Miracle-dz/UniFAR-FTUs huggingface dataset:
LS-GRUNet: Glucose Forecasting Using Deep Learning for Closed-loop Diabetes Management

Diabetes is a chronic condition which requires regular monitoring of glucose levels and accurate insulin dosing through multiple daily injections. Recent work has shown that continuous glucose monitoring (CGM) and automated insulin dosing enables better glycaemic control in Type 1 diabetes patients. The CGM sensors typically record interstitial glucose levels in a minimally invasive manner. However, this technique leads to a physiological delay between blood glucose levels and interstitial glucose levels, hence glucose forecasting is performed to account for this delay. In this work, we have introduced a multilayer deep neural framework with combination of long short-term memory (LSTM) with gated recurrent unit (GRU) to predict the future glucose level depending upon previous data such as glucose levels, meal information for a prediction horizon of 15 min,30 min and 60 min. This approach was tested on an insilico dataset of 10 Adult T1D scenarios created using the UVA/Padova simulator. Through a complete comparison in terms of root mean square error (RMSE), mean absolute relative difference (MARD) and mean absolute error (MAE), the results reveal decent improvement over existing approaches in the literature. For 15 min prediction horizon (PH) the RSME was 5.27 mg/dL, MAE was 4.04 mg/dL and MARD was 2.911% and for 30 min PH RMSE was 14.85 mg/dL, MAE was 11.04 mg/dL and MARD was 8.42%. Through a complete comparison of RMSE, MARD, and MAE, the results reveal considerable improvements over existing approaches in the literature.
Threats, Drivers, and Conservation Imperative of Agrobiodiversity

Agrobiodiversity underpins food, nutrition and livelihood security, ecosystem and environmental health, and climate change resilience but it is under threat of extinction. This paper highlights threats of agrobiodiversity, its drivers and conservation imperatives. Review shows prior to the green revolution, several crops and varieties were found in situ and on-farm but the number has declined since then. Extinction is contributing to decline in crop productivity and resilience and consequently the long-term sustainability of human wellbeing. Extinction is attributable to various natural and man-made factors. Various international and national level efforts are underway but not adequate to curb the loss. Therefore, further efforts are required to conserve and utilize agrobiodiversity, which will require concerted efforts in exploring agrobiodiversity, identifying drivers of loss and bolstering conservation efforts. This can be done through implementation of biodiversity-friendly legislations, actions and incentive mechanisms adhering to relevant global and national level policies, negotiations and conventions.
The Review of Depression and Self-Esteem

Despite the extensive literature on depression and self-esteem, the underlying relationship between them remains unclear. The purpose of the present study is to systematically summarize the models, effects, and relationship between depression and self-esteem. The results showed that there was the most support for the vulnerability model, which proposed that self-esteem had a large effect on depression, and less support for the scar model which assumed that depression affected self-esteem and minimal support for the common factor model. Meanwhile, despite the existence of the scar model, no studies have concluded that depression affects self-esteem. These findings are remarkable for furthering the understanding of the effects of depression on self-esteem and their implications for treatment.
Method for Spot Detection on Solar-like Stars

As a planet eclipses its parent star, a dark starspot may be occulted, causing a detectable variation in the light curve. This work describes how features on the surface of a solar-like star can be studied by using planetary transits. Images of the Sun were used in order to simulate such transits, with the planet being modeled as a dark disk at various positions along its orbit. From modeling of these transits, it might be possible to infer the physical properties of the spots, such as size, intensity, position, and temperature. Recent transit observations for HD 209458 were used as tests to the model.
Board # 100 : Research Design, Data Collection, and Assessment Methods for an Integrated STEM Education Model (Work in Progress)

The goal of this research is to assess the effectiveness of an integrated STEM education model. The study is being conducted under a three-year NSF-ITEST funded project (award #1513248), Teachers and Researchers Advancing Integrated Lessons in STEM (TRAILS). This research incorporates engineering design as a STEM subject integrator and scientific inquiry to provide an authentic learning context for promoting 21 st century skills and connections in STEM learning. In addition, the study seeks to assess effective strategies to increase STEM self-efficacy within science (biology or physics) and engineering technology education (ETE) teachers, and advance students’ learning of STEM content at schools in rural settings. In order to evaluate the effectiveness of the TRAILS model, researchers developed and adopted various measures and instruments. Data collection for the study includes utilizing the following: a) instruments measuring STEM lesson content knowledge (knowledge tests), b) attitudinal perceptions of teachers and students (pre/posttest surveys and delayed posttest surveys), c) rubrics for assessing 21 st century skills in project based learning, d) classroom observations, and e) student knowledge transfer problems. This variety of quantitative and qualitative data collection provides opportunities for triangulating data and analysis to ensure rigorous evaluation of TRAILS goals and outcomes. The quasi-experimental research design implements an experimental group in which teachers participate in professional development, an online community of practice, and implement integrated STEM lessons. A comparison group of teachers also participate in the data collection process but do not participate in professional development or any of the activities of the experimental group in cohort one. The research design including instruments utilized, the methods for assessing 21 st century learning skills, classroom observation, and knowledge transfer problems, will be described, including preliminary analysis procedures.
Prediction Model of Carbon Dioxide Concentration in Pig House Based on Deep Learning

The air environment (e.g., high concentration of carbon dioxide) in a pig house will affect the health conditions and growth performance of the pigs, and the quality of pork as well. In order to reduce the cumulative concentration of carbon dioxide in the pig house, the prediction model was established by the deep learning method to predict the changes of the carbon dioxide cumulative concentration in a pig house. This model will also be used for the real-time monitoring and adjustment of the concentration of carbon dioxide of the pig house. The experiment was designed to collect environmental parameters (e.g., temperature, humidity, wind speed, and carbon dioxide concentration) data in the pig house for several months. The ensemble empirical mode decomposition–gated recurrent unit (EEMD–GRU) prediction model was established in the prediction of carbon dioxide concentration in the pig house. The results show that compared with the other models, the prediction accuracy of the EEMD–GRU model is the highest, and the root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and r-squared (R2) of carbon dioxide concentration in autumn and winter are 123.2 ppm, 88.3 ppm, 3.2%, and 0.99, respectively. The RMSE, MAE, MAPE, and R2 for carbon dioxide concentration are 129.1 ppm, 93.2 ppm, 5.9%, and 0.76 in spring and summer. The prediction model proposed in this paper can effectively predict the concentration of carbon dioxide in the pig house and provide effective help for the precise control of the pig house environment.
FES cycling with electric motor assist

The aim of this study was to develop and test feedback control strategies for integration of elec- tric motor assist and functional electrical stimula- tion for paraplegic cycling. An integrated two-loop feedback control strategy is proposed, in which the electric motor is driven to provide feedback con- trol of cycling speed, and the cyclist's leg power is controlled by automatic variation of stimulation intensity. Representative experimental results are presented for one complete-lesion paraplegic sub- ject. The results show accurate feedback control of: cycle cadence; leg power; and external distur- bance rejection. We conclude that the addition of electric motor assist, with an integrated feedback control strategy, can compensate for external dis- turbances, it can greatly increase the overall power output and thereby signicantly extend the range of operation, and it can provide optimal operating conditions for the stimulated muscles.
On the Design of Beamforming Feedback for Wi-Fi Sensing

In recent years, channel state information (CSI) has been widely used for Wi-Fi sensing. Most of the existing Wi-Fi sensing researches are conducted based on the CSI matrix. It is noted that since the IEEE 802.11ac standard, beamforming weights feedback will be the only feedback type supported in the mainstream Wi-Fi standards. This letter aims to investigate Wi-Fi sensing based on beamforming weights feedback, where two feedback schemes namely Scheme 1 and Scheme 2 are analyzed and discussed. In Scheme 1, the transmit beamforming matrix (i.e., beamforming weight) is obtained by directly performing eigenvalue decomposition (EVD) on the channel autocorrelation matrix. As for Scheme 2, the transmit beamforming matrix is obtained based on performing EVD on the conjugate transpose of the channel autocorrelation matrix. The analysis shows that Scheme 1 retains the angle of departure (AOD), together with Doppler differences and time delay differences between different paths, while Scheme 2 can retain the entire AOD, Doppler, and time delay information. The effects of imperfect systems on sensing performance in practice are also discussed in this letter.
Current Evidence of Watermelon (Citrullus lanatus) Ingestion on Vascular Health: A Food Science and Technology Perspective

The amino acid L-arginine is crucial for nitric oxide (NO) synthesis, an important molecule regulating vascular tone. Considering that vascular dysfunction precedes cardiovascular disease, supplementation with precursors of NO synthesis (e.g., L-arginine) is warranted. However, supplementation of L-citrulline is recommended instead of L-arginine since most L-arginine is catabolized during its course to the endothelium. Given that L-citrulline, found mainly in watermelon, can be converted to L-arginine, watermelon supplementation seems to be effective in increasing plasma L-arginine and improving vascular function. Nonetheless, there are divergent findings when investigating the effect of watermelon supplementation on vascular function, which may be explained by the L-citrulline dose in watermelon products. In some instances, offering a sufficient amount of L-citrulline can be impaired by the greater volume (>700 mL) of watermelon needed to reach a proper dose of L-citrulline. Thus, food technology can be applied to reduce the watermelon volume and make supplementation more convenient. Therefore, this narrative review aims to discuss the current evidence showing the effects of watermelon ingestion on vascular health parameters, exploring the critical relevance of food technology for acceptable L-citrulline content in these products. Watermelon-derived L-citrulline appears as a supplementation that can improve vascular function, including arterial stiffness and blood pressure. Applying food technologies to concentrate bioactive compounds in a reduced volume is warranted so that its ingestion can be more convenient, improving the adherence of those who want to ingest watermelon products daily.
Unfolded Protein Response Differentially Modulates the Platelet Phenotype

Background: Unfolded protein response (UPR) is a multifaceted signaling cascade that alleviates protein misfolding. Although well studied in nucleated cells, UPR in absence of transcriptional regulation has not been described. Intricately associated with cardiovascular diseases, platelets, despite being anucleate, respond rapidly to stressors in blood. We investigate the UPR in anucleate platelets and explore its role, if any, on platelet physiology and function. Methods: Human and mouse platelets were studied using a combination of ex vivo and in vivo experiments. Platelet lineage-specific knockout mice were generated independently for each of the 3 UPR pathways, PERK (protein kinase RNA [PKR]-like endoplasmic reticulum kinase), XBP1 (X-binding protein), and ATF6 (activating transcription factor 6). Diabetes patients were prospectively recruited, and platelets were evaluated for activation of UPR under chronic pathophysiological disease conditions. Results: Tunicamycin induced the IRE1α (inositol-requiring enzyme-1alpha)-XBP1 pathway in human and mouse platelets, while oxidative stress predominantly activated the PERK pathway. PERK deletion significantly increased platelet aggregation and apoptosis and phosphorylation of PLCγ2, PLCβ3, and p38 MAPK. Deficiency of XBP1 increased platelet aggregation, with higher PLCβ3 and PKCδ activation. ATF6 deletion mediated a relatively modest effect on platelet phenotype with increased PKA (protein kinase A). Platelets from diabetes patients exhibited a positive correlation between disease severity, platelet activation, and protein aggregation, with only IRE1α-XBP1 activation. Moreover, IRE1α inhibition increased platelet aggregation, while clinically approved chemical chaperone, sodium 4-phenylbutyrate reduced the platelet hyperactivation. Conclusions: We show for the first time, that UPR activation occurs in platelets and can be independent of genomic regulation, with selective induction being specific to the source and severity of stress. Each UPR pathway plays a key role and can differentially modulate the platelet activation pathways and phenotype. Targeting the specific arms of UPR may provide a new antiplatelet strategy to mitigate thrombotic risk in diabetes and other cardiovascular diseases.
LoRa BASED SMART STREET LIGHT MANAGEMENT FRAMEWORK

— The idea of outlining a new framework for streetlights is to reduce the power consumption involved in the present lighting system which consumes about 80% of the world’s electricity. Smart lighting provides remote control mechanism that can be adjusted dynamically on the basis of environmental conditions. This can ensure longevity of the application and economic usage of power. This research aims to develop energy-efficient street lighting systems. In this research, a novel solution that utilizes the new upcoming technology known as Long-Range (LoRa) for communication and Arduino microcontroller for processing, is proposed. Light Dependent Resistor (LDR) and current sensor are used to sense the presence of illumination intensity based on which the switching ON/OFF of street light is performed automatically. LoRa technology supports communication upto 18 km when compared with the other traditional systems, namely Bluetooth, WLAN, and ZigBee. Due to this the usage of cloud support can be eliminated. In this research, a prototype is developed to analyze the performance of the proposed work in real time scenario.
Impact of Health on Worker Productivity: Evidence from South Asia

Health is an essential element that enables people to spend their life with great potential. A healthy life helps to live with confidence and self-esteem. At the macro level, the key foundation of economic development is health. On the micro-level, health c an efficiently ensure people’s productive and gratifying life. Health affects economic growth in any ways i.e. workers' poor health causes a reduction in productivity, on the other hand, due to healthy nutrition productivity rises. The core objective of conducting this study is to investigate the impact of human health on worker productivity. The health proxies that are used in this study is life expectancy. The indicator of education is the school enrollment at the secondary level; labor force and gross capital formation are also used as independent variables. The study used a panel of South Asian countries from 1991 to 2019, by applying panel OLS, fixed-effects model, random-effects model, and generalized method of moments (GMM). The results demonstrate that health and education significantly and positively influence productivity. This study recommends that the government of every South Asian country should take essential steps and make policies regarding improvement in health status and advancement in the education system.
An Analytical Study of Performance Evaluation of Mutual Funds

Mutual fund defined as mechanism of trust that pools the hard earn money of people in variety of schemes in accordance with specific objective. The industry of mutual fund witnessed an exceptional growth in 21 st century. There is number of scheme enhanced the mobilization of fund that provides boost to the industry. The contribution of mutual funds ensures growth in the global financial market. The mutual fund industry achieves major growth in emerging economies like India by incurring huge investments from investors. The ecosystem of AMCs generates opportunities for investors in terms of being safe and arbitration with limited risk. The research paper is an attempt to rank the selected mutual fund on the basis of performance evaluation. The researcher used method/tool such as sharpe ratio, treynor ratio, Jensen ratio and m squared ratio for performance evaluation and ranking selected mutual fund.
Inernet of Everything: A Solution to Mobile Banking using Voice Recognition

-The advancement in banking transaction system over the years has been enormous, and the needs for identifications of customer’s authentication, validation and confirmation are of utmost priority and should be dealt with judiciously. Mobile banking has emerged as one of the main division in digital world of financial transactions and consists of information inquiry, notifications and alerts, applications and payment transfer. Mobile based application is used for connecting customer handset with bank server for all such services in the banking industry. The current trend of Mobile banking as gone beyond the use of One Time Password (OTP) applications used by banks. The problem with current banking applications is that they send data directly to customer in plain text form compromising with security recognised as OTP in most of the online transaction. An online banking customer logging in to the bank’s website with username and password triggers a request to send an OTP to his or her registered mobile phone or the OTP may not be necessary after one or two transaction. There is every likely hold of Mobile phone been stealing, access by unauthorised person or being hacked. Upon receipt of a text message with the OTP, the customer enters it with an additional field on the banking site’s login page to complete the login process since your details are already on your phone. It could have been fine if
Interface Engineering for Enhanced Magnetic Vortex Pinning by 1D-BZO APCs in a Wide Angular Range

Microstructural analysis of the BaZrO3 (BZO)/YBa2Cu3O7 (YBCO) interface has revealed a highly defective and oxygen deficient 2-3 nm thick YBCO column surrounding the BZO one-dimensional artificial pinning centers (1D-APCs). The resulting semi-coherent interface is the consequence of the ∼7.7% BZO/YBCO lattice mismatch and is responsible for the low pinning efficiency of BZO 1D-APCs. Herein, we report an interface engineering approach of dynamic Ca/Cu replacement on YBCO lattice to reduce/eliminate the BZO/YBCO lattice mismatch for improved pinning at a wide angular range of the magnetic field orientation. The Ca/Cu replacement induces a local elongation of the YBCO c-lattice near the BZO/YBCO interface, thereby ensuring a reduction in the BZO/YBCO lattice mismatch to ∼1.4% and a coherent BZO/YBCO interface. This has resulted in enhanced pinning at B//c-axis and a broad angular range of B-field orientation. For example, the 6 vol.% BZO/YBCO film with interface engineering exhibits F p ∼158 GN/m3 at 65 K and B//c-axis, which is 440% higher than the ∼36.1 GN/m3 for the reference 6% BZO/YBCO sample, and enhanced Jc and F p in a wide angular range up to ∼ 80°. This result illustrates a facile scheme for engineering 1D-APC/YBCO interface to resume the pristine pinning efficiency of the 1D-APCs.
Extent of Variation Resilience in Strained CMOS: From Transistors to Digital Circuits

Process-related and stress-induced changes in threshold voltage are major variability concerns in ultra-scaled CMOS transistors. The device designers consider this variability as an irreducible part of the design problem and use different circuit level optimization schemes to handle these variations. In this paper, we demonstrate how an increase in the negative steepness of the universal mobility relationship improves both the process-related (e.g., oxide thickness fluctuation, gate work-function fluctuation), as well as stress-induced or reliability-related (e.g., Bias Temperature Instability or BTI) parametric variation in CMOS technology. Therefore, we calibrate the universal mobility parameters to reflect the measured variation of negative steepness in uniaxially strained CMOS transistor. This allows us to study the extent of (process-related and stress-induced parametric) variation resilience in uniaxial strain technology by increasing the negative steepness of the mobility characteristics. Thus, we show that variability analysis in strained CMOS technology must consider the presence of self-compensation between mobility variation and threshold voltage variation, which leads to considerable amount of variation resilience. Finally, we use detailed circuit simulation to stress the importance of accurate mobility variation modeling in SPICE analysis and explain why the variability concerns in strained technology may be less severe than those in unstrained technology.
Quick certification cellular phone ip contrasted to ranked cellular phone ip

Cellular phone IP represents the essential Transportability administration protocol to backing the Transportability in IP-based machines. Although, Cellular phone IP isn’t capable for quarantine sensitive Applications. The Quick Certification Cellular phone IP protocol (QICA) is usually recommended to dodge the problems of Cellular phone IP and to contest the necessities of time period Applications. So, QICA doesn’t want hierarchic specification as is that the container with best mini Transportability administration protocols, e.g. Rank Cellular phone IP (RCIP). A study show that QICA accomplish kind of like RCIP though the Cellular Nodule (CN) shift inside a site reside of 2 hierarchic slabs solely and surpass RCIP Rather. During the one paper we have a tendency to evolve a close exemplary to examine QICA and distinction it to RCIP. Our subject targets a distinction of the signal price of the 2 protocols. Our study displays that QICA plainly surpass RCIP with honor to the bundle cargo value. What is more, the region amend value though increasing QICA is commensurate to the region amend price exploitation RCIP. Therefore QICA is bigger productive than RCIP with honor to the entire signal price.
Origin of oxygen vacancies in resistive switching memory devices

The resistive switching state in Cr-doped SrTiO3 was induced by applying an electric field. This was done in ambient air and in an atmosphere of H2/Ar. The distribution of the thereby introduced oxygen vacancies was studied by spatially resolved X-ray fluorescence images. It was concluded that the oxygen vacancies were introduced in the interface between the SrTiO3 and the positively biased electrode.