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Femoral neck fractures (FNF) are one of the most common fractures, with a projected increase in incidence with population growth and ageing. The Femoral Neck System (FNS) launched in 2019 was developed specifically for fixation of FNF with the purported advantages of providing both angular and rotational stability. We report our experience with the FNS and evaluate its effectiveness and associated complications.

The operating strategy of the power system is changing from the minimum cost to the minimum cost with a minimum emission approach as a result of growing worries about global warming and environmental change brought on by the combustion of fossil fuels. The generating scheduling problem becomes a multi-objective one as a result of the economic and emission objectives' inherent conflict. In this study, a multi-objective whale-differential evolution-genetic algorithm (WODEGA) is employed to produce an optimal solution that illustrates a potential trade-off between the unit commitment (UC) problem's emission and cost objectives. The environmental and economic dispatch problem with system and unit constraints is solved using the multi-objective WODEGA method. Main goal of research is to explore the problem of unit commitment and sub-problem of unit commitment i.e. economic dispatch.

A closed electromagnetic resonant chamber (RC) is a highly favorable artificial environment for wireless communication. A pair of antennas within the chamber constitutes a two-port network described by an impedance matrix. We analyze communication between the two antennas when the RC has perfectly conducting walls and the impedance matrix is imaginary-valued. The transmit antenna is driven by a current source, and the receive antenna is connected to a load resistor whose voltage is measured by an infinite-impedance amplifier. There are a countably infinite number of poles in the channel, associated with resonance in the RC, which migrate towards the real frequency axis as the load resistance increases. There are two sources of receiver noise: the Johnson noise of the load resistor, and the internal amplifier noise. An application of Shannon theory yields the capacity of the link, subject to bandwidth and power constraints on the transmit current. For a constant transmit power, capacity increases without bound as the load resistance increases. Surprisingly, the capacity-attaining allocation of transmit power versus frequency avoids placing power close to the resonant frequencies.

Numerical schemes based on the immersed boundary method (IBM) offer the advantages of avoiding the body-conformal structured or unstructured grid generation process in the complex tumor morphology. This study uses the finite-volume immersed boundary method (FV-IBM) to solve bioheat physics in actual liver tumor tissue. IBM is employed in this methodology to enforce the boundary effect on the non-body conformal Cartesian grid. The finite-volume method (FVM) is used as a numerical technique to discretize the governing equations. The validation and verification of the FV-IB method have shown that the scheme is second-order accurate. Furthermore, the numerical results in the spherical tumor model are in good agreement with previously reported results for steady and transient cases. Results for MNPs-based hyperthermia investigation with two heat source (Gaussian and uniform) distribution patterns in the liver tumor are in good agreement with the numerical solution of COMSOL Multiphysics. Thus, a simple and robust FV-IBM-based numerical scheme is proposed to solve the bioheat models in arbitrary tissue shapes.

Hereby, in this paper, we have reported synthesis of uniform spherical-shaped nanoparticles of zinc oxide via green method, as well as their photocatalytic activity. The nanoparticles of zinc oxide were synthesized utilizing flower extract of Rhododendron arboreumwhere it performs the function of reducing as well as capping agent. The synthesized nanoparticles were characterized by numerous spectroscopic techniques such as UV–Vis and FT-IR. Scanning electron microscope analysis of product revealed spherical zinc oxide nanoparticles. Energy-dispersive spectral analysis indicated elemental composition, i.e., oxygen and zinc. The green synthesized zinc oxide nanoparticles have been employed as nanocatalyst for photocatalytic degradation of two cationic dyes, i.e., Fuchsin basic and Malachite green dye. In addition, various physicochemical parameters such as effect of the dye concentration, catalyst dosage and pH have also been optimized indicating better performance of these nanoparticles. Zinc oxide nanoparticles showed 99.18% degradation of Malachite green dye and 99.272% degradation of Fuchsin basic dye. These nanoparticles have great potential candidate as developing catalyst for selective degradation of cationic dyes.

The ever-increasing demand for energy and power consumption due to population growth, economic expansion, and evolving consumer choices has led to the need for renewable energy sources. Traditional energy sources such as coal, oil, and gas have contributed to global pollution and have adverse effects on human health. As a result, the use of renewable energy for power generation has increased tremendously. One such area of research is solar irradiation prediction, which utilizes Artificial Intelligence and Machine Learning techniques. With the use of real-time predicted data, the digital twins are intended to add value to the organization by identifying and preventing problems, predicting performance, and improving operations. This paper provides an overview of various learning methods used for predicting irradiance and presents a new ensemble solar irradiance forecasting model that combines eight machine learning models to ensure model diversity. The model's most critical factors for predicting irradiance include temperature, cloudiness index, relative humidity, and day of the week. To conduct a comprehensive analysis, the proposed 8-Stacking Regression Cross Validation (8 STR-CV) model was tested using data from three different climatic zones in India. The model's high accuracy scores of 98.8% for Visakhapatnam, 98% for Nagpur, and 97.8% for the mountainous region make it a valuable tool for future prediction in various sectors, including power generation and utilization planning.

With the commencement of new technologies like IoT and the Cloud, the sources of data generation have increased exponentially. The use and processing of this generated data have motivated and given birth to many other domains. The concept of a smart city has also evolved from making use of this data in decision-making in the various aspects of daily life and also improvement in the traditional systems. In smart cities, various technologies work collaboratively; they include devices used for data collection, processing, storing, retrieval, analysis, and decision making. Big data storage, retrieval, and analysis play a vital role in smart city applications. Traditional data processing approaches face many challenges when dealing with such voluminous and high-speed generated data, such as semi-structured or unstructured data, data privacy, security, real-time responses, and so on. Probabilistic Data Structures (PDS) has been evolved as a potential solution for many applications in smart cities to complete this tedious task of handling big data with real-time response. PDS has been used in many smart city domains, including healthcare, transportation, the environment, energy, and industry. The goal of this paper is to provide a comprehensive review of PDS and its applications in the domains of smart cities. The prominent domain of the smart city has been explored in detail; origin, current research status, challenges, and existing application of PDS along with research gaps and future directions. The foremost aim of this paper is to provide a detailed survey of PDS in smart cities; for readers and researchers who want to explore this field; along with the research opportunities in the domains.

Globally, there is a rapid and significant change in the distribution of the urban population. Concerning which there is an increase in traffic rule violations in smart cities, resulting in traffic congestion and accidents. Anomalous vehicle recognition in smart cities is a critical issue that demands prompt and real‐time responsive solutions to address such situations. This article proposes an effective technique utilizing a persistent bloom filter to store and retrieve vehicle data, to improve road safety in urban locations. The technique employs distinct bloom filters to store vehicle data based on the hour, day, month, and year, which enables effective temporal membership queries on vast data. The proposed approach of anomalous vehicle recognition in smart cities using a persistent bloom filter is a memory‐efficient and intelligent monitoring technique. According to experimental analysis on large datasets such as “Montgomery County 911 Calls", “EMS and Fire Calls", “Seattle Fire Dept: 911", and “Traffic Violations in Montgomery County", the approach has the potential to boost query efficiency by up to 80% in comparison to conventional methods, in addition to decreasing storage space demands by up to 60%. The proposed approach has the potential to bridge the gap between research and practice in the field of urban safety and to enhance road safety while considering the dynamic changes in the road network. Employing traditional approaches to detect violations and monitor real‐time changes in a vast dataset of vehicles can be a laborious undertaking. The proposed technique provides a reliable and efficient approach to handling big data and improving traffic safety in smart cities. This research aims to create an intelligent monitoring system for recognizing anomalous vehicles in smart cities, utilizing memory‐efficient persistent bloom filters. The solution aims to improve road safety by implementing a real‐time, responsive approach with O(1) time complexity for detecting traffic rule violations in urban areas.

Molecular oxygen requires activation in order to be reduced, which prompts extensive searching for efficient and sustainable electrode materials to drive electrochemical oxygen reduction reaction (ORR), of primary importance for energy production and storage. A conjugated polymer PEDOT is a metal-free material for which promising ORR experimental results have been obtained. However, sound theoretical understanding of this reaction at an organic electrode is insufficient, as the concepts inherited from electrocatalysis at transition metals are not necessarily relevant for a molecular organic material. In this work, we critically analyze the basics of electrochemical ORR and build a model for our DFT calculations of the reaction thermodynamics based on this analysis. Altogether, this work leads to a conclusion that outer sphere electron transfer that currently attracts increasing attention in the context of ORR is a viable mechanism at a conducting polymer electrode.

The rising demand for enhanced catalytic pathways for activation of small molecules has invoked the design and synthesis of metal-free heterogeneous catalysts. Despite the great potential of these catalysts, very few precedents have been reported. Thus, we have prepared two boron doped carbon nitride catalysts with neighboring surface active Lewis acidic (B) and Lewis basic (N) sites and undoped carbon nitride for hydrogenation of styrene under mild conditions. The catalysts have been characterized by transmission electron microscopy (TEM), X-ray photoemission spectroscopy (XPS), X-ray diffraction (XRD) spectroscopy and Fourier transform infrared (FTIR) spectroscopy. Their catalytic mechanism is assessed by computational studies. DFT calculations reveal the favorable interaction of H2with adjacent B and N atoms, where relief in the angle strain is the driving force for the reaction.

Breast-conserving surgery is imprecise requiring re-excision in up to 40% of cases. One potential method of improving breast-conserving surgery accuracy is to use a beta particle detector to evaluate the surface of the excised tissue for any cancerous deposits, intraoperatively. Patients could be injected with a radiopharmaceutical that emits beta particles and preferentially accumulates within cancer cells. Cancer cells found on the surface of the excised tissue indicate that the surgery is incomplete. The purpose of this paper is to develop and analyze a novel single pixel beta sensitive detector. The detector is made up of a calcium fluoride europium doped [CaF2(Eu)] scintillation crystal, which is coupled to a silicon photomultiplier. A computational model of the detector response was derived from an empirically generated, 2-D, detector sensitivity map. This study determined that a CaF2(Eu) scintillator of 0.5-mm thickness provided superior beta to gamma detection ratio. According to the detector response, it is expected that with an acquisition time of 30 s, the tumor-to-background ratio of 5 or higher, and a normal breast tissue activity of 1.69 kBq/ml, less than 1 mm2 tumor detection is achievable. The result of this paper indicates that the radio-guided surgery with a CaF2(Eu) scintillation detector could be feasible to intraoperatively assess tumor margin involvement.

In the present research work, crystallographic, optical, molecular, morphological and magnetic properties of Zn1-xCuxO (ZnCu) and Zn1-x-yCeyCuxO (ZnCeCu) nanoparticles have been investigated. Polyvinyl alcohol (PVA) coated ZnCu and ZnCeCu nanoparticles have been synthesized by chemical sol-gel method and thoroughly studied using various characterization techniques. X-ray diffraction pattern indicates the wurtzite structure of the synthesized ZnCu and ZnCeCu particles. Transmission electron microscopy analysis shows that the synthesized ZnCu and ZnCeCu particles are of spherical shape, having average sizes of 27 nm and 23 nm, respectively. The incorporation of Cu and Ce in the ZnO lattice has been confirmed through Fourier transform infrared spectroscopy. Room temperature photoluminescence spectra of the ZnO doped with Cu and co-doped Ce display two emission bands, predominant ultra-violet near-band edge emission at 409.9 nm (3 eV) and a weak green-yellow emission at 432.65 nm (2.27 eV). Room temperature magnetic study confirms the diamagnetic behavior of ZnCu and ferromagnetic behavior of ZnCeCu.

Cyber-physical systems (CPS) are life-critical, complex systems that are formed by the in-depth integration of communication, computation, and control. With the availability of a plethora of data generation sources and medical devices across the globe, CPS are gaining a lot of eminence in healthcare. As CPS are a relatively new concept, originated in Industry 4.0, the number of surveys involving various aspects of the architecture framework is limited, especially in the field of healthcare. Additionally, there is no survey, covering the integration of CPS, cloud computing, and big data analytics for Healthcare 4.0. In this paper, an in-depth review covering all the possible aspects associated with CPS has been explored. Advances and technological progress of CPS in distinguished application domains along with the recent work in these domains are also presented. Finally, some of the most important challenges and open issues for future research are discussed to design high-quality frameworks for Healthcare 4.0.

Goss's wilt and leaf blight is a bacterial disease of maize (Zea maysL.) caused by the Gram‐positive bacterium Clavibacter michiganensissubsp. nebraskensis. Goss's wilt has re‐emerged as an important disease in the western United States and is spreading to other areas. Although the reasons for this re‐emergence are not completely known, it is important to understand the genetic basis of resistance to Goss's wilt. The objective of this study was to map the quantitative trait loci (QTL) underlying resistance to Goss's wilt. To achieve this objective, joint linkage and linkage mapping in 3 of the 25 nested association mapping families were used. Three biparental linkage mapping families including ‘B73’ × ‘Oh43’, B73 × ‘HP301’, and B73 × ‘P39’ were evaluated for Goss's wilt in Nebraska. Eleven QTL were detected on chromosomes 1, 2, 3, 4, 5, and 10 through joint linkage mapping. The joint linkage model explained 45% of the phenotypic variation for Goss's wilt. Linkage mapping in each of the three families identified nine, six, and four QTL in the families B73 × Oh43, B73 × HP301, and B73 × P39, respectively. Joint linkage and linkage analysis were also conducted within each environment to detect any environment‐specific QTL. However, most of the QTL were colocalized with QTL detected in across environment joint linkage and linkage mapping. These results will help us to understand the genetic basis of resistance to Goss's wilt better and may facilitate maize breeding programs to incorporate resistance to Goss's wilt into the maize germplasm.

Modeling and optimization of machining parameters are the indispensable elements in modern metal cutting processes. The present study realize the interaction of drilling input process parameters such as spindle speed, feed rate and number of holes and their influence on the surface roughness, diameter and position of hole obtained in drilling of mild steel. The contour plots were generated to highlights the interaction of process parameters as well as their effect on responses. An empirical model of surface roughness, diameter and position of hole was developed using response surface methodology (RSM). The model fitted and measured values were quite close, which indicates that the developed models can be effectively used to predict the respective response. The process parameters are optimized using desirability-based approach response surface methodology.

The aim of this study is to propose a new baroreflex sensitivity (BRS) index using improved Hilbert–Huang transform (HHT) using weighted coherence (CW) criterion and apply it to assess baroreflex in supine and standing postures. Improved HHT is obtained by addressing the mode mixing and end effect problems associated with empirical mode decomposition which is a required step in the computation of HHT and thus mitigating the unwanted low frequency component from the power spectrum. This study was first performed on synthetic signals generated using integral pulse frequency model and further extended to real RR interval and systolic blood pressure records of 50 healthy subjects, 20 post acute myocardial infarction patients undergoing postural stress from supine to standing position. Evaluation is also performed on standard EuroBaVar database, comprising of 21 subjects, under supine and standing positions. The results are (i) enhanced values of supine-to-standing low frequency BRS index (α-LF) equal to 1.78 and high frequency BRS index (α-HF) equal to 2.48 are obtained using improved HHT compared to standard HHT (α-LF=1.54, α-HF=2.36) and traditional power spectral density (α-LF=1.55, α-HF=2.34) for healthy subjects, (ii) there is an increased rate of change of LF/HF power ratios from supine to standing positions, and (iii) number of BRS responses obtained using CW criterion are greater than those obtained by using mean coherence criterion. In conclusion, the new BRS index takes into consideration the non-linear nature of interactions between heart rate variability and systolic blood pressure variability.

Cadmium-doped zinc oxide (CZO) has been the potential candidate for the fabrication of low-cost transparent conductors having applications in energy conversion devices such as thin-film solar cells and light-emitting diodes. In this work, the effect of different precursor solvents on the structural, morphological, and optical properties of sol?gel spin-coated CZO films was investigated. The X-ray diffraction study has revealed the hexagonal wurtzite crystal structure with crystallite size ranging from 45 to 49 nm for these films. The surface morphology of these films was analyzed by the atomic force microscopy. The precursor solvent effect was also analyzed using the UV?vis spectroscopy and fluorescence spectroscopic techniques. All the prepared films show the larger values of optical transparency (>80%) along with the shift in the fundamental absorption edge and the direct optical gap was found to be between 3.14 and 3.19 eV. The highly intense band edge emission for the sample was synthesized using the 2-ethoxyethanol while the presence of other defect-related bands in the other samples has been observed. The change in the precursor solvent volatility influences the crystal structure to favor the change in the density/type of defect states in the bandgap is used to discuss the present results. The formation of highly porous films will be suitable for gas sensor applications while the larger value of optical transparency and lower surface roughness have their probable application as the transparent electrodes in optoelectronics.

Changes in pedestrian-vehicle traffic conflicts in urban streets redesigned according to the principles of shared space were investigated with a recently developed pedestrian-vehicle conflict analysis (PVCA) method. In a first step, the PVCA method was revised to reflect more accurately the features of shared space; this revision included the definition of a systematic process for identifying conflict occurrences on the one hand and the full quantification of the conflict severity grading process on the other. Then the refined PVCA method was applied to a case study in London with video data from periods before and after the redevelopment of the Exhibition Road site from a conventional dual carriageway to a modern design with some elements of shared space. The results of the comparative analysis indicated a general decrease in traffic conflict rates as a result of the redesign but also highlighted specific issues that may require additional analysis.

The regioselective ring lithiation of BF3‐complexed 3‐picoline (1a), 3,4‐lutidine (1b), and 3,5‐lutidine (1c) was studied. The dilithiation of 1a, 1b, and 1cwas also investigated to experimentally explore the relative preference of the sites on the substituted pyridine ring for lithiation. The role of the complex‐induced proximity effect (CIPE) for inducing lithiation in these moieties was investigated using both experimental and computational studies.

Background

Review of the angiographic data of 118 live kidney donors was performed to assess the renal vessel anatomy; compare the findings with the perioperative findings using multislice spiral (MS) computed tomographic angiography (CTA) with the use of 50 mL of intravenous contrast; determine the sensitivity of this technique in the workup of live potential renal donors; and finally to discuss and compare the results of the present study with the reported results using single-slice spiral (SS) CTA, magnetic resonance angiography (MRA), and conventional angiography (CA).

We have investigated the possible antidiabetic properties of fruit extracts of Emblica officinalisGaertn., Terminalia chebulaRetz. and T. belliricaRoxb., individually and in combination (Triphala) in a high fructose diet induced rat model of insulin resistance. In the first part of the study, normal animals were studied for hypoglycemic activity. In the second part, animals were given a high fructose diet (HFD) for 40 days, for the last 20 days of which fruit extracts were also given. Body weight, fasting plasma glucose (FPG), and area under the curve (AUC) of the oral glucose tolerance test (OGTT) were assessed at the baseline, and at days 20 and 40. Fasting plasma insulin levels and the homeostasis model assessment (HOMA) resistance index were also assessed at baseline, 20 and 40 days. Fasting lipid levels were measured at the end of the study. During the first part of the investigation, in which extracts were given to normal animals, T. chebulashowed significant hypoglycemic activity. During the second part of the study, in which the extracts were given to HFD fed rats, T. chebulacaused a significant decrease in FPG and AUC. Emblica officinalisand Triphala caused a normalization of FPG. T. belliricacaused a reduction in AUC levels, but had no effect on FPG levels. T. belliricacaused a reduction in serum total cholesterol, triglyceride and low density lipoprotein levels. In conclusion, all three components of Triphala showed significant antidiabetic properties. T. bellirica, in addition, showed hypolipidemic activity.