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The recently introduced topological heavy fermion model (THFM) provides a means for interpreting the low-energy electronic degrees of freedom of the magic angle twisted bilayer graphene as hybridization amidst highly dispersing topological conduction and weakly dispersing localized heavy fermions. In order to understand the Landau quantization of the ensuing electronic spectrum, a generalization of THFM to include the magnetic field B is desired, but currently missing. Here we provide a systematic derivation of the THFM in B and solve the resulting model to obtain the interacting Hofstadter spectra for single particle charged excitations. While naive minimal substitution within THFM fails to correctly account for the total number of magnetic subbands within the narrow band i.e., its total Chern number, our method—based on projecting the light and heavy fermions onto the irreducible representations of the magnetic translation group— reproduces the correct total Chern number. Analytical results presented here offer an intuitive understanding of the nature of the (strongly interacting) Hofstadter bands. The recently-developed topological heavy fermion model explains the low energy electrons of magic-angle twisted bilayer graphene as a hybridization between states localized at AA stacking sites and itinerant topological states, denoted by f and c electrons in analogy to heavy fermion systems. Here, the authors extend this model to a nonzero magnetic field, obtaining interacting Hofstadter spectra in the flatband limit by analytic methods. [ABSTRACT FROM AUTHOR]

PURPOSE: Mentorship is an integral part of student training in higher education. The most commonly adopted design in Indian Educational Institutes is traditional mentorship; teacher--student mentorship. Larger mentor--mentee ratios are one of the difficulties in this ongoing design, thus we investigate the effect of a concept called peer mentoring where students are assigned specific older peers as mentors. METHODS: The study commenced after receiving ethical approval from the Institutional Ethics Review Committee. Written informed consent and demographic details were obtained from all the participants. One hundred and twenty students were recruited to participate in the study through a systematic random sampling method. Further on they were divided into two groups: teacher--student mentorship and peer mentorship, respectively. All participants were pretested using "Westside Test Anxiety," "Rosenberg Self-Esteem," and "Self-Perception of Test Taking Scale." One session was conducted every week for 12 weeks. The postassessment was performed using the same preevaluation measures. RESULTS: Findings of the present study demonstrate that by the end of 12 weeks' both groups demonstrated reduction in anxiety, improved self-esteem and confidence, and test-taking skills. However, students undergoing peer mentorship demonstrated a greater reduction in their anxiety levels (P < 0.05), better self-esteem levels (P < 0.05), improved confidence levels and test-taking skills (P > 0.05) as compared to traditional mentorship. CONCLUSION: Peer mentorship program was beneficial in reducing anxiety levels and improving self-esteem, confidence, and perception of test-taking skills. As a result, peer mentoring must be implemented as an adjunct to traditional mentorship programs in higher education. [ABSTRACT FROM AUTHOR]

The applications of liquid crystals in the field of renewable, clean and sustainable technologies of energy storage are of utmost importance at present. This paper delves into dielectric spectroscopic studies of a weakly polar nematic liquid crystal (NLC) enriched with an anthraquinone dye. The primary objective is to assess the impact of increasing dye concentrations on various properties. Anthraquinone dye has been found to increase the dielectric permittivity of weakly polar NLC, leading to a 4.7-fold increase in dielectric anisotropy. Simultaneously, a reduction of around 11% in threshold and operating voltages of the NLC has also been recorded after using dye as the guest material. The added dipolar contributions provided by dye molecules have been attributed to this surplus permittivity. The NLC has been found to have an approximately 54% faster response to the applied field. The intrinsic polarization field of dye molecules accelerates nearby LC molecule reorientation, leading to a 56.5% faster fall time and a 29.8% faster rise time in a 3.0 wt% dye-doped LC cell. These experimental results have been validated via computational studies as well. The simulation results about dipole moment and polarizability provide robust support for our experimental results. Such composites evince their potential for energy storage and 5G communication technologies with adjustable impedance and permittivity. [ABSTRACT FROM AUTHOR]

Background: Diabetes mellitus (DM) is a complex endocrinological disorder with altered metabolism of blood glucose. Diabetic ketoacidosis (DKA) is one of the life-threatening acute complications of DM that mainly occurs in type 1 diabetes patients, as well as in some patients with type 2 diabetes. The mortality rate associated with DKA depends on the experience of the treating hospital in dealing with this condition; thus, it is critical that patients detect DKA and get medical help as soon as possible. Aims and Objectives: To study risk factors for DKA, clinical and biochemical profile of DKA patients. Correlation between serum amylase level, serum bicarbonate level and mean duration of hospital stay. Materials and Methods: A cross-sectional analytical study was carried out on 100 DKA patients in the Department of Medicine, SGMH Rewa, Madhya Pradesh from January 2021 to June 2022. The data extracted included clinical presentation, precipitating factors, laboratory profile, complications, and hospitalization outcomes. Results: Of the 100 patients admitted for DKA; 70 had type 2 diabetes (70%) and 30 (30%) were type I diabetes. The average age at the time of presentation was 48.61±19.59 years. The commonest precipitating factor was infection (38%) followed by other factors (62%). The most common clinical features at the time of presentation were altered sensorium, fever, vomiting, polyuria, polydipsia, weakness, lethargy, myalgia, headache, anorexia, abdominal pain, and orthopnea. The values for RBS, HCO3, and pH were 525.0±62.4, 12.6±2.69, and 7.14±0.31, respectively. There was no significant difference in clinical and biochemical profile of patients with type 1 and type 2 diabetes. The mortality rate was 3% and factors found to be significant predictors were comorbid condition, severity of mental status, severity of dehydration, RBS at the time of presentation, and severe acidosis. Conclusion: The most common precipitating factors are infection and omission of insulin or irregular treatment. The most common clinical features at the time of presentation are nausea, vomiting, abdominal pain, headache, and dehydration. There is no significant difference in the clinical and biochemical profile of patients with type 1 and type 2 diabetes. The mortality rate in DKA is 3% and the most notable predictors of poor prognosis are; severity of altered sensorium, severity of comorbid condition, severe dehydration, severe acidosis, and identification and treatment of precipitating factors are more important. Patient education plays a crucial role in the prevention of DKA. [ABSTRACT FROM AUTHOR]

Heavy metals pose serious threats to both individuals and the environment, and there is growing global concern over potentially harmful elements. Heavy metal contamination can have a significant impact on the soil ecosystem's functioning. This requires convenient, efficient, and beneficial remediation approaches. The "ecosystem engineer", earthworms, can modify and enhance soil quality. The ability of earthworms to bioaccumulate metals in substantial amounts in their tissues makes them potentially beneficial as an ecological indicator of soil pollution. Vermiremediation is a new discipline of research in which earthworms are used to detoxify organically contaminated soils. Earthworms have an influential metabolic system, and their gut bacteria and chloragocyte cells play a significant role in their tendency to valorize and detoxify heavy metals. Remediation by earthworms can be considered sustainable, efficient, and ecologically beneficial. The present review provides a wide range of information on earthworms' appropriateness as prospective species for bioremediation and detoxification of toxic metal-contaminated soil to mitigate human health and environmental problems. [ABSTRACT FROM AUTHOR]

Background: Diastolic dysfunction in young adults is associated with increased morbidity and mortality. The identification of prospective risk markers associated with diastolic dysfunction could allow for targeted primary prevention efforts. We try to establish the correlation between the fatty liver with diastolic dysfunction in normotensive young patients under 40 years of age. Method: This cross-sectional analytical study was conducted between April 2021 and March 2022 in Sanjay Gandhi Memorial Hospital associated with Shyam Shah Medical College, Rewa. It included 214 normotensive cases under 40 years with fatty liver. Patient information, clinical examination, and various tests were conducted to assess diastolic dysfunction. The collected data was compared with previous studies for analysis. Results: Out of 214 cases 105 (49%) were male and 109 were female (51%). Mean age of the patients was 27.84 ± 8.27 years. Out of 214 patient's normal diastolic dysfunction found in 167 (78.04%) cases followed by the 26 (12.15%) cases had grade-1, 15 (7.0%) cases had grade 2 and 06 (2.81%) patients had grade 3 diastolic dysfunction. Among all cases 180 (84.11%) of the patients had grade 1 fatty liver out of which 156 (86.66%) had no diastolic dysfunction, while the 17 (9.44%) cases had grade-1, 6 (3.33%) had grade 2, and 1 (0.55%) patient had grade 3 diastolic dysfunction. 29 (13.55%) cases were found to have grade 2 fatty liver out of which 6 (20.68%) had no diastolic dysfunction, while the 9 (31.03%) cases had grade-1, 9 (31.03%) had grade 2, and 5 (17.25%) patients had grade 3 diastolic dysfunction. 5 (2.33%) cases found to have grade 3 fatty liver all 5 (2.33%) were found to have no diastolic dysfunction. Conclusion: The prevalence of diastolic abnormalities in adults under 40 years with fatty liver was 21.9%, indicating a significant correlation. Clinicians should consider cardiovascular risks and undertake early risk factor modification. [ABSTRACT FROM AUTHOR]

The issue of managing organic waste such as animal waste and industrial waste has emerged as a result of the fast development in urbanization around the world. It can be hazardous to the environment and public health if these are not properly stored, collected, and disposed of. These biological wastes can be turned into nutrient-rich biofertilizers using the vermicomposting process. The bio-oxidative method includes the combined activity of earthworms and microbes. The pH, organic carbon, organic matter, and the C:N ratio of the various organic waste mixtures showed a declining tendency during this process but the content of nitrogen, available phosphorous and exchangeable potassium showed a rising trend as the vermicomposting time progressed. Maximum earthworm growth and reproduction were reported better in different feed materials prepared from industrial wastes. Therefore, the present review article is based on the knowledge of using earthworms to stabilize waste. [ABSTRACT FROM AUTHOR]

In this work, we consider a hybrid aerial full-duplex (FD) relaying protocol consisting of a reconfigurable intelligent surface (RIS) mounted over an FD unmanned aerial vehicle (UAV) relay operating in the decode and forward mode to assist the information transfer between the base station and multiple users. For better spectral efficiency, we investigate the use of non-orthogonal multiple access (NOMA) in such networks and focus on both the performance analysis and design optimization of the considered RIS-NOMA network under imperfect channel state information (CSI) and successive interference cancellation (SIC) at each user, and residual-self interference (RSI) at UAV. We first formulate the sum rate maximization problem and adopt the block coordinate descent method to deal with the non-convex nature of the problem. Thereafter, we propose an algorithm based on the Riemannian conjugate gradient method to get the optimal phase shifts at the RIS, an iterative algorithm to obtain the optimal UAV/RIS position and the exhaustive method to obtain the optimum power allocation coefficients. Next, with obtained optimal position, phase shift and power coefficients, we further analyze the performance of the network and derive the closed-form expressions of outage probability, achievable throughput and ergodic capacity. We present Monte Carlo simulation-based results to validate the accuracy of the proposed algorithms and derived expressions and demonstrate the superiority of NOMA over OMA. [ABSTRACT FROM AUTHOR]

In this paper, a reconfigurable intelligent surfaces (RISs)-aided millimeter wave (mmWave) uplink (UL) rate-splitting multiple access (RSMA) system is investigated which targets to achieve better rate performance and enhanced coverage capability for multiple users. The considered UL RSMA model splits the rate for each user by dividing their message into multiple parts and hence exploits all the necessary degrees of freedom to achieve maximum capacity region and high user fairness. In particular, we focus on the sum-rate maximization for considered UL RSMA system subject to joint optimization of power allocation to the UL users and beamforming design, i.e., active receive beamforming at the base-station (BS) and passive beamforming at multiple RISs. To efficiently mitigate high inter-node interference in multi-user scenario, we first provided a low-complex user pairing scheme based on k-means clustering and then develop an effective low-cost alternating optimization framework to solve the joint optimization problem sub-optimally by decoupling the problem into different sub-problems of power allocation and beamforming design. Specifically, the sub-problems of power allocation and beamforming design are solved using successive convex approximation, Riemannian manifold and fractional programming techniques. Later, the unified solution based on block coordinate descent (BCD) algorithm is proposed. Extensive numerical simulations validate that the user-clustering effectively significantly improves the performance gain and the considered RSMA system outperforms the conventional multiple schemes in terms rate and user-fairness. Also, the exploitation of spatial correlation among each RIS elements i.e., non-diagonal phase-matrices at each RIS achieve better performance that conventional diagonal phase-matrices setting. [ABSTRACT FROM AUTHOR]

Due to the dynamic nature of a vehicular fog computing environment, efficient real-time resource allocation in an Internet of Vehicles (IoV) network without affecting the quality of service of any of the onboard vehicles can be challenging. This article proposes a priority-sensitive task offloading and resource allocation scheme in an IoV network, where vehicles periodically exchange beacon messages to inquire about available services and other important information necessary for making the offloading decisions. In the proposed methodology, the vehicles are stimulated to share their idle computation resources with the task vehicles, whereby a deep reinforcement learning algorithm based on soft actor–critic is designed to classify the tasks based on priority and computation size of each task for optimally allocating the power. Furthermore, we also design deep deterministic policy gradient (DDPG) and twin delayed DDPG (TD3) algorithms for the considered framework. In particular, the algorithms work toward achieving the optimal policy for task offloading by maximizing the mean utility of the considered network. Extensive numerical results under different network conditions, along with comparison among the three algorithms, are presented to validate the feasibility of distributed reinforcement learning for task offloading in future IoV networks. [ABSTRACT FROM AUTHOR]

In the present study, the isomeric forms of a biologically active 2-aminopyrimidinium picrate (2APP) cocrystal were investigated using spectroscopic measurements (FT-IR and FT-Raman) and density functional theory calculations. The vibrational assignments of IR and Raman peaks were predicted and the experimental FT-IR and FT-Raman spectra of the condensed phase of 2APP were compared with the simulated one. The intrinsic reaction coordinate (IRC) analysis was performed on all the possible reaction pathways to identify the isomeric forms of 2APP and transition state geometry. From the IRC analysis, a relatively stable form (named as isomer 2) has been identified in addition to the existing isomeric form (isomer 1) in the crystalline packing of 2APP. The presence of non-covalent interactions within the isomeric forms of 2APP was investigated with the help of quantum topological atoms in molecules analysis. Reactivity descriptors and charge delocalization from lone pair to acceptor entities of both the isomers were predicted to validate the interactions present in the molecule and also to understand the charge distribution within the molecule. [ABSTRACT FROM AUTHOR]

Kawasaki disease is a systemic vasculitis, especially of the coronary arteries, affecting children. Despite extensive research, much is still unknown about the principal driver behind the amplified inflammatory response. We propose mitochondria may play a critical role. Mitochondria serve as a central hub, influencing energy generation, cell proliferation, and bioenergetics. Regulation of these biological processes, however, comes at a price. Release of mitochondrial DNA into the cytoplasm acts as damage-associated molecular patterns, initiating the development of inflammation. As a source of reactive oxygen species, they facilitate activation of the NLRP3 inflammasome. Kawasaki disease involves many of these inflammatory pathways. Progressive mitochondrial dysfunction alters the activity of immune cells and may play a role in the pathogenesis of Kawasaki disease. Because they contain their own genome, mitochondria are susceptible to mutation which can propagate their dysfunction and immunostimulatory potential. Population-specific variants in mitochondrial DNA have also been linked to racial disparities in disease risk and treatment response. Our objective is to critically examine the current literature of mitochondria's role in coordinating proinflammatory signaling pathways, focusing on potential mitochondrial dysfunction in Kawasaki disease. No association between impaired mitochondrial function and Kawasaki disease exists, but we suggest a relationship between the two. We hypothesize a framework of mitochondrial determinants that may contribute to ethnic/ racial disparities in the progression of Kawasaki disease. [ABSTRACT FROM AUTHOR]

A literary criticism of the books "Instrumental Rationality: The Normativity of Means-Ends Coherence" by John Brunero and "Rational Powers in Action: Instrumental Rationality and Extended Agency" by Sergio Tenenbaum is presented. It examines philosophical aspects of the theory of rationality and explores relationship between substantive and structural rationality.

Reconfigurable intelligent surface (RIS) has emerged as important transmission technology to improve the spectral/energy efficiency in the next-generation (beyond 5G (B5G) and 6G) wireless communication network and has numerous applications in the areas of Internet of Things (IoT) and vehicular communication systems. Thus, in this paper, we investigate the application of RIS in unmanned aerial vehicle (UAV) enabled vehicular communication system with infinite and finite block length codes, where UAV communicates with the single antenna ground vehicle in the presence of several interfering vehicles on the road. We have obtained the approximate closed-form statistics of received SINR at ground vehicle in the presence of multiple nonidentical interference links. Furthermore, we analyze the performance of the considered system in terms of the coverage probability, bit-error-rate, block error rate (BLER) and goodput. It has been shown through the numerical results that the deployment of RIS significantly improves the performance of UAV-enabled vehicular communication network, even in the presence of the direct link between the UAV and the ground vehicle. Additionally, we also investigate the impact of various channel and system parameters like practical reflection coefficients of RIS, number of RIS reflecting elements, and number of interfering vehicles on the system performance. The analytical results are corroborated with Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

In cognitive radio networks, wireless nodes adapt to the surrounding radio environment and utilize the spectrum of licensed users. The cognitive radio environment is dynamic, and wireless channels are accessible by both legitimate and illegitimate users. Therefore, maintaining the security of cognitive radio networks is a challenging task, which must be addressed thoroughly. Further, with the recent exponential surge in wireless nodes and associated high data rate requirements, energy consumption is also growing at an unprecedented rate. Hence, energy efficiency becomes an important metric that must be considered in the design of future wireless networks. Accordingly, by considering the great ecological and economic benefits of green wireless networks, this work focus on energy-efficient resource allocation in secure cognitive radio networks. Since physical-layer security is an emerging technique that improves the security of communication devices, in this paper, an ergodic secure energy efficiency problem for a cognitive radio network is formulated with a primary user, a secondary user, and an eavesdropper. As the formulated problem is non-convex, a concave lower bound is applied to transform the original non-convex problem into a convex one. Further, by adopting the fractional programming and dual decomposition techniques, optimal power allocation strategies are obtained with the aim of maximizing the ergodic secure energy efficiency of the secondary user with constraints on the average interference power and average transmit power. Numerical examples are used to demonstrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Owing to the factors such as controllable mobility, ready-to-use technology, low cost, easy implementation, and so on, unmanned aerial vehicle (UAV) possesses tremendous potential to be one of the primary candidates for next-generation (6G) wireless networks. This paper presents a UAV-assisted multiuser communication network where a multiple antenna UAV base station (BS) serves multiple single antenna ground users (GUs). UAV-BS uses a laser source-based charging mechanism to fulfill its power requirement and applies simultaneous wireless information and power transfer (SWIPT) in the downlink in order to provide desired power to energy-constrained GUs. Also, a clustering-based hybrid multiple access technique is used that combines both orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) signaling to transmit the information to all GUs, simultaneously. Due to the involved analytical complexity corresponding to the multiple antennas and users, we use a hybrid beamforming method for efficient communication. Next, we analyze the performance of the proposed framework in terms of user outage probabilities, their respective throughput, and average power harvested considering non-linear energy harvesting and derive expressions of these performance metrics. Moreover, we formulate an optimization problem where the throughput of one GU is maximized by optimally choosing the power allocation parameter while ensuring the desired target throughput at other GU in each cluster. We also illustrate how crucial is the optimal selection of the target rates to maximize the network performance. Simulation results are provided to validate the accuracy of derived expressions and to highlight the dominance of hybrid beamforming and hybrid NOMA compared to conventional methods on the performance of the considered network. [ABSTRACT FROM AUTHOR]

Wireless sensor networks, consisting of sensor nodes, monitoring the real-world phenomena generate a huge amount of data. However, the transmission of these measured values consumes most of the battery power of energy constrained sensor nodes. In this paper, threshold based data reduction system (TBDRS) is proposed in order to reduce the transmissions from the sensor node by exploiting the correlation between the measured values. Unlike other systems, TBDRS uses a control mechanism for threshold based switching on the basis of estimation error. This switching allows the system to achieve better trade-off between convergence speed and misadjustment, thereby improving the lifetime of the wireless sensor network by reducing the number of transmissions and computations. Due to the settling time, misadjustment trade-off capability, TBDRS can also be used in disaster management applications where the sensor data variations are more. The performance analysis of the system is evaluated in terms of mean square error. Moreover, the performance of TBDRS is evaluated for different parameters including length, step size and scaling factor. The simulation results validate that the proposed system achieves 70.56% and 83.01% better performance than the state-of-the-art system for an accuracy of 0.1 in terms of data reduction and number of computations, respectively. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surface (RIS) has emerged as an important transmission technology for numerous applications in Internet of Things (IoT) systems. Thus, in this paper, we investigate the application of RIS in energy harvesting (EH) based unmanned aerial vehicle (UAV) communication network with finite block length (BL) codes, where a rotary wing type flying UAV communicates with the multiple single antenna IoT users with the aid of multiple RISs mounted on several skyscraper buildings. To transmit the signal to a particular IoT user, the UAV selects an RIS on the basis of either UAV-RIS (i.e., partial) or UAV-RIS-IoT (i.e., full) channel state information (CSI) and then transmits the signal through the selected RIS along with the direct link transmission. In particular, we derive (i) the expression for probability of RIS selection, (ii) the statistical distribution of instantaneously received information signal-to-noise ratio (SNR) at the IoT user. Based on the derived statistics, we analyze the performance of the considered system under finite BL codes in terms of the average outage probability, average block error rate (ABLER) and goodput averaged over entire flying duration. Moreover, the BLER performance with finite BL codes is also compared with the infinite BL codes scenario. Additionally, we also investigate the impact of various channel and system parameters like imperfect CSI, number of RISs and the number of reflecting elements at each RIS, location of IoT users, variable altitude of the UAV, and the severity of channel fading of UAV-RIS link on the system performance. Furthermore, we have obtained the optimum UAV location in each time slot which minimizes the ABLER per time slot over all the users in the network. The analytical results are corroborated with Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

Graphene and carbon nanotubes (CNTs) have gotten a lot of attention because of their varied nanostructures, making it a very intriguing and comprehensive topic in nanotechnology. Graphene and carbon nanotubes (CNTs) both have unique electrical, mechanical, thermal, catalytic, and electrochemical features because they are made up of sp2 hybridized carbon atoms. Carbon nanotube hybrid nanostructured materials (CNT hybrid nanocomposites), Carbon nanotubes (CNTs), and nanotechnology have the potential to improve energy conversion and storage device applications. Carbon nanotubes are being evaluated for application in renewable energy sources, including solar cells and hydrogen storage. Carbon nanotubes (CNTs) are utilized in storage technologies such as Li-ion batteries, supercapacitors, and thermal energy harvesting. We describe the functions of carbon nanotubes (CNTs) in new energy storage technologies, particularly electrochemical supercapacitors and Lithium-ion batteries, in this study. The use of carbon nanotubes in binder-free electrodes, microscaled current collectors, and adaptable and stretchy energy storage systems is also explored. [ABSTRACT FROM AUTHOR]

To address the issues of poor graphene dispersion, uneven thermal conductivity, and the environmental effect of porous polyurethane (PU) solutions, natural nano cellulose is employed as a surfactant to dissolve the graphene slurry in order to build a composite heating film. By altering the volume of the graphene slurry, the screen-printing method performs in-situ coating on heat-reflective cloth (sportswear lining materials) and determines the heating impact and washing qualities of the clothing. The results reveal that natural nanocellulose has a good dispersion effect. After the addition of silver paste, graphene dispersions with varying concentrations exhibit good thermal and electrical conductivity. When the heating voltage is 8v and the graphene slurry concentration is 12.5 % (wwt), the surface temperature of the heating film can exceed 50°C while the power consumption is low, which not only maintains long-term power supply but also addresses the shortcomings of the traditional polyester heating film, such as uncomfortable wearing. Furthermore, even after washing and soaking it more than 50 times, it has an excellent heating function. [ABSTRACT FROM AUTHOR]

Nanotechnology has an impact on many scientific and technical fields, including environmental safety. Environmental applications of nanotechnology include water and wastewater treatment, in which different nanomaterials utilize adsorption and separation processes, as well as a variety of other approaches, to remove pollutants, pathogens, and other hazardous elements. Diverse forms, various composites, and active component functionalization are only a few of the ways nanomaterials are formed. To ensure a plentiful supply of water, nanostructures have presented a practical alternative. Due to its very specific area of surface, microinterface properties, and remediation potential, nanomaterials have emerged as a hot topic in environmental research. The review paper covers diverse treatment methods for wastewater, including adsorption, catalysis, spacing, and disinfection, and a range of nanomaterials such as NPs for graphene, TiO2 nanoparticles (NPs), (nZVI), NPs for nanoscale Fe3O4, ZnO NPs, nanoparticles in silver (Ag-NPs), Carbon nanotubes (CNTs), and several additional NPs as well as various nanocomposite materials, such as inorganic and organic supports, magnetic nanocomposite, and nanocomposite membranes, etc. Most crucially, the possible application of nanomaterials in water and wastewater treatment is also considered in the future. [ABSTRACT FROM AUTHOR]

In the context of the characterization of increasing impurities, rapid urbanization and industrialization, and decrease in the available water resources, the application of conventional water treatment and wastewater treatment procedures is becoming more difficult. Recent development processing techniques, such as disinfection and antimicrobial mechanisms, membrane filtration, sensing and monitoring, and UV radiation, are very promising and therefore revised in this paper, providing alternatives to better protect human health and the environment. Its fundamental principles, main applications, and recent innovations have been emphasized. Particularly in comparison to their existing conclusions and recommendations research needs, the benefits and drawbacks of such technologies are demonstrated. Conventional wastewater treatment technology, along with wastewater minimization and water recycling programs, provides promise for reducing and maybe preventing, the unavoidable loss of useful water. The conclusion is that the applications of these technologies will be enhanced at an unparalleled scale alongside increasing knowledge and advances in the industrial sector. [ABSTRACT FROM AUTHOR]

This letter investigates the problem of accurate localization of a target node in wireless sensor networks using time of arrival (TOA) and received signal strength (RSS) measurements in an adverse non-line of sight (NLOS) environment. The proposed methodology works without any requirement of the NLOS path identification or the prior knowledge of NLOS bias distribution. A non-linear weighted least squares (NLWLS) problem is formulated through general approximations on the hybrid data model. The formulated NLWLS problem is solved using a computationally efficient majorization-minimization (MM) algorithm in which the NLWLS objective is iteratively minimized via simple update steps. The proposed MM algorithm is guaranteed to converge to a stationary point of the NLWLS objective. Simulation results and computational complexity analysis validate that the proposed MM algorithm attains fast convergence with lower latency. Moreover, the proposed hybrid localization algorithm outperforms the state-of-art methods in terms of estimation accuracy and computational complexity. [ABSTRACT FROM AUTHOR]

This paper investigates unmanned aerial vehicles (UAVs)-assisted full-duplex (FD) non-orthogonal multiple access (NOMA) system based cellular network, aiming to improve overall sum-rate throughput of the system through dynamic user clustering, optimal UAV placement and power allocation. Since each UAV operates in FD mode, self-interference (SI), co-channel interference (CCI), inter-UAV interference (IUI) and intra-node interference (INI) dominate the system’s performance. Consequently, we propose an unconventional two-stage dynamic user clustering for user nodes (UNs) to reduce the cross-interference in multi-UAV aided FD-NOMA system. Particularly, all UNs are initially clustered into $K$ clusters using k-means clustering in the first stage where each cluster is served by an UAV. Furthermore, each cluster is further divided into sub-clusters and each sub-clusters are operated in FD-NOMA scheme. Finally, to control interferences, a sum-rate throughput maximization problem is formulated for each UAV to jointly optimize uplink and downlink power allocation and UAV placement. The joint optimization problem is non-convex and difficult to solve directly, for which we decoupled the original problem by addressing UAV placement and power allocation separately. We first fix the UAV position and then solve the problem iteratively using successive convex approximation (SCA) method. By utilizing brute-force search algorithm, an optimal UAV placement is later performed which corresponds to maximum possible sum-rate throughput. Simulation results demonstrate that the proposed solution for the considered FD-NOMA system outperforms the conventional schemes. [ABSTRACT FROM AUTHOR]

The aim of the current study is to apply multivariate singular spectrum analysis (M-SSA) techniques and investigate both shallow and intermediate-depth earthquake characteristics in eastern Nepal and the southern Tibetan Himalaya. Space–time-depth-magnitude (STDM) domain time-series were computed for a time window of 776 events, using a complete catalog (2005–2020) provided by the European-Mediterranean Seismological Center. Several criteria and tests, such as the quantile–quantile plot, Hankel matrix, and principal and reconstruction components analysis of STDM time-series were introduced to characterize the causality and predictability of seismic changes. It was evident from the quantile–quantile plot those events (Mw) do not approximate a linear trend but present a nonlinear trend, which is possibly due to the unusual seismically generated strain that cannot be accurately unstable compared to large earthquakes. Principal component analysis of the Hankel matrix strongly influences the ability of M-SSA to extract the measured and noise errors of an STDM time-series. Based on a reconstruction component analysis, the separability of the varying correlation coefficient between measured and predicted STDM time-series was evaluated and reconstructed in three groups: trend, oscillating, and noise group components. In conclusion, supporting the current research, it can be claimed that the results serve as a baseline study of seismicity using the M-SSA approach; by taking the example of eastern Nepal and the southern Tibetan Himalaya, users will be able to utilize M-SSA at the global level. [ABSTRACT FROM AUTHOR]

Ultra-reliable low-latency communication (URLLC) is one of the most important components in the fifth generation (5G) cellular networks for realizing mission-critical applications. In this paper, we jointly optimize the transceiver design and decoding error probability (DEP) of a full-duplex (FD) URLLC system, where the base station (BS) operates in FD mode, while the uplink (UL) and downlink (DL) users work in half-duplex (HD) mode. Accordingly, an optimization problem is formulated to maximize the achievable total (UL plus DL) rate for an FD URLLC system under finite blocklength, subject to the end-to-end (E2E) reliability constraint from the UL user to each DL user and the total transmission power constraint at the UL user and at the BS. We analyze the problem structure and convexify the problem by approximating the channel dispersion in scenarios of high and mid-to-high signal-to-interference plus noise ratio (SINR) regimes, respectively. Next, efficient iterative algorithms are proposed to find the near-optimal power allocation for the UL user and transceiver weights for the BS. Furthermore, closed-form expressions of the transceiver weights are derived, and the convergence of the proposed algorithms is proved. Simulation examples demonstrate the impact of the code blocklength, number of DL users, transmitter/receiver distortion and DEP threshold on the system performance. [ABSTRACT FROM AUTHOR]

A reconfigurable intelligent surface (RIS)-assisted wireless communication system with non-linear energy harvesting (EH) and ultra-reliable low-latency constraints is considered for its possible applications in industrial automation. A distant data-center (DC) communicates with the multiple destination machines with the help of a full-duplex (FD) server machine (SM) and RIS. Assuming the deficiency of enough transmission power at the FD-SM, the SM is considered in the near vicinity of the destinations in the industry to forward the data received from the distant DC. The reception at SM is assisted by the RIS and a non-linear hybrid power-time splitting (PTS) based EH receiver architecture is adopted to extend the lifespan of SM, thus increasing network lifetime. The scheduling of multiple destinations is done by SM based on the considered selection criteria namely, random (RND) scheduling, absolute (ABS) channel-power-based (CPB) scheduling and normalized (NRM) CPB scheduling. The end-to-end performance of the considered FD RIS-assisted network is analyzed, and the expressions for the block error rate (BLER) for all scheduling schemes are derived. Moreover, the effects of number of RIS elements, packet size, channel uses on the system performance are analyzed for the considered ultra-reliable and low-latency communication (URLLC) network. The scheduling fairness of all the scheduling schemes is also analyzed to study the performance-fairness trade-off. The derived analytical results are verified through Monte-Carlo simulations. [ABSTRACT FROM AUTHOR]

This paper investigates the full-duplex (FD)-enabled unmanned aerial vehicles (UAVs) communication system designed to improve spectrum utilization and coverage issues in the suburban environment. The reliability analysis of the considered system is analyzed in terms of block error rate (BLER) under ultra-reliable and low-latency communication constraints. With the assumption of the combined effect of fading and shadowing, the closed-form expressions for BLER and system goodput are obtained over Rician shadowed fading channels considering various shadowing scenarios, inter-UAV interference, and self-interference (SI) cancellation capabilities at FD node. The obtained results over Rician shadowed fading for FD-enabled UAV system are also compared with it's half-duplex counterpart over Rician fading channels. It was concluded that strong SI suppression capabilities at FD GS can results in almost 85% of performance gain at low shadowing severity conditions. The numerical results reveal important observations related to the impact of shadowing severity in the suburban areas, SI cancellation capabilities, blocklength and channel uses on the reliability performance of the FD-enabled multi-UAV system. [ABSTRACT FROM AUTHOR]

SARS-CoV-2 harbors many known unknown regions in the form of hypothetical open reading frames (ORFs). Although the mechanisms underlying the disease pathogenesis are not clearly understood, molecules such as long noncoding RNAs (lncRNAs) play a key regulatory role in the viral pathogenesis from endocytosis. We asked whether or not the lncRNAs in the host are associated with the viral proteins and argue that lncRNA-mRNAs molecules related to viral infection may regulate SARS-CoV-2 pathogenesis. Toward the end of the perspective, we provide challenges and insights into investigating these transgression pathways. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surface (IRS) has recently emerged as a promising technology for 6 G wireless systems, due to its capability to reconfigure the wireless propagation environment. In this paper, we investigate a Rate-Splitting Multiple Access (RSMA) for IRS-assisted downlink system, where the base station (BS) communicates with single-antenna users with the help of an IRS. RSMA relies on rate-splitting (RS) at the BS and successive interference cancellation (SIC) at the users and provides a generalized multiple access framework. We derive a new architecture called IRS-RS that leverages the interplay between RS and IRS. For performance analysis, we utilize an on-off control technique to control the passive beamforming vector of the IRS-RS and derive the closed-form expressions for outage probability of cell-edge users and near users. Moreover, we also analyze the outage behavior of cell-edge users for a sufficiently large number of reflecting elements. Additionally, we also analyze the outage performance of cooperative RS based decode-and-forward (DF)-assisted framework called DF-RS. Through simulation results, it is shown that the proposed framework outperforms the corresponding DF-RS, RS without IRS and IRS-assisted conventional non-orthogonal multiple access (NOMA) schemes. Furthermore, the impact of various system's parameters such as the number of IRS reflecting elements and the number of users on the system performance is revealed. [ABSTRACT FROM AUTHOR]

In this paper, a multi-user full-duplex (FD) two-way relaying system with decode-and-forward protocol is considered where all the nodes are assumed to be mobile and to have FD abilities. The residual self-interference (RSI) at each node is modeled as a Rician distributed random variable and the effect of mobility is incorporated by adopting the first order auto-regressive (AR) model. Then, the signal-to-interference-plus-noise-ratio (SINR) based scheduling schemes namely random scheduling, absolute channel power-based (CPB) scheduling, hybrid scheduling, and normalized CPB scheduling, are modified and the user pair selection is carried out on the basis of instantaneous channel statistics. The performance of the considered framework is analyzed for the modified scheduling schemes in terms of error probability and average rate. Next, the closed-form expressions for the symbol error probability (SEP) and average rate are derived for independent and non-identically distributed Rayleigh fading channels. Also, the numerical analysis highlighting the impact of user mobility and imperfect channel estimation on the scheduling strategies, fairness is presented. Furthermore, the impacts of the degree of traffic asymmetry, scheduling fairness, user mobility, channel estimation errors and RSI on the system performance are investigated. Numerical results are validated through the Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

In recent years, there has been increasing interest in analytic philosophy that engages with non-Western philosophical traditions, including South Asian religions such as Hinduism, Buddhism, and Jainism. However, thus far, there has been (to my knowledge) no engagement with Sikhism, despite its status as a major world religion with a rich philosophical tradition. This paper is an attempt to get a start at analytic philosophical engagement with Sikh philosophy. My focus is on Sikh ethics, and in particular on the theory of vice and virtue that can be gleaned from Sikh scripture. According to this theory, the five major vices have a unified source in the vice of haumai. Haumai is a kind of false conception of oneself as singularly important, and correspondingly, a false conception of the world as revolving around oneself, as a world of objects there for one's use. Vice, then, comes down to the failure to recognize the importance of others. The corresponding picture of virtue is that virtue consists in a recognition of the importance of others, through the recognition of an ultimate reality on which all are One. After reconstructing the Sikh theory of vice and virtue, I conclude with some comparative remarks on Sikh and Western ethics. [ABSTRACT FROM AUTHOR]

Susanna Rinard has recently offered a new argument for pragmatism and against evidentialism. According to Rinard, evidentialists must hold that the rationality of belief is determined in a way that is different from how the rationality of other states is determined. She argues that we should instead endorse a view she calls Equal Treatment, according to which the rationality of all states is determined in the same way. In this paper, I show that Rinard's claims are mistaken, and that evidentialism is more theoretically virtuous than its opponents sometimes give it credit for. Not only does evidentialism not make an exception for belief, but it fits naturally into a unified, explanatorily powerful account of the rationality of intentional mental states. According to such an account, the rationality of all intentional mental states, including belief, is determined by the right kind of reasons for those states. Since the right kind of reasons for belief just are evidential considerations, this unified account entails evidentialism. I conclude, contra Rinard, that evidentialism can be (and often is) situated within a general account of rationality that is at least as theoretically virtuous as pragmatism, if not more so. [ABSTRACT FROM AUTHOR]

Hydrogen is significant and may be viewed as an alternative for main fossil fuels, coal, crude oil, and natural gas, as well as its derivatives when utilized as fuel. It has the potential to be a clean, efficient, and inexpensive energy source. The main benefit is that its oxygen-burning products are water and not carbon-containing and greenhouse gases CO and CO2. Conventional forms of energy are dependent on fossil fuels and have several consequences, namely pollution, climate change, and increased price. Promising alternatives are renewable energy sources like solar and wind energy. However, the main limitation for renewable energy sources is that they are always unavailable and provide us with interrupted energy. As a result, energy resources should be combined with energy storage devices in order to offer continuous power. This paper examines the various storage systems and concentrates on energy storage systems based on hydrogen. [ABSTRACT FROM AUTHOR]

Ovarian cancer (OC) is known to be the most lethal cancer in women worldwide, and its etiology is poorly understood. Recent studies show that mitochondrial DNA (mtDNA) content as well as mtDNA and nuclear genes encoding mitochondrial proteins influence OC risk. This review presents an overview of role of mitochondrial genetics in influencing OC development and discusses the contribution of mitochondrial proteome in OC development, progression and therapy. A role of mitochondrial genetics in racial disparity is also highlighted. In-depth understanding of role of mitochondria in OC will help develop strategies toward prevention and treatment and improving overall survival in women with OC. [ABSTRACT FROM AUTHOR]

Pigmentation abnormalities are reported in the spectrum of phenotypes associated with aging and in patients with mitochondrial DNA depletion syndrome (MDS). Yet, a relevant animal model that mimics these effects and would allow us to evaluate the detrimental aspects of mtDNA depletion on melanocyte function has not been described. Here, we characterize the pigmentary changes observed in the ears of a mtDNA‐depleter mouse, which phenotypically includes accentuation of the peri‐adnexal pseudonetwork, patchy hyper‐ and hypopigmentation, and reticular pigmentation. Histologically, these mice show increased epidermal pigmentation with patchy distribution, along with increased and highly dendritic melanocytes. These mtDNA‐depleter mice mimic aspects of the cutaneous, pigmentary changes observed in humans with age‐related senile lentigines as well as MDS. We suggest that this mouse model can serve as a novel resource for future interrogations of how mitochondrial dysfunction contributes to pigmentary skin disorders. The mtDNA‐depleter mouse model also serves as a useful tool to identify novel agents capable of treating pigmentary changes associated with age‐related mitochondrial dysfunction in humans. [ABSTRACT FROM AUTHOR]

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The COVID-19 pandemic has been the primary global health issue since its outbreak in December 2019. Patients with metabolic syndrome suffer from severe complications and a higher mortality rate due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We recently proposed that SARS-CoV-2 can hijack host mitochondrial function and manipulate metabolic pathways for their own advantage. The aim of the current study was to investigate functional mitochondrial changes in live peripheral blood mononuclear cells (PBMCs) from patients with COVID-19 and to decipher the pathways of substrate utilization in these cells and corresponding changes in the inflammatory pathways. We demonstrate mitochondrial dysfunction, metabolic alterations with an increase in glycolysis, and high levels of mitokine in PBMCs from patients with COVID-19. Interestingly, we found that levels of fibroblast growth factor 21 mitokine correlate with COVID-19 disease severity and mortality. These data suggest that patients with COVID-19 have a compromised mitochondrial function and an energy deficit that is compensated by a metabolic switch to glycolysis. This metabolic manipulation by SARS-CoV-2 triggers an enhanced inflammatory response that contributes to the severity of symptoms in COVID-19. Targeting mitochondrial metabolic pathway(s) can help define novel strategies for COVID-19. [ABSTRACT FROM AUTHOR]

Generalized Spatial Modulation (GSM) is being considered for high capacity and energy-efficient networks of the future. However, signal detection due to inter channel interference among the active antennas is a challenge in GSM systems and is the focus of this letter. Specifically, we explore the feasibility of using deep neural networks (DNN) for signal detection in GSM. In particular, we propose a block DNN (B-DNN) based architecture, where the active antennas and their transmitted constellation symbols are detected by smaller sub-DNNs. After $N$ -ordinary DNN detection, the Euclidean distance-based soft constellation algorithm is implemented. The proposed B-DNN detector achieves a BER performance that is superior to traditional block zero-forcing (B-ZF) and block minimum mean-squared error (B-MMSE) detection schemes and similar to that of classical maximum likelihood (ML) detector. Further, the proposed method requires less computation time and is more accurate than alternative conventional numerical methods. [ABSTRACT FROM AUTHOR]

Because of the ongoing pandemic around the world, the mechanisms underlying the SARS-CoV-2-induced COVID-19 are subject to intense investigation. Based on available data for the SARS-CoV-1 virus, we suggest how CoV-2 localization of RNA transcripts in mitochondria hijacks the host cell's mitochondrial function to viral advantage. Besides viral RNA transcripts, RNA also localizes to mitochondria. SARS-CoV-2 may manipulate mitochondrial function indirectly, first by ACE2 regulation of mitochondrial function, and once it enters the host cell, open-reading frames (ORFs) such as ORF-9b can directly manipulate mitochondrial function to evade host cell immunity and facilitate virus replication and COVID-19 disease. Manipulations of host mitochondria by viral ORFs can release mitochondrial DNA (mtDNA) in the cytoplasm and activate mtDNA-induced inflammasome and suppress innate and adaptive immunity. We argue that a decline in ACE2 function in aged individuals, coupled with the age-associated decline in mitochondrial functions resulting in chronic metabolic disorders like diabetes or cancer, may make the host more vulnerable to infection and health complications to mortality. These observations suggest that distinct localization of viral RNA and proteins in mitochondria must play essential roles in SARS-CoV-2 pathogenesis. Understanding the mechanisms underlying virus communication with host mitochondria may provide critical insights into COVID-19 pathologies. An investigation into the SARS-CoV-2 hijacking of mitochondria should lead to novel approaches to prevent and treat COVID-19. [ABSTRACT FROM AUTHOR]

Spectrum sharing and full duplexing are two promising technologies for alleviating the severe spectrum crunch that has threatened to blight the progress of future wireless communication systems. In this paper, we consider a two tier coexistence framework involving a collocated multiple-input-multiple-output (MIMO) radar system (RS) and a full-duplex MIMO cellular system (CS). Considering imperfect channel state information and hardware impairments at the CS, we focus on a spectrum sharing environment to improve the quality of service (QoS) for cellular users by designing $i)$ precoders at CS via the minimization of sum mean-squared-errors, subject to the constraints of transmit powers of the CS and probability of detection (PoD) of the RS, and $ii)$ precoders at the RS to mitigate the interference from RS towards CS. While the monotonically increasing relationship between PoD and its non-centrality parameter is exploited to resolve the PoD in terms of interference threshold towards the RS, a generalized likelihood ratio test for target detection is used to derive detector statistics of the precoded radar waveforms. Numerical results demonstrate the feasibility of the proposed spectrum sharing algorithms, albeit with certain tradeoffs in RS transmit power, PoD and QoS of cellular users. [ABSTRACT FROM AUTHOR]

The role of drug N‐acetylcysteine (NAC) in preventing contrast‐induced nephropathy (CIN) and kidney diseases has been investigated with the help of in vitro Raman spectroscopy and density functional theory (DFT). Renal dysfunction or kidney failure is diagnosed by an increase in serum creatinine (CRN). The exposure to contrast agents during angiography also causes an increase in serum CRN, a condition termed as CIN. NAC is given to such patients, as it is known to prevent the toxic effect of CRN, although its mechanism of action is not clearly known till date. In the present study, we have studied the interaction between CRN and NAC and tried to detect the formation of a stable complex between the two by analyzing the in vitro Raman spectra of aqueous solutions of CRN and NAC mixed in different molar ratios. From the Raman spectral analysis, it is observed that a stable complex is formed at 1:1 molar ratio of CRN and NAC. This complex has been synthesized in the laboratory, and upon drying, it is transparent, gel‐like in appearance, and slightly yellowish in color. The complex is hygroscopic and has much better water solubility than CRN. Fourier‐transform infrared (FT‐IR) and Raman spectral analyses of the synthesized complex show the structural changes taking place because of complexation and provide proof that the complex is stable at room temperature. DFT‐based studies on a number of plausible structures of the complex have also been done to determine the most stable structure of the complex, and the mechanism of its formation has been explored by transition‐state calculations. This study highlights the effective role of NAC in reducing the toxic effect of CRN as the water‐soluble complex of CRN, and NAC is likely to be removed through urine. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a full duplex (FD) multi-user non-orthogonal multiple access (NoMA) communication system based on the optimization of received signal-to-interference-plus-noise ratio (SINR) per unit power. Since the communication system operates in the FD mode, co-channel interference (CCI) and self-interference (SI) dominate the system’s performance. Accordingly, to combat the CCI, we adopt a game-theoretic approach and propose users’ clustering algorithms and to suppress the SI, we formulate an optimization problem to maximize the power-normalized SINR (PN-SINR). While the user clustering optimization problem is constrained by: 1) the successive interference cancellation (SIC) constraint and 2) two binary constraints for the allocations of uplink (UL) and downlink (DL) users, the PN-SINR problem is constrained by: 1) total transmit power budget at the base station and UL users; 2) the fundamental condition for the implementation of successive interference cancellation in the NoMA; and 3) the minimum fairness condition for the UL users. The original PN-SINR problem is non-convex and hence is converted into an equivalent subtractive-form problem, after which we propose an iterative algorithm to find the optimal power allocation policy. Properties of all the proposed algorithms are thoroughly investigated and the numerical results are provided. Based on the channel conditions and suppression level of SI and CCI, the superiority of the proposed FD-NoMA system over half-duplex NoMA and FD orthogonal multiple access systems is verified. [ABSTRACT FROM AUTHOR]

In this paper, I defend an account of the reasons for which we act, believe, and so on for any Ф such that there can be reasons for which we Ф. Such reasons are standardly called motivating reasons. I argue that three dominant views of motivating reasons (psychologism, factualism and disjunctivism) all fail to capture the ordinary concept of a motivating reason. I show this by drawing out three constraints on what motivating reasons must be, and demonstrating how each view fails to satisfy at least one of these constraints. I then propose and defend my own account of motivating reasons, which I call the Guise of Normative Reasons Account. On the account I defend, motivating reasons are propositions. A proposition is the reason for which someone Ф‐s when (a) she represents that proposition as a normative reason to Ф, and (b) her representation explains, in the right way, her Ф‐ing. As I argue, the Guise of Normative Reasons Account satisfies all three constraints on what motivating reasons must be, and weathers several objections that might be leveled against propositionalist views. [ABSTRACT FROM AUTHOR]