challenge affecting various organs,are of three primary types—Type 1, Type 2, and Gestational—stemming from intricate interplays of genetics and environment. On a global scale, 537 million adults grapple with diabetes, with India experiencing a growing burden. The vital role of insulin in glucose regulation involves a complex biosynthesis process. Economic hurdles, compounded by soaring insulin prices, call for policy interventions to ensure accessible healthcare. Diverse insulin types cater to distinct patient needs, while biosimilars, like the FDA-approved Semglee, offer affordability. Economic analyses underscore the advantages of biosimilars, highlighting the dynamic landscape of diabetes management and treatment costs.

Diabetes, a persistent metabolic challenge affecting various organs,are of three primary types—Type 1, Type 2, and Gestational—stemming from intricate interplays of genetics and environment. On a global scale, 537 million adults grapple with diabetes, with India experiencing a growing burden. The vital role of insulin in glucose regulation involves a complex biosynthesis process. Economic hurdles, compounded by soaring insulin prices, call for policy interventions to ensure accessible healthcare. Diverse insulin types cater to distinct patient needs, while biosimilars, like the FDA-approved Semglee, offer affordability. Economic analyses underscore the advantages of biosimilars, highlighting the dynamic landscape of diabetes management and treatment costs.

Iron line spectroscopy has been one of the leading methods not only for measuring the spins of accreting black holes but also for testing fundamental physics. Basing on such a method, we present an analysis of a dataset observed simultaneously by NuSTAR and NICER for the black hole binary candidate MAXI J1803-298, which shows prominent relativistic reflection features. Various relxill_nk flavors are utilized to test the Kerr black hole hypothesis. The results obtained from our analysis provide stringent constraints on Johannsen deformation parameter $\alpha_{13}$ with the highest precise to date, namely $\alpha_{13}=0.023^{+0.071}_{-0.038}$ from relxillD_nk and $\alpha_{13}=0.006^{+0.045}_{-0.022}$ from relxillion_nk respectively in 3-$\sigma$ credible lever, where Johannsen metric reduces to Kerr metric when $\alpha_{13}$ vanishes. Furthermore, we investigate the best model-fit results using Akaike Information Criterion and assess its systematic uncertainties., Comment: Accepted by ApJ

This paper introduces a novel sector-based methodology for star-galaxy classification, leveraging the latest Sloan Digital Sky Survey data (SDSS-DR18). By strategically segmenting the sky into sectors aligned with SDSS observational patterns and employing a dedicated convolutional neural network (CNN), we achieve state-of-the-art performance for star galaxy classification. Our preliminary results demonstrate a promising pathway for efficient and precise astronomical analysis, especially in real-time observational settings.

Differentially rotating stars and planets transport angular momentum internally due to turbulence at rates that have long been a challenge to predict reliably. We develop a self-consistent saturation theory, using a statistical closure approximation, for hydrodynamic turbulence driven by the axisymmetric Goldreich--Schubert--Fricke (GSF) instability at the stellar equator with radial differential rotation. This instability arises when fast thermal diffusion eliminates the stabilizing effects of buoyancy forces in a system where a stabilizing entropy gradient dominates over the destabilizing angular momentum gradient. Our turbulence closure invokes a dominant three-wave coupling between pairs of linearly unstable eigenmodes and a near-zero frequency, viscously damped eigenmode that features latitudinal jets. We derive turbulent transport rates of momentum and heat, and provide them in analytic forms. Such formulae, free of tunable model parameters, are tested against direct numerical simulations; the comparison shows good agreement. They improve upon prior quasi-linear or ``parasitic saturation" models containing a free parameter. Given model correspondences, we also extend this theory to heat and compositional transport for axisymmetric thermohaline instability-driven turbulence in certain regimes., Comment: Accepted for publication in ApJ

Searches for dark matter with liquid xenon time projection chamber experiments have traditionally focused on the region of the parameter space that is characteristic of weakly interacting massive particles, ranging from a few GeV/$c^2$ to a few TeV/$c^2$. Models of dark matter with a mass much heavier than this are well motivated by early production mechanisms different from the standard thermal freeze-out, but they have generally been less explored experimentally. In this work, we present a re-analysis of the first science run (SR1) of the LZ experiment, with an exposure of $0.9$ tonne$\times$year, to search for ultraheavy particle dark matter. The signal topology consists of multiple energy deposits in the active region of the detector forming a straight line, from which the velocity of the incoming particle can be reconstructed on an event-by-event basis. Zero events with this topology were observed after applying the data selection calibrated on a simulated sample of signal-like events. New experimental constraints are derived, which rule out previously unexplored regions of the dark matter parameter space of spin-independent interactions beyond a mass of 10$^{17}$ GeV/$c^2$., Comment: 9 pages, 7 figures

The Mg II k \& h line intensity ratios can be used to probe the characteristics of the plasma in the solar atmosphere. In this study, using the observations recorded by the Interface Region Imaging Spectrometer (IRIS), we study the variation of the Mg II k \& h intensity ratio for three flares belonging to X-class, M-class, and C-class, throughout their evolution. We also study the k-to-h intensity ratio as a function of magnetic flux density obtained from the line-of-sight magnetograms recorded by the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO). Our results reveal that while the intensity ratios are independent of magnetic flux density, they show significant changes during the evolution of the C-class and M-class flares. The intensity ratios start to increase at the start of the flare and peak during the impulsive phase before the flare peak and decrease rapidly thereafter. The values of the ratios fall even below the pre-flare level during the peak and decline phases of the flare. These results are important in light of the heating and cooling of localized plasma and provide further constraints on the understanding of flare physics., Comment: Accepted for publication in ApJ

We report the first experimental detection of a reflected Alfv\'en wave from an Alfv\'en-speed gradient under conditions similar to those in coronal holes. The experiments were conducted in the Large Plasma Device at the University of California, Los Angeles. We present the experimentally measured dependence of the coefficient of reflection versus the wave inhomogeneity parameter, i.e., the ratio of the wave length of the incident wave to the length scale of the gradient. Two-fluid simulations using the Gkeyll code qualitatively agree with and support the experimental findings. Our experimental results support models of wave heating that rely on wave reflection at low heights from a smooth Alfv\'en-speed gradient to drive turbulence.

In a previous paper, we reported evidence for quasi-periodicities in the \textsl{TESS} light curves of BL Lacerate and two other blazars found serendipitously in the SDSS AGN catalog. In this work, we find tentative evidence for quasi-periodic features in the \textsl{TESS} observations of five sources in the fourth catalog of the Fermi--LAT (4FGL) sources: J090453.4$-$573503, J2345$-$1555, B0422+004, J002159.2$-$514028, and B0537$-$441. We analysed the \textsl{TESS} light curves of these blazars that we extracted using a customized approach. The quasi-periodic oscillations (QPOs) are searched for using two timing analysis techniques: generalized Lomb-Scargle periodogram and weighted wavelet Z-transform. Their apparent periods lie in the range of 2.8--6.5 days and have at least 3$\sigma$ significance in both of these methods. QPOs at such timescales can originate from the kink instability model which relates the quasi-periodic feature with the growth of kinks in the magnetized relativistic jets. We performed MCMC simulations to obtain the posterior distribution of parameters associated with this model and found the kink period consistent with previous studies., Comment: 12 pages, 4 figures. Accepted for publication in MNRAS main journal

Ebstein's abnormality is an intricate congenital deformity of the tricuspid valve. Newborn and infant health is an often-discussed topic. The condition exhibits a wide range of severity and medical characteristics, necessitating tailored treatment for each patient. This article provides an account of the inherent characteristics and progression of Ebstein's abnormalities in children and adolescents. This includes the indications and manifestations that appear at the time of diagnosis. This section describes the contemporary methods used to categorize Ebstein's abnormalities. We provide diagnostic techniques for assessing the severity of illnesses that have the potential to enhance decision-making in surgical procedures. Furthermore, we explore several surgical alternatives for neonates in severe conditions, as well as many surgical procedures following the operation. In order to effectively enhance both the duration and quality of life for this complex and diverse group of patients, it is essential to possess sufficient information and comprehension of the aforementioned factors. Effective management requires a nuanced and personalized approach. It is crucial to have an accurate understanding of the many anatomical and hemodynamic factors, related abnormalities, and available treatment choices.

Ebstein's abnormality is an intricate congenital deformity of the tricuspid valve. Newborn and infant health is an often-discussed topic. The condition exhibits a wide range of severity and medical characteristics, necessitating tailored treatment for each patient. This article provides an account of the inherent characteristics and progression of Ebstein's abnormalities in children and adolescents. This includes the indications and manifestations that appear at the time of diagnosis. This section describes the contemporary methods used to categorize Ebstein's abnormalities. We provide diagnostic techniques for assessing the severity of illnesses that have the potential to enhance decision-making in surgical procedures. Furthermore, we explore several surgical alternatives for neonates in severe conditions, as well as many surgical procedures following the operation. In order to effectively enhance both the duration and quality of life for this complex and diverse group of patients, it is essential to possess sufficient information and comprehension of the aforementioned factors. Effective management requires a nuanced and personalized approach. It is crucial to have an accurate understanding of the many anatomical and hemodynamic factors, related abnormalities, and available treatment choices.

Ebstein's abnormality is an intricate congenital deformity of the tricuspid valve. Newborn and infant health is an often-discussed topic. The condition exhibits a wide range of severity and medical characteristics, necessitating tailored treatment for each patient. This article provides an account of the inherent characteristics and progression of Ebstein's abnormalities in children and adolescents. This includes the indications and manifestations that appear at the time of diagnosis. This section describes the contemporary methods used to categorize Ebstein's abnormalities. We provide diagnostic techniques for assessing the severity of illnesses that have the potential to enhance decision-making in surgical procedures. Furthermore, we explore several surgical alternatives for neonates in severe conditions, as well as many surgical procedures following the operation. In order to effectively enhance both the duration and quality of life for this complex and diverse group of patients, it is essential to possess sufficient information and comprehension of the aforementioned factors. Effective management requires a nuanced and personalized approach. It is crucial to have an accurate understanding of the many anatomical and hemodynamic factors, related abnormalities, and available treatment choices.

Statistically, the cool loop's footpoints are diagnosed using Si~{\sc iv} resonance lines observations provided by Interface Region Imaging Spectrograph (IRIS). The intensity and Full Width at Half Maximum (FWHM) of the loop's footpoints in $\beta${--}$\gamma$ active regions (ARs) are higher than the corresponding parameters of footpoints in $\beta$ ARs. However, the Doppler velocity of footpoints in both ARs are almost similar to each other. The intensities of footpoints from $\beta${--}$\gamma$ AR is found to be around 9 times that of $\beta$ AR when both ARs are observed nearly at the same time. The same intensity difference reduces nearly to half (4 times) when considering all ARs observed over 9 years. Hence, the instrument degradation affects comparative intensity analysis. We find that Doppler velocity and FWHM are well-correlated while peak intensity is neither correlated with Doppler velocity nor FWHM. The loop's footpoints in $\beta$-$\gamma$ ARs have around four times more complex Si~{\sc iv} spectral profiles than that of $\beta$ ARs. The intensity ratios (Si~{\sc iv} 1393.78~{\AA}/1402.77~{\AA}) of the significant locations of footpoints differ, marginally, (i.e., either less than 1.9 or greater than 2.10) from the theoretical ratio of 2, i.e., 52\% (55\%) locations in $\beta$ ($\beta${--}$\gamma$) ARs significantly deviate from 2. Hence, we say that more than half of the footpoint locations are either affected by the opacity or resonance scattering. We conclude that the nature and attributes of the footpoints of the cool loops in $\beta$-$\gamma$ ARs are significantly different from those in $\beta$ ARs., Comment: 17 pages, 12 Figures (11 main + 1 appendix), Accepted for Publication in MNRAS

General Relativity predicts the spacetime metric around an astrophysical black hole to be described by Kerr solution which is a massive rotating black hole without any residual charge. In a previous paper, we analyzed the NuSTAR observations of six X-ray binaries to obtain constraints on deformation parameter $\alpha_{13}$ using a state-of-the-art relativistic model. In this work, we continue analyzing NuSTAR observations of four more X-ray Binaries; two of which are X-ray Transients very close to the supermassive black hole at the center of our galaxy. The other two sources have complicated absorption which is accounted by time-resolved and flux-resolved spectroscopy. The constraints obtained are consistent with the Kerr hypothesis and are comparable with those obtained in previous studies and those from gravitational events., Comment: 14 pages, 10 figures

Detection of redshifted \ion{H}{i} 21-cm emission is a potential probe for investigating the Universe's first billion years. However, given the significantly brighter foreground, detecting 21-cm is observationally difficult. The Earth's ionosphere considerably distorts the signal at low frequencies by introducing directional-dependent effects. Here, for the first time, we report the use of Artificial Neural Networks (ANNs) to extract the global 21cm signal characteristics from the composite all-sky averaged signal, including foreground and ionospheric effects such as refraction, absorption, and thermal emission from the ionosphere's F and D-layers. We assume a 'perfect' instrument and neglect instrumental calibration and beam effects. To model the ionospheric effect, we considered the static and time-varying ionospheric conditions for the mid-latitude region where LOFAR is situated. In this work, we trained the ANN model for various situations using a synthetic set of the global 21cm signals created by altering its parameter space based on the "$\rm \tanh$" parameterized model and the Accelerated Reionization Era Simulations (ARES) algorithm. The obtained result shows that the ANN model can extract the global signal parameters with an accuracy of $\ge 96 \% $ in the final study when we include foreground and ionospheric effects. On the other hand, a similar ANN model can extract the signal parameters from the final prediction dataset with an accuracy ranging from $97 \%$ to $98 \%$ when considering more realistic sets of the global 21cm signals based on physical models., Comment: 21 pages, 19 figures, Published in MNRAS

Percy Bysshe Shelley’s exploration of love spans his poetic works, revealing a profound evolution from personal passion to a universal force of redemption and liberation. This paper delves into Shelley’s philosophical journey as depicted in his major works, examining the themes of bondage and freedom in “The Triumph of Life” alongside the transformative power of love in “Prometheus Unbound.” Shelley’s examination of the Promethean legend serves as a backdrop for his exploration of love’s evolving nature. From its initial portrayal as a personal deity in “Epipsychidion” to its broader significance as a universal principle in “Adonais,” love emerges as a redemptive force, transcending individual desires to encompass humanity’s collective aspirations. In “Prometheus Unbound,” Shelley presents love as a heroic vision of rebellion against tyranny, symbolizing wisdom, justice, and peace in the face of oppression. Through meticulous analysis of symbolism and action, the paper illuminates Shelley’s profound insight into the transformative potential of love, culminating in the triumph of love over adversity. “The Triumph of Life” offers a more symbolic view of love, contrasting earthly passion with a spiritual love that grants liberation from the limitations of the material world. Shelley suggests that love, in its purest form, holds the key to individual and societal transformation, offering solace in suffering and rebellion against oppression. In conclusion, Shelley’s concept of love evolves from personal indulgence to mature, symbolic representation, emphasizing its role in individual salvation and societal renewal. The enduring message of Shelley’s works underscores the transformative power of love as a force for redemption and liberation.

Percy Bysshe Shelley’s exploration of love spans his poetic works, revealing a profound evolution from personal passion to a universal force of redemption and liberation. This paper delves into Shelley’s philosophical journey as depicted in his major works, examining the themes of bondage and freedom in “The Triumph of Life” alongside the transformative power of love in “Prometheus Unbound.” Shelley’s examination of the Promethean legend serves as a backdrop for his exploration of love’s evolving nature. From its initial portrayal as a personal deity in “Epipsychidion” to its broader significance as a universal principle in “Adonais,” love emerges as a redemptive force, transcending individual desires to encompass humanity’s collective aspirations. In “Prometheus Unbound,” Shelley presents love as a heroic vision of rebellion against tyranny, symbolizing wisdom, justice, and peace in the face of oppression. Through meticulous analysis of symbolism and action, the paper illuminates Shelley’s profound insight into the transformative potential of love, culminating in the triumph of love over adversity. “The Triumph of Life” offers a more symbolic view of love, contrasting earthly passion with a spiritual love that grants liberation from the limitations of the material world. Shelley suggests that love, in its purest form, holds the key to individual and societal transformation, offering solace in suffering and rebellion against oppression. In conclusion, Shelley’s concept of love evolves from personal indulgence to mature, symbolic representation, emphasizing its role in individual salvation and societal renewal. The enduring message of Shelley’s works underscores the transformative power of love as a force for redemption and liberation.

Diabetes, a persistent metabolic challenge affecting various organs,are of three primary types—Type 1, Type 2, and Gestational—stemming from intricate interplays of genetics and environment. On a global scale, 537 million adults grapple with diabetes, with India experiencing a growing burden. The vital role of insulin in glucose regulation involves a complex biosynthesis process. Economic hurdles, compounded by soaring insulin prices, call for policy interventions to ensure accessible healthcare. Diverse insulin types cater to distinct patient needs, while biosimilars, like the FDA-approved Semglee, offer affordability. Economic analyses underscore the advantages of biosimilars, highlighting the dynamic landscape of diabetes management and treatment costs.

Karpatriji, who authored Marxvad Aur Ramrajya, adheres to the ancient Indian political philosophy tradition. It includes governance as an annealed part of the troika, philosophy, politics, and economics. Genesis of Hindu political philosophy owes to Kautilyaand Shukracharya to show the Indian integration of the milieu of the three disciplines in unison, i.e. Neeti-shastra. Chanakya, also known as Kautilya, offers a doctrine of the mandala, known as spheres of influence, in foreign policy; mandala philosophy finds resonance and tacit presence in the book Marxvad Aur Ramrajya amongst discussed subject matter. Karpatriji illustrated the embeddedness of dharmic phenomena1 in the governance framework of Ramrajya and presents a thesis on Dharmic perspectives in the post-modern world. The book is a magnum opus on a comparative view of Marxism and Dharmic proposition on governance, having veracity of themes and topics discussed in the work. It details Marxism not as a standalone Vad or alternative view on social theory, but instead depicts Marxism founded on a well-developed foundation of Western philosophy, classical Greek philosophy, and Western political thoughts of his time. Vad can remain a theory in the Dharmic tradition until subject to rigorous testing and validating outcomes through distinct stages of showing a Siddhantaor - a doctrine. In Marxvad Aur Ramrajya2, Karpatriji begins with a background of this idea. The author then shows the principal argument of the opponent, called Purvapaksa; later dismantling the proposition through logic, using established notions and new notions, to support or add to the established concepts, and eventually instituting the Siddhanta, the alternative view accepted by the Purvapaksin. The work reinforces the method of Purvapaksa and offers a detailed exhibition of the development processes of an argument within Siddhanta. The contestation and convergence of Marxvad Aur Ramrajya happened so distantly. Ramrajya says that just governan

Karpatriji, who authored Marxvad Aur Ramrajya, adheres to the ancient Indian political philosophy tradition. It includes governance as an annealed part of the troika, philosophy, politics, and economics. Genesis of Hindu political philosophy owes to Kautilyaand Shukracharya to show the Indian integration of the milieu of the three disciplines in unison, i.e. Neeti-shastra. Chanakya, also known as Kautilya, offers a doctrine of the mandala, known as spheres of influence, in foreign policy; mandala philosophy finds resonance and tacit presence in the book Marxvad Aur Ramrajya amongst discussed subject matter. Karpatriji illustrated the embeddedness of dharmic phenomena1 in the governance framework of Ramrajya and presents a thesis on Dharmic perspectives in the post-modern world. The book is a magnum opus on a comparative view of Marxism and Dharmic proposition on governance, having veracity of themes and topics discussed in the work. It details Marxism not as a standalone Vad or alternative view on social theory, but instead depicts Marxism founded on a well-developed foundation of Western philosophy, classical Greek philosophy, and Western political thoughts of his time. Vad can remain a theory in the Dharmic tradition until subject to rigorous testing and validating outcomes through distinct stages of showing a Siddhantaor - a doctrine. In Marxvad Aur Ramrajya2, Karpatriji begins with a background of this idea. The author then shows the principal argument of the opponent, called Purvapaksa; later dismantling the proposition through logic, using established notions and new notions, to support or add to the established concepts, and eventually instituting the Siddhanta, the alternative view accepted by the Purvapaksin. The work reinforces the method of Purvapaksa and offers a detailed exhibition of the development processes of an argument within Siddhanta. The contestation and convergence of Marxvad Aur Ramrajya happened so distantly. Ramrajya says that just governan

We report new limits on the kinetic mixing strength of the dark photon spanning the mass range 0.21 -- 1.24 $\mu$eV corresponding to a frequency span of 50 -- 300 MHz. The Dark E-Field Radio experiment is a wide-band search for dark photon dark matter. In this paper we detail changes in calibration and upgrades since our proof-of-concept pilot run. Our detector employs a wide bandwidth E-field antenna moved to multiple positions in a shielded room, a low noise amplifier, wideband ADC, followed by a $2^{24}$-point FFT. An optimal filter searches for signals with Q $\approx10^6$. In nine days of integration, this system is capable of detecting dark photon signals corresponding to $\epsilon$ several orders of magnitude lower than previous limits. We find a 95% exclusion limit on $\epsilon$ over this mass range between $6\times 10^{-15}$ and $6\times 10^{-13}$, tracking the complex resonant mode structure in the shielded room., Comment: 15 pages, 12 figures, submitted to PRD

Weakly interacting massive particles (WIMPs) may interact with a virtual pion that is exchanged between nucleons. This interaction channel is important to consider in models where the spin-independent isoscalar channel is suppressed. Using data from the first science run of the LUX-ZEPLIN dark matter experiment, containing 60 live days of data in a 5.5~tonne fiducial mass of liquid xenon, we report the results on a search for WIMP-pion interactions. We observe no significant excess and set an upper limit of $1.5\times10^{-46}$~cm$^2$ at a 90\% confidence level for a WIMP mass of 33~GeV/c$^2$ for this interaction.

The Data Acquisition System (DAQ) for the LUX-ZEPLIN (LZ) dark matter detector is described. The signals from 745 PMTs, distributed across three subsystems, are sampled with 100-MHz 32-channel digitizers (DDC-32s). A basic waveform analysis is carried out on the on-board Field Programmable Gate Arrays (FPGAs) to extract information about the observed scintillation and electroluminescence signals. This information is used to determine if the digitized waveforms should be preserved for offline analysis. The system is designed around the Kintex-7 FPGA. In addition to digitizing the PMT signals and providing basic event selection in real time, the flexibility provided by the use of FPGAs allows us to monitor the performance of the detector and the DAQ in parallel to normal data acquisition. The hardware and software/firmware of this FPGA-based Architecture for Data acquisition and Realtime monitoring (FADR) are discussed and performance measurements are described., Comment: 18 pages, 24 figures

The first science run of the LUX-ZEPLIN (LZ) experiment, a dual-phase xenon time project chamber operating in the Sanford Underground Research Facility in South Dakota, USA, has reported leading limits on spin-independent WIMP-nucleon interactions and interactions described from a non-relativistic effective field theory (NREFT). Using the same 5.5~t fiducial mass and 60 live days of exposure we report on the results of a relativistic extension to the NREFT. We present constraints on couplings from covariant interactions arising from the coupling of vector, axial currents, and electric dipole moments of the nucleon to the magnetic and electric dipole moments of the WIMP which cannot be described by recasting previous results described by an NREFT. Using a profile-likelihood ratio analysis, in an energy region between 0~keV$_\text{nr}$ to 270~keV$_\text{nr}$, we report 90% confidence level exclusion limits on the coupling strength of five interactions in both the isoscalar and isovector bases., Comment: 7 pages, 4 figures

Four new species of the jumping spider genus Stenaelurillus Simon, 1886 are described from India: Stenaelurillus feral Tripathi, Kuni & Kadam sp. nov. (♂, from the Eastern Coastline), S. naldurg Kuni, Kadam & Tripathi sp. nov. (♂♀, from the Deccan Plateau), S. judithbleisterae Kadam, Tripathi & Kuni sp. nov. (♂♀, from the Western Ghats) and S. solapur Kuni, Tripathi & Kadam sp. nov. (♂♀, from the Deccan Plateau). Detailed diagnoses, descriptions, illustrations, natural history and distribution map are provided. Additionally, new locality records for the other five species within the states are presented and mapped.

There has been considerable interest and resulting progress in implementing machine learning (ML) models in hardware over the last several years from the particle and nuclear physics communities. A big driver has been the release of the Python package, hls4ml, which has enabled porting models specified and trained using Python ML libraries to register transfer level (RTL) code. So far, the primary end targets have been commercial FPGAs or synthesized custom blocks on ASICs. However, recent developments in open-source embedded FPGA (eFPGA) frameworks now provide an alternate, more flexible pathway for implementing ML models in hardware. These customized eFPGA fabrics can be integrated as part of an overall chip design. In general, the decision between a fully custom, eFPGA, or commercial FPGA ML implementation will depend on the details of the end-use application. In this work, we explored the parameter space for eFPGA implementations of fully-connected neural network (fcNN) and boosted decision tree (BDT) models using the task of neutron/gamma classification with a specific focus on resource efficiency. We used data collected using an AmBe sealed source incident on Stilbene, which was optically coupled to an OnSemi J-series SiPM to generate training and test data for this study. We investigated relevant input features and the effects of bit-resolution and sampling rate as well as trade-offs in hyperparameters for both ML architectures while tracking total resource usage. The performance metric used to track model performance was the calculated neutron efficiency at a gamma leakage of 10$^{-3}$. The results of the study will be used to aid the specification of an eFPGA fabric, which will be integrated as part of a test chip.

This Letter reports a search for charge-parity (CP) symmetry violating non-standard interactions (NSI) of neutrinos with matter using the NOvA Experiment, and examines their effects on the determination of the standard oscillation parameters. Data from $\nu_{\mu}(\bar{\nu}_{\mu})\rightarrow\nu_{\mu}(\bar{\nu}_{\mu})$ and $\nu_{\mu}(\bar{\nu}_{\mu})\rightarrow\nu_{e}(\bar{\nu}_{e})$ oscillation channels are used to measure the effect of the NSI parameters $\varepsilon_{e\mu}$ and $\varepsilon_{e\tau}$. With 90% C.L. the magnitudes of the NSI couplings are constrained to be $|\varepsilon_{e\mu}| \, \lesssim 0.3$ and $|\varepsilon_{e\tau}| \, \lesssim 0.4$. A degeneracy at $|\varepsilon_{e\tau}| \, \approx 1.8$ is reported, and we observe that the presence of NSI limits sensitivity to the standard CP phase $\delta_{\tiny\text{CP}}$.

Cryptography plays a pivotal role in safeguarding sensitive information and facilitating secure communication. Classical cryptography relies on mathematical computations, whereas quantum cryptography operates on the principles of quantum mechanics, offering a new frontier in secure communication. Quantum cryptographic systems introduce novel dimensions to security, capable of detecting and thwarting eavesdropping attempts. By contrasting quantum cryptography with its classical counterpart, it becomes evident how quantum mechanics revolutionizes the landscape of secure communication.

Locomotion mechanics of legged robots are suitable when pacing through difficult terrains. Recognising terrains for such robots are important to fully yoke the versatility of their movements. Consequently, robotic terrain classification becomes significant to classify terrains in real time with high accuracy. The conventional classifiers suffer from overfitting problem, low accuracy problem, high variance problem, and not suitable for live dataset. On the other hand, classifying a growing dataset is difficult for convolution based terrain classification. Supervised recurrent models are also not practical for this classification. Further, the existing recurrent architectures are still evolving to improve accuracy of terrain classification based on live variable-length sensory data collected from legged robots. This paper proposes a new semi-supervised method for terrain classification of legged robots, avoiding preprocessing of long variable-length dataset. The proposed method has a stacked Long Short-Term Memory architecture, including a new loss regularization. The proposed method solves the existing problems and improves accuracy. Comparison with the existing architectures show the improvements., Comment: Preliminary draft of the work published in IEEE conference 2023

Recent advancements in non-invasive detection of cardiac hemodynamic instability (CHDI) primarily focus on applying machine learning techniques to a single data modality, e.g. cardiac magnetic resonance imaging (MRI). Despite their potential, these approaches often fall short especially when the size of labeled patient data is limited, a common challenge in the medical domain. Furthermore, only a few studies have explored multimodal methods to study CHDI, which mostly rely on costly modalities such as cardiac MRI and echocardiogram. In response to these limitations, we propose a novel multimodal variational autoencoder ($\text{CardioVAE}_\text{X,G}$) to integrate low-cost chest X-ray (CXR) and electrocardiogram (ECG) modalities with pre-training on a large unlabeled dataset. Specifically, $\text{CardioVAE}_\text{X,G}$ introduces a novel tri-stream pre-training strategy to learn both shared and modality-specific features, thus enabling fine-tuning with both unimodal and multimodal datasets. We pre-train $\text{CardioVAE}_\text{X,G}$ on a large, unlabeled dataset of $50,982$ subjects from a subset of MIMIC database and then fine-tune the pre-trained model on a labeled dataset of $795$ subjects from the ASPIRE registry. Comprehensive evaluations against existing methods show that $\text{CardioVAE}_\text{X,G}$ offers promising performance (AUROC $=0.79$ and Accuracy $=0.77$), representing a significant step forward in non-invasive prediction of CHDI. Our model also excels in producing fine interpretations of predictions directly associated with clinical features, thereby supporting clinical decision-making.

The recent breakthroughs in Large Language Models (LLMs) have mostly focused on languages with easily available and sufficient resources, such as English. However, there remains a significant gap for languages that lack sufficient linguistic resources in the public domain. Our work introduces Komodo-7B, 7-billion-parameter Large Language Models designed to address this gap by seamlessly operating across Indonesian, English, and 11 regional languages in Indonesia. Komodo-7B is a family of LLMs that consist of Komodo-7B-Base and Komodo-7B-Instruct. Komodo-7B-Instruct stands out by achieving state-of-the-art performance in various tasks and languages, outperforming the benchmarks set by OpenAI's GPT-3.5, Cohere's Aya-101, Llama-2-Chat-13B, Mixtral-8x7B-Instruct-v0.1, Gemma-7B-it , and many more. This model not only demonstrates superior performance in both language-specific and overall assessments but also highlights its capability to excel in linguistic diversity. Our commitment to advancing language models extends beyond well-resourced languages, aiming to bridge the gap for those with limited linguistic assets. Additionally, Komodo-7B-Instruct's better cross-language understanding contributes to addressing educational disparities in Indonesia, offering direct translations from English to 11 regional languages, a significant improvement compared to existing language translation services. Komodo-7B represents a crucial step towards inclusivity and effectiveness in language models, providing to the linguistic needs of diverse communities., Comment: 30 Pages, 8 Figures, 4 Tables

This study introduces and evaluates the PRECISE framework, utilizing OpenAI's GPT-4 to enhance patient engagement by providing clearer and more accessible chest X-ray reports at a sixth-grade reading level. The framework was tested on 500 reports, demonstrating significant improvements in readability, reliability, and understandability. Statistical analyses confirmed the effectiveness of the PRECISE approach, highlighting its potential to foster patient-centric care delivery in healthcare decision-making.

Recent advancements in language technology and Artificial Intelligence have resulted in numerous Language Models being proposed to perform various tasks in the legal domain ranging from predicting judgments to generating summaries. Despite their immense potential, these models have been proven to learn and exhibit societal biases and make unfair predictions. In this study, we explore the ability of Large Language Models (LLMs) to perform legal tasks in the Indian landscape when social factors are involved. We present a novel metric, $\beta$-weighted $\textit{Legal Safety Score ($LSS_{\beta}$)}$, which encapsulates both the fairness and accuracy aspects of the LLM. We assess LLMs' safety by considering its performance in the $\textit{Binary Statutory Reasoning}$ task and its fairness exhibition with respect to various axes of disparities in the Indian society. Task performance and fairness scores of LLaMA and LLaMA--2 models indicate that the proposed $LSS_{\beta}$ metric can effectively determine the readiness of a model for safe usage in the legal sector. We also propose finetuning pipelines, utilising specialised legal datasets, as a potential method to mitigate bias and improve model safety. The finetuning procedures on LLaMA and LLaMA--2 models increase the $LSS_{\beta}$, improving their usability in the Indian legal domain. Our code is publicly released.

Although blockchain technology was first introduced in 2008 and materialised in 2009, the early usage of blockchain were mainly limited to financial technologies, particularly cryptocurrencies. Later, blockchain became a widespread emerging technology, utilised in multifaceted sectors and applications. In fact, various new and innovative application of blockchain and distributed ledger technologies are still continuously being researched and explored. On the other hand, smart-contracts were first introduced in 1990s, however, it did not gain enough popularity until being integrated with blockchain technologies lately. The duo lately been seen as the key to many innovations in various industries and sectors. So, we took data from 1445 blockchain-related patent documents and tried to map out the historical and current trends in patenting activities in the blockchain field. This helps us get a better grasp of how blockchain technologies are evolving and being tracked. In addition to serving as an indicator of science and technology growth, patents are also used to judge the research potential and development of a particular technology.

Context Software start-ups have shown their ability to develop and launch innovative software products and services. Small, motivated teams and uncertain project scope makes start-ups good candidates for adopting Agile practices. Objective We explore how start-ups use Agile practices and what effects can be associated with the use of those practices. Method We use a case survey to analyze 84 start-up cases and 56 Agile practices. We apply statistical methods to test for statistically significant associations between the use of Agile practices, team, and product factors. Results Our results suggest that development of the backlog, use of version control, code refactoring, and development of user stories are the most frequently reported practices. We identify 22 associations between the use of Agile practices, team, and product factors. The use of Agile practices is associated with effects on source code and overall product quality. A team's positive or negative attitude towards best engineering practices is a significant indicator for either adoption or rejection of certain Agile practices. To explore the relationships in our findings, we set forth a number of propositions that can be investigated in future research. Conclusions We conclude that start-ups use Agile practices, however without following any specific methodology. We identify the opportunity for more fine-grained studies into the adoption and effects of individual Agile practices. Start-up practitioners could benefit from Agile practices in terms of better overall quality, tighter control over team performance, and resource utilization., Comment: arXiv admin note: text overlap with arXiv:2309.12434

The "metaverse", wherein users can enter virtual worlds to work, study, play, shop, socialize, and entertain, is fast becoming a reality, attracting billions of dollars in investment from companies such as Meta, Microsoft, and Clipo Labs. Further, virtual reality (VR) headsets from entities like Oculus, HTC, and Microsoft are rapidly maturing to provide fully immersive experiences to metaverse users. However, little is known about the network dynamics of metaverse VR applications in terms of service domains, flow counts, traffic rates and volumes, content location and latency, etc., which are needed to make telecommunications network infrastructure "metaverse ready". This paper is an empirical measurement study of metaverse VR network behavior aimed at helping telecommunications network operators better provision and manage the network to ensure good user experience. Using illustrative hour-long network traces of metaverse sessions on the Oculus VR headset, we first develop a categorization of user activity into distinct states ranging from login home to streetwalking and event attendance to asset trading, and undertake a detailed analysis of network traffic per state, identifying unique service domains, protocols, flow profiles, and volumetric patterns, thereby highlighting the vastly more complex nature of a metaverse session compared to streaming video or gaming. Armed with the network behavioral profiles, our second contribution develops a real-time method MetaVRadar to detect metaverse session and classify the user activity state leveraging formalized flow signatures and volumetric attributes. Our third contribution practically implements MetaVRadar, evaluates its accuracy in our lab environment, and demonstrates its usability in a large university network so operators can better monitor and plan resources to support requisite metaverse user experience., Comment: This paper is accepted at ACM SIGMETRICS/IFIP PERFORMANCE 2024 and is published by the Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS)

Allocating conflicting jobs among individuals while respecting a budget constraint for each individual is an optimization problem that arises in various real-world scenarios. In this paper, we consider the situation where each individual derives some satisfaction from each job. We focus on finding a feasible allocation of conflicting jobs that maximize egalitarian cost, i.e. the satisfaction of the \nc{individual who is worst-off}. To the best of our knowledge, this is the first paper to combine egalitarianism, budget-feasibility, and conflict-freeness in allocations. We provide a systematic study of the computational complexity of finding budget-feasible conflict-free egalitarian allocation and show that our problem generalizes a large number of classical optimization problems. Therefore, unsurprisingly, our problem is \NPH even for two individuals and when there is no conflict between any jobs. We show that the problem admits algorithms when studied in the realm of approximation algorithms and parameterized algorithms with a host of natural parameters that match and in some cases improve upon the running time of known algorithms., Comment: Accepted in 23rd International Conference on Autonomous Agents and Multiagent Systems(AAMAS 2024)

This work, in a pioneering approach, attempts to build a biometric system that works purely based on the fluid mechanics governing exhaled breath. We test the hypothesis that the structure of turbulence in exhaled human breath can be exploited to build biometric algorithms. This work relies on the idea that the extrathoracic airway is unique for every individual, making the exhaled breath a biomarker. Methods including classical multi-dimensional hypothesis testing approach and machine learning models are employed in building user authentication algorithms, namely user confirmation and user identification. A user confirmation algorithm tries to verify whether a user is the person they claim to be. A user identification algorithm tries to identify a user's identity with no prior information available. A dataset of exhaled breath time series samples from 94 human subjects was used to evaluate the performance of these algorithms. The user confirmation algorithms performed exceedingly well for the given dataset with over $97\%$ true confirmation rate. The machine learning based algorithm achieved a good true confirmation rate, reiterating our understanding of why machine learning based algorithms typically outperform classical hypothesis test based algorithms. The user identification algorithm performs reasonably well with the provided dataset with over $50\%$ of the users identified as being within two possible suspects. We show surprisingly unique turbulent signatures in the exhaled breath that have not been discovered before. In addition to discussions on a novel biometric system, we make arguments to utilise this idea as a tool to gain insights into the morphometric variation of extrathoracic airway across individuals. Such tools are expected to have future potential in the area of personalised medicines., Comment: 31 pages, 15 figures, Submitted to PLOS ONE (Manuscript Number: PONE-D-23-29558)