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Glomerular diseases are the leading drivers of nondiabetic chronic kidney disease disability-adjusted life years in resource-limited countries. Proper diagnosis and treatment relies on resources including kidney biopsy, ancillary testing, and access to evidence-based therapies.We conducted a cross-sectional internet-based survey cascaded through society mailing lists among nephrologists in countries of Asia, Africa, and Eastern Europe. We collected the data on respondent demographics, their ability to perform and appropriately interpret a kidney biopsy, and their access to complementary investigations and treatment practices.A total of 298 kidney care specialists from 33 countries (53.3% from Asia and 44.6% from Africa; 64% from academic or university hospitals) participated in the survey. Of these specialists, 85% performed kidney biopsy. About 61% of the respondents could not obtain a kidney biopsy in more than 50% of patients with suspected glomerular disease. About 43% of the respondents from Africa had access to only light microscopy. Overall, the inability to undertake and fully evaluate a biopsy and perform ancillary investigations were more profound in Africa than in Asia. Overall, 59% of participants reported that more than 75% of their patients meet the cost of diagnosis and treatment by out-of-pocket payments. Empirical use of immunosuppression was higher in Africa than in Asia. The main barriers for diagnosis and treatment included delayed presentation, incomplete diagnostic work-up, and high cost of treatment.Major system-level barriers impede the implementation of guideline-driven approaches for diagnosis and treatment of patients with glomerular disease in resource-limited countries.

Objective: To investigate the accuracy of Vesical Imaging-Reporting and Data System (VI-RADS) in detection of muscle-invasive bladder cancer (MIBC) we performed a systematic review and meta-analysis of the available literature. Materials and Methods: Scopus, Web of Science, PubMed, and EMBASE were searched up to 8 March 2021 for the studies evaluating the diagnostic performance of VI-RADS for the detection of MIBC. Inclusion criteria were patients with bladder cancer; index test of VI-RADS based on multiparametric MRI; reference test of histopathological findings from TURBT, re-TURBT, or cystectomy and study design of cohort. Case reports, review articles, and editorials were eliminated, as well as studies with insufficient knowledge to acquire TP, FP, FN, and TN values of VI-RADS. The MIDAS module of STATA was for statistical analysis. The heterogeneity was explored using subgroup analysis and meta-regression analysis. Results: Overall, 22 eligible studies, consisting of 2,576 participants and 5,414 MRI reports, were included in this meta-analysis. The area under curve (AUC) of VI-RADS at cut-point values of 3 and 4 were 0.93 (95%CI: 0.91, 0.95), 0.93 (95%CI: 0.90, 0.95), respectively. Based on Youden's J statistic, the optimal VI-RADS cutoff value for predicting MIBC was determined as 3 which granted a pooled sensitivity of 89% (95%CI: 87%, 91%; I2=48%) and a specificity of 84% (95%CI: 80%, 87%; I2=90%). Based on meta-regression, the sources of inter-study heterogeneity for VI-RADS ≥ 3 were the sample size > 70, study design, single-center vs multi-center, patient population characteristics (i.e., gender, age), reference standard, histology, magnetic strength, T2WI slice thickness, and the number of radiologists reporting the MRI results (P value ≤ 0.01). Conclusion: The VI-RADS demonstrates consistently high diagnostic accuracy to predict MIBC. This scoring system could be applied in standard staging MRI reports of bladder cancer and can be incorporated into future MIBC work up guidelines.

High performance acute toxic methanol sensor based on hydrothermally prepared hexagonal nanodisc (NDs) of ZnO/CdO/SnO2 (ZnCdSnO2 or ZCSO) was fabricated onto glassy carbon electrode (GCE). The characterization of ZCSO NDs in-terms of functional group analysis, binding energy evaluation, oxidation states, optical absorbance, crystallinity, structural morphology, and elemental compositions were performed by FTIR spectroscopy, X-ray photoelectron spectroscopy (XPS), UV-visible spectroscopy, XRD, FESEM-coupled-EDS analysis respectively. The current versus concentration plot was exhibited linear on a wide range of methanol concentration (0.01 nM to 0.1 mM) clarified as linear dynamic methanol detection range (LDR). Considering the ZCSO NDs-coated surface area onto GCE over the slope of LDR, noticeable methanol sensor sensitivity (4.5475 µAµM-1cm-2) was perceived. Besides this, a considerable lower limit (7.69±0.38 pM) of detection at signal/noise=3 is obtained. The overall results of methanol chemical sensor were found with satisfactory and acceptable results in terms of their reproducibility, sensitivity, stability, and response-time. Additionally, the assembled ZCSO NDs-coated electrode was validated with real environmental samples and result was found good and acceptable. On considering the outcome of applicability and the way of this sensor assembling, this unique method might be a potential technique in the field of portable sensor development for the safety of environmental and healthcare fields in a broad scale.

Inter-firm openness is critical to creating an open innovation ecosystem. However, a method for measuring openness among ecosystem firms has not been developed. We demystify the largely implicit openness construct by introducing a five-dimensional, 20-item Inter-Firm Openness Scale (IFO-Scale). Using three qualitative and four quantitative data sets from two innovation hubs: Macquarie Business Park (Australia) and Silicon Valley (USA), we present the development and validation procedures in three interrelated studies. Study 1 generates a descriptive model of an open innovation ecosystem, identifies the critical openness dimensions among ecosystem firms, and refines items for measurement. Study 2 examines dimensionality and internal construct validity. Finally, Study 3 establishes the nomological- and criterion-related external construct validity. The IFO-Scale replicates across samples and demonstrates strong psychometric properties. The measure aids managers in assessing the degree of inter-firm openness in their innovation ecosystems and enable researchers to test and advance open innovation theory.

We reviewed and analyzed the most effective methods to reduce infectious complications (IC) after transrectal prostate biopsy (TRPB). We included only prospective randomized-controlled trials in the analysis. The analysis neither demonstrated any superiority of fluoroquinolones over other antibiotic classes nor of targeted antibiotics over empiric regimens in men undergoing TRPB. However, longer course antibiotics (3 days or more) compared to single dose or day regimens, combination of fluoroquinolones with aminoglycosides compared to fluoroquinolones alone and povidone-iodine rectal cleansing compared to control significantly reduced IC following TRPB. A combination of addition of aminoglycosides to oral antibiotics for 3 days along with povidone-iodine rectal cleansing may be an optimum strategy to minimize the risk of IC after TRPB.

The steady decrease in the levelized cost of solar energy (LCOE) has made it increasingly cost-competitive against fossil fuels. The cost reduction is supported by a combination of material, device, and system innovations. To this end, bifacial solar farms are expected to decrease LCOE further by increasing the energy yield; but given the rapid pace of design/manufacturing innovations, a cost-inclusive optimization of bifacial PV systems at the farm-level (including land costs) has not been reported. In our worldwide study, we use a fundamentally new approach to decouple energy yield from cost considerations by parameterizing the LCOE formula in terms of “land-related cost” and “module-related cost” to show that an interplay of these parameters defines the optimum design of bifacial farms. For ground-mounted solar panels, we observe that the panels must be oriented horizontally and packed densely for locations with high “land-related cost”, whereas the panels should be optimally tilted for places with high “module-related cost”. For systems with relatively high “module-related costs” and for locations with |latitude| > 30°, the bifacial modules must be tilted ∼10°–15° higher and will reduce LCOE by 2–6% compared to their monofacial counterparts. The results in this paper will guide the deployment of LCOE-minimized ground-mounted tilted bifacial farms around the world.

The effective utilization of slag-based Silicon fertilizer (silicate fertilizer) in agriculture to improve crop productivity and to mitigate environmental consequences turns it into a high value added product in sustainable agriculture. Despite the integral role of soil microbiome in agricultural production and virtually all ecosystem processes, our understanding of the microbial role in ecosystem functions and agricultural productivity in response to the silicate fertilizer amendment is, however, elusive. In this study, using 16S rRNA gene and ITS amplicon illumina sequencing and a functional gene microarray, i.e., GeoChip 5, we report for the first time the responses of soil microbes and their functions to the silicate fertilizer amendment in two different geographic races of Oryza sativa var. Japonica (Japonica rice) and var. Indica (Indica rice). The silicate fertilizer significantly increased soil pH, photosynthesis rate, nutrient (i.e., C, Si, Fe, P) availability and crop productivity, but decreased N availability and CH4 and N2O emissions. Moreover, the silicate fertilizer application significantly altered soil bacterial and fungal community composition and increased abundance of functional genes involved in labile C degradation, C and N fixation, phosphorus utilization, CH4 oxidation, and metal detoxification, whereas those involve in CH4 production and denitrification were decreased. The changes in the taxonomic and functional structure of microbial communities by the silicate fertilizer were mostly regulated by soil pH, plant photosynthesis, and nutrient availability. This study provides novel insights into our understanding of microbial functional processes in response to the silicate fertilizer amendment in rice cropping systems and has important implications for sustainable rice production. Keywords: Microbial responses/feedbacks, Silicate fertilization, GeoChip, Functional genes, Illumina sequencing

The prospect of additional energy yield and improved reliability have increased commercial interest in bifacial solar modules. Recent publications have quantified the bifacial gain for several configurations. For example, a standalone, optimally-tilted bifacial panel placed over a flat ground (with 50% albedo) is expected to produce a bifacial energy gain of 30% (per module area). In contrast, self and mutual shading in a farm with periodically spaced panels reduces the bifacial gain to 10–15% (per farm area). Bifacial gain is negligible for vertical arrays—although the configuration is of significant interest since it can prevent soiling. Here, we calculate the bifacial gain of a solar farm where vertical arrays are placed over sculpted/patterned ground. We conclude that vertical panels straddling (upward) triangle-shaped ground maximizes the energy output. Our worldwide calculation with up-triangle ground configuration and 50% albedo leads to the following conclusion. Compared to a traditional tilted monofacial design, the bifacial gain is (i) small up to 20° latitude, (ii) increases to 50% at 40° latitude, and (iii) reaches up to 100% at 60° latitude. Overall, high bifacial gains are observed in many regions particularly those with moderate to low clearness index. The enhanced output, along with reduced soiling loss and lower cleaning cost of the ground sculpted vertical bifacial (GvBF) solar farm could be of significant technological interest, especially in regions such as the Middle East and North Africa (MENA) susceptible to significant soiling losses.

Nitrous oxide (N2O) is a major greenhouse gas (GHG) with high global warming potential. A majority of the N2O flux comes from agricultural sources, mainly due to nitrogen (N) fertilization. The soil N2O flux, induced by N fertilization, mainly originated from two different sources, i.e., fertilizer and soil organic nitrogen (SON). It is essential to know the individual contribution of these two different sources in total N2O flux for planning necessary mitigation strategies. It is also indispensable to know the seasonal difference of emission factors (EF) for having more accurate N2O inventory. Therefore, an experiment was conducted in a South Korean upland soil during summer and winter seasons using 15N labeled urea as an artificial N source and source specific N2O emissions were distinguished under different environmental conditions. To characterize the N2O emissions from urea, 0, 50, 100 and 200% of the Korean N recommendation rate was selected for specified crops. The Korean N recommendation rate for red pepper (Capsicum annuum) and garlic (Allium sativum) was 190 and 250 kg N ha−1, respectively. Direct emissions from urea were estimated from the difference of 15N2O flux emitted from 15N-urea treated soil and the natural abundance of 15N2O. From total N2O fluxes, urea originated N2O flux was 0.87% and 0.13% of the applied N in warm and cold seasons, respectively and the rest comes from SON. Nitrous oxide EF in the warm season was 2.69% of applied N and in the cold season that was 0.25%. Nitrous oxide fluxes showed a significant exponential relationship with soil temperature. The results show the necessity of considering the different N2O EF for warm and cold cropping seasons to reduce uncertainty in N2O inventory. The findings of this research may help better understand N2O source partitioning and the emission budget from warm and cold cropping seasons.

This paper evaluates the impact of Peer-to-Peer (P2P) energy trading among the smart homes in a microgrid. Recent trends show that the households are gradually adopting renewables (e.g., photovoltaics) and energy storage (e.g., electric vehicles) in their premises. This research addresses the energy cost optimization problem in the smart homes which are connected together for energy sharing. The contributions of this paper is threefold. First, we propose a near-optimal algorithm, named Energy Cost Optimization via Trade (ECO-Trade), which coordinates P2P energy trading among the smart homes with a Demand Side Management (DSM) system. Our results show that, for real datasets, 99% of the solutions generated by the ECO-Trade algorithm are optimal solutions. Second, P2P energy trading in the microgrid potentially results in an unfair cost distribution among the participating households. We address this unfair cost distribution problem by enforcing Pareto optimality, ensuring that no households will be worse off to improve the cost of others. Finally, we evaluate the impact of renewables and storage penetration rate in the microgrid. Our results show that cost savings do not always increase linearly with an increase in the renewables and storage penetration rate. Rather they decrease gradually after a saturation point.

Understanding the components of water consumption of a crop or pasture through evapotranspiration is important for improving water management. In this study the FAO dual crop coefficient methodology has been used in conjunction with a portable evapotranspiration chamber in-situ, to quantify the basal crop (Kcb) and soil evaporation (Ke) coefficients of a pasture as a function of leaf area index and a widely used spectro-optical reflectance index, NDVI. To facilitate the measurement of soil evaporation component, small segments of the green biomass of a target pasture canopy, Tall Fescue (Festuca arundinacea var. Dovey) were allowed to rapidly senesce by applying a commercial herbicide while preserving the soil moisture and canopy structure. The ratio between the transpiration and evapotranspiration components (Kcb/Kc) increased from 0.03 to 0.46 for zero to highest available vegetation cover (LAI from 0 to 4.22). A significant linear relationship was observed between Kcb and NDVI (R2 = 0.88) suggesting the possibility of using the latter, for example through remote sensing technologies, to determine the former.

The paradigm shift towards high data rate demands of mobile users in IMT-2020 commonly known as 5G, led to the possibility of using Aerial Base Stations (ABS) to fulfill such requirements. However, for implementation of ABS, an appropriate air-to-ground channel model is needed. It is an important factor to incorporate the understanding of the channel fading behavior before designing the system. In this article, we present novel channel propagation results obtained from ray tracing simulations for different environments, such as Suburban, Urban and Urban-High-Rise, according to ITU Radio-communication parameters. The details of different channel characteristics such as Spatial Correlation and Cumulative Distribution Function for Small Scale Parameters as Delay Spread and Angle-of-Arrival are presented for different ABS heights. We also focus on various channel modeling approaches and frameworks for 3D channel models.

Hydrogen sulfide (H2S) is a flammable, colorless and hazardous gas. Initially it was considered as an environment toxic gas; but, after its endogenous production discovery in plants, a wide variety of functions have been found associated with H2S. H2S plays an imperative role in the modulation of ripening and quality changes in various fruits and vegetables by regulating certain physiological aspects such as respiration, ethylene biosynthesis, color metabolism, enzymatic browning, softening, chilling injury and postharvest decay during storage. H2S also acts as a signaling molecule to combat against oxidative stress by scavenging reactive oxygen species (ROS) due to up-regulation of antioxidative enzymes activities. Reduced membrane permeability, inhibited lipid peroxidation, up-regulation of antioxidant activities and inhibition of ROS production eventually leads to reduced senescence having conserved quality with extended shelf or cold storage life of H2S treated fruits and vegetables. Potential of H2S in delaying ripening and reducing senescence of fruits and vegetables is generally accepted. However, it may be worth considering the commercial H2S application as a strategy of conserving external color, retarding senescence and reducing various physiological storage disorders of fruits and vegetables with acceptable consumer quality in the future. This review summarizes the possible role and mechanism of H2S in prolonging storage life and conserving the quality attributes of fruit and vegetable crops during shelf or low temperature storage.

Breast cancer [BC] is the deadliest neoplasm in women globally and the second leading cause of cancer associated deaths. Current treatment methods include chemotherapy, hormonal therapy, radiation therapy and surgery. However, BC has shown resistance to these therapies and are often associated with side effects, multidrug resistance, recurrence are the major issues in BC treatment. Currently, dietary phytocompounds have emerged as beneficial agents for the prevention and treatment of cancer because of their safe and cost effective nature. Ursolic acid [UA] is widely spread in fruits and vegetables having the ability to inhibit BC proliferation, angiogenesis and metastasis, arrest cell cycle, induced apoptosis, scavenge free radicals and regulate several anti-apoptotic and pro-apoptotic proteins. UA has also shown potential anticancer, anti-inflammatory and antioxidant activities in several human BC cells. This review paper encompasses the role of UA against BC and their mechanism of action in vitro and in vivo studies.

Over the past decades, with increasing steel manufacturing, the huge amount of by-products (slags) generated need to be reused in an efficient way not only to reduce landfill slag sites but also for sustainable and eco-friendly agriculture. Our preliminary laboratory study revealed that compared to blast furnace slag, electric arc furnace slag and ladle furnace slag, the Linz-Donawitz converter (LD) slag markedly decreased CH4 production rate and increased microbial activity. In the greenhouse experiment, the LD slag amendment (2.0 Mg ha−1) significantly (p

Amperometric microelectrode arrays (MEAs) interrogate the concentration at multiple positions simultaneously and with sufficient sampling rates, thus being able to capture fast transient gradients. However, sensitivity variability issues in amperometric MEAs degrade the reliability of the measurements, particularly at the small concentration scales found in physiological studies. This paper describes the development of on-chip platinum amperometric MEAs and in situ transient calibration for reliable measurement of physiological transient concentration gradients. The designed MEA geometry facilitates positioning near a 2D cell culture setup, and the proposed in situ transient calibration minimizes the effects of sensitivity variability, thus allowing for calculation of gradients based on concentration differences between closely spaced electrodes. The effectiveness of the MEA and the in situ transient calibration was evaluated by measuring controllably-generated gradients, and then calculating the difference between experimental and simulated data using normalized time analysis. Gradients generated by periodic uptake intervals as fast as 150 ms followed by recovery intervals of 60 s were measured over a spatial range of 70 μm, with spatial resolution of 35 μm, and sampling time and measurement time of 10 ms. Transient gradients of hydrogen peroxide were also measured above the surface of a 2D cell culture of human astrocytes, thus demonstrating the approach in actual physiological measurements.

The estimation of actual crop evapotranspiration (ETc) from any given land cover or crop type is important for irrigation water management and agricultural water consumption analysis. The main parameter used for such estimations is the crop coefficient (Kc). Spectral reflectance indices, such as the normalized difference vegetation index (NDVI) and the crop coefficient of a specific crop or pasture canopy are important indicators of ‘vigour’, namely the photosynthetic activity and rate of biomass accumulation. Measuring both parameters simultaneously, with a view to understanding how they interact, or for creating optical, surrogate indicators of Kc is very difficult because Kc itself is difficult to measure. In this study a portable enclosed chamber was used to measure ETc of a pasture and subsequently calculated Kc from reference evapotranspiration (ETo) data derived from a nearby automatic weather station (AWS). Calibration of the chamber confirms the suitability of the device to measure the amount of water vapour produced by local plant evapotranspiration, producing a calibration factor (C) close to 1 (C = 1.02, R2 = 0.87). The coincident NDVI values were measured using a portable active optical sensor. In a test involving a pasture (Festuca arundinacea var. Dovey) at two different stages of growth in two consecutive growing seasons, the NDVI and crop coefficients were observed to be strongly correlated (R2 = 0.80 and 0.77, respectively). A polynomial regression (R2 = 0.84) was found to be the best fit for the combined, multi-temporal Kc-NDVI relationship. The main advantages of this method include the suitability of operating at a smaller scale (

Background The universities of Bangladesh are closed for more than seventeen months due to the covid-19 pandemic. This prolonged detachment has psychological consequences among the students. This study assessed the anxiety level and its determinants among the undergraduate students of Bangladesh, along with constraints faced by them during e-learning. Methods A web-based cross-sectional survey among 206 undergraduate students was conducted using a well-structured questionnaire. Their anxiety level was estimated using Zung's self-rating anxiety scale (SAS) and determinates were identified by employing a Tobit model. The problem confrontation index (PCI) was used to rank the constraints. Results About 82.5% of the undergraduate students in Bangladesh are experiencing mild to extreme anxiety, while 14.08% are experiencing extreme anxiety. Students' gender, father's year of schooling, family size, residential area, academic year, current accommodation, and access to high-speed internet affect their level of anxiety. Learning alone at home, lacking access to learning resources and inaccessibility to other e-learning platforms are the top three constraints students faced during e-learning. Limitations Self-reported data, socio-demographic variables and online survey. Conclusion Covid-19 has been causing anxiety among the students. This study recommends providing better internet services for facilitating e-learning along with access to different e-learning platforms.

The evolution of transistor topology from planar to confined geometry transistors (i.e., FinFET, Nanowire FET, Nanosheet FET) has met the desired performance specification of sub-20 nm integrated circuits (ICs), but only at the expense of increased power density and thermal resistance. Thus, self-heating effect (SHE) has become a critical issue for performance/reliability of ICs. Indeed, temperature is one of the most important factors determining ICs reliability, such as Negative Bias Temperature Instability (NBTI), Hot Carrier Injection (HCI), and Electromigration (EM). Therefore, an accurate SHE model is essential for predictive, reliability-aware ICs design. Although SHE is collectively determined by the thermal resistances/capacitances associated with various layers of an IC, most researchers focus on isolated components within the hierarchy (i.e., a single transistor, few specific circuit configurations, or specialized package type). This fragmented approach makes it difficult to verify the implications of SHE on performance and reliability of ICs based on confined geometry transistors. In this paper, we combine theoretical modeling and systematic transistor characterization to extract thermal parameters at the transistor level to demonstrate the importance of multi-time constant thermal circuits to predict the spatio-temporal SHE in modern sub-20 nm transistors. Based on the refined Berkeley Short-channel IGFET Model Common Multi-Gate (BSIM-CMG) model, we examine SHE in typical digital circuits (e.g., ring oscillator) and analog circuits (e.g., two-stage operational amplifier) by Verilog-A based HSPICE simulation. Similarly, we develop a physics-based thermal compact model for packaged ICs using an effective media approximation for the Back End Of Line (BEOL) interconnects and ICs packaging. We integrate these components to investigate SHE behavior implication on ICs reliability and explain why one must adopt various (biomimetic) strategies to improve the lifetime of self-heated ICs.

With the rapidly growing interest in bifacial photovoltaics (PV), a worldwide map of their potential performance can help assess and accelerate the global deployment of this emerging technology. However, the existing literature only highlights optimized bifacial PV for a few geographic locations or develops worldwide performance maps for very specific configurations, such as the vertical installation. It is still difficult to translate these location- and configuration-specific conclusions to a general optimized performance of this technology. In this paper, we present a global study and optimization of bifacial solar modules using a rigorous and comprehensive modeling framework. Our results demonstrate that with a low albedo of 0.25, the bifacial gain of ground-mounted bifacial modules is less than 10% worldwide. However, increasing the albedo to 0.5 and elevating modules 1 m above the ground can boost the bifacial gain to 30%. Moreover, we derive a set of empirical design rules, which optimize bifacial solar modules across the world, that provide the groundwork for rapid assessment of the location-specific performance. We find that ground-mounted, vertical, east-west-facing bifacial modules will outperform their south-north-facing, optimally tilted counterparts by up to 15% below the latitude of 30 degrees, for an albedo of 0.5. The relative energy output is the reverse of this in latitudes above 30 degrees. A detailed and systematic comparison with experimental data from Asia, Europe, and North America validates the model presented in this paper. An online simulation tool (https://nanohub.org/tools/pub) based on the model developed in this paper is also available for a user to predict and optimize bifacial modules in any arbitrary location across the globe.

Device to device (D2D) communication has attracted enormous attention for future cellular networks which helps to increase the cellular capacity, improve the user throughput, and extend the battery lifetime of user equipments (UEs) by reusing the spectrum resources. However, D2D devices provide interferences in the system while reusing the resources. Proper control of interferences helps to increase the performance of the overall system. Adaptive power allocation among cellular and D2D users contributes to providing an efficient interference management system. In this paper, we propose an online power allocation method, i.e., multi-armed bandit solver for D2D communication. We explore the proposed method to improve the system throughput and D2D throughput as well. We incorporate the set of states for this learning algorithm with the appropriate number of system-defined variables, which increases the observation space and consequently improve the balance of spectrum usage. Finally, we compare our proposed work with existing distributed reinforcement learning and random allocation of resources. Simulation results depict that the proposed resource allocation method outperforms the existing works regarding overall system throughput as well as D2D throughput by efficiently controlling the interference levels.

In future remote healthcare monitoring system, it is necessary to constantly monitor the patients physiological parameters. For example, a pregnant woman parameters such as blood pressure and heart rate of the woman and heart rate and movements of fetal to control their health condition. To support the high-intensity and short-lived demands of these emerging applications, Narrowband Internet of Things (NB-IoT) is a promising technology that provides long-range communications at a low data rate for sensors with reduced device processing complexity and long battery lifetime. This paper aims to investigate the realistic performance of NB-IoT in terms of effective throughput, patient served per cell and latency in healthcare monitoring system with both in-band and stand-alone deployment.