Miracle-dz/UniFAR-FTUs huggingface dataset:
Wireless Communication Technologies for IoT in 5G: Vision, Applications, and Challenges

Communication technologies are developing very rapidly and achieving many breakthrough results. The advent of 5th generation mobile communication networks, the so-called 5G, has become one of the most exciting and challenging topics in the wireless study area. The power of 5G enables it to connect to hundreds of billions of devices with extreme-high throughput and extreme-low latency. The 5G realizing a true digital society where everything can be connected via the Internet, well known as the Internet of Things (IoT). IoT is a technology of technologies where humans, devices, software, solutions, and platforms can connect based on the Internet. The formation of IoT technology leads to the birth of a series of applications and solutions serving humanity, such as smart cities, smart agriculture, smart retail, intelligent transportation systems, and IoT ecosystems. Although IoT is considered a revolution in the evolution of the Internet, it still faces a series of challenges such as saving energy, security, performance, and QoS support. In this study, we provide a vision of the Internet of Things that will be the main force driving the comprehensive digital revolution in the future. The communication technologies in the IoT system are discussed comprehensively and in detail. Furthermore, we also indicated indepth challenges of existing common communication technologies in IoT systems and future research directions of IoT. We hope the results of this work can provide a vital guide for future studies on communication technologies for IoT in 5G.
A 30 Year Retrospective on Dennard's MOSFET Scaling Paper

Table I is reproduced from Dennard's paper and summarizes transistor or circuit parameter changes under ideal scaling conditions, whereis the unitless scaling constant. The tantalizing benefits of MOSFET device scaling immediately leap out from this table: as transistors get smaller, they can switch faster and use less power. But of course learning exactly how to make transistors smaller in a way that could be done practically in high volume manufacturing would take time. It would take time to develop lithographic techniques to pattern smaller feature sizes, to grow thinner gate oxides, and to reduce defects levels at these increasingly challenging dimensions. But this paper gave our industry a roadmap, a method for setting targets and expectations for coming generations of process technology. This paper gave us the more specific transistor scaling formula needed to continue Moore's Law, which was first articulated in a paper by Gordon Moore in 1965 and was in effect being followed by the semiconductor industry since the early 1960's. (To read reprints of Gordon Moore's 1965 and 1975 papers along with recent commentaries on Moore's Law, see the September 2006 issue of the IEEE Solid-State Circuits Society Newsletter.) Device or Circuit Parameter
Design of All-Optical Self Healing Ring for SDH Applications

We establishes a general model for the design of all-optical protection ring of synchronous digital hierarchly (SDH) in this paper. The signal-noise ratio (SNR) at 10 -9 bit error ratio (BER) is the critical parameter for determining the maximum ring size and obtained from the comprehensive investigations about amplified spontaneous emission (ASE), beating noise among various noise and the features of optical limiting amplifiers (OLA). A forward error correction (FEC) is deployed to increase the ring size and improve the transmission performance which is degraded due to the cascading of too many OLAs along protection ring.
Recidivism of Low-Risk People That Receive Residential Community-Based Correctional Programs: The Role of Risk Contamination

Objectives Placing low-risk individuals into residential community-based correctional programs often results in minimal or iatrogenic impacts upon recidivism. Contamination through exposure to higher-risk program participants is a mechanism that has been used to explain these effects. This study empirically explores this phenomenon. Methods A series of survival models examine data from low-risk paroled people released from a state’s prisons from 2005 to 2011 (n = 3,862) to assess the impact of residential community-based program participation upon recidivism. The daily rate of exposure to higher-risk people while attending programs is modeled for a subset of program participants (n = 202) to assess impacts upon time to failure within 18-months of program completion. Results Program participation increased the hazards of failure by approximately 66% for low-risk paroled people. Exposure to higher-risk people did not have significant impacts upon recidivism. Conclusions The current study coincides with past work demonstrating that policy makers and practitioners should be mindful of the potential iatrogenic or minimal recidivism effects associated with treating low-risk people through residential community-based programs. The mechanisms by which these effects are produced are in need of further exploration. Particular attention should be paid to whether programs can disrupt pro-social aspects of low-risk peoples’ lives.
Biopython: Comparing the DNA Polymerase I (polA) Gene of Thermophilic, Mesophilic, and Psychrophilic Bacteria

Biopython is a specialized Python tool for computational molecular biology. Various computational molecular analysis that can be performed using Biopython, such as reconstructing phylogenetic trees, multiple sequence analysis, generating complementary sequences, counting amino acids, etc. This technical notes paper describes in detail the procedures computational DNA sequence analysis using Biopython. The DNA polymerase I (polA) gene sequences of bacteria were used in this study to compare the differences between Thermophilic, Mesophilic, and Psychrophilic bacteria.
Reaction Kinetics and Process Model of the Polyacrylonitrile Fibers Stabilization Process Based on Dielectric Measurements

Microwave-based dielectric heating is a suitable method for energy- and time-efficient processes. Considering the energy required in the production of carbon fibers, it is evident that microwave-based dielectric heating during the different phases of the production needs to be considered too. Nevertheless, the dielectric properties of the processed material needs to be known for the design of an appropriate microwave applicator. When looking at the first stage in the production, the stabilization stage of the PAN fiber, the important data about the dielectric properties is very limited in literature. For this reason, first in-situ temperature-dependent measurements of the dielectric properties during the stabilization stage are presented. The impact of raising temperatures and chemical reactions on the dielectric properties of the heated PAN fiber is discussed. Secondly, the steps taken to set up the reaction kinetics from the dielectric loss point of view are given. This enables determination of the reaction degree as a function of the measured dielectric loss for the first time. The established correlation opens the potential for the application to processes such as an in-situ quality determination. The strong temperature impact on the process is shown, and reaction kinetics are analyzed accordingly. In a final third step, a heat transfer model is presented. It utilizes the evaluated reaction kinetics data and microwave heating, creating a first modelling approach for monitoring and controlling the desired fiber temperature, leading towards an online process.
A Joint Resource Allocation, Security with Efficient Task Scheduling in Cloud Computing Using Hybrid Machine Learning Techniques

The rapid growth of cloud computing environment with many clients ranging from personal users to big corporate or business houses has become a challenge for cloud organizations to handle the massive volume of data and various resources in the cloud. Inefficient management of resources can degrade the performance of cloud computing. Therefore, resources must be evenly allocated to different stakeholders without compromising the organization’s profit as well as users’ satisfaction. A customer’s request cannot be withheld indefinitely just because the fundamental resources are not free on the board. In this paper, a combined resource allocation security with efficient task scheduling in cloud computing using a hybrid machine learning (RATS-HM) technique is proposed to overcome those problems. The proposed RATS-HM techniques are given as follows: First, an improved cat swarm optimization algorithm-based short scheduler for task scheduling (ICS-TS) minimizes the make-span time and maximizes throughput. Second, a group optimization-based deep neural network (GO-DNN) for efficient resource allocation using different design constraints includes bandwidth and resource load. Third, a lightweight authentication scheme, i.e., NSUPREME is proposed for data encryption to provide security to data storage. Finally, the proposed RATS-HM technique is simulated with a different simulation setup, and the results are compared with state-of-art techniques to prove the effectiveness. The results regarding resource utilization, energy consumption, response time, etc., show that the proposed technique is superior to the existing one.
Mechanistic Kinetic Modelling Framework for the Conversion of Waste Crude Glycerol to Value-Added Hydrogen-Rich Gas

The kinetics for crude glycerol autothermal reforming was studied over S/C ratio of 2.6 and O2/C ratio of 0.125 using 5% Ni/CeZrCa catalyst. Both power law and mechanistic kinetic models were studied. The overall power law model for crude glycerol autothermal reforming was investigated with a pre-exponential factor of 4.3 × 1010 mol/gcat.min and activation energy of 8.78 × 104 J/mol. The reaction orders with respect to crude glycerol, water and oxygen are 1.04, 0.54 and 1.78 respectively. The power law model presented an absolute average deviation of 5.84%, which showed a good correlation between the predicted and experimental rate. Mechanistic models were developed for crude glycerol autothermal reforming. For steam reforming, the Eley–Rideal approach best described the reaction rate with the surface reaction being the rate-determining step (AAD < 10%). The kinetics of the total oxidation reaction was best described by the power law model with an AAD of less than 1%, whereas for the TOR process, the molecular adsorption of crude glycerol with an AAD of 14.6% via Langmuir Hinshelwood Hougen-Watson approach was best. CO2 methanation resulted in an AAD of 5.8% for the adsorption of carbon dioxide (CO2) by the Eley–Rideal mechanism.
The development of biodegradable hemostatic and absorbable sponges containing chlorhexidine digluconate and their in vitro characterization—A QbD approach

Medical sponges are one of the most common tools used in various fields of medicine and are used to close wound surfaces in burns and trophic ulcers, showing absorbent and antiseptic properties, and stimulate tissue regeneration. The aim of this study was to optimize the composition of medical sponges with chlorhexidine digluconate based on a material of natural origin xenoderma. The central composite design was used to establish the relationship between independent variables such as quantities of medical gelatin, propyleneglycol, and formaldehyde and dependent variables such as pH, the percentage of water absorption, the degree of in vitro degradation, thickness, and the time of complete dissolution, in order to obtain the optimal formulation using Response Surface Methodology. Using the concept of Quality by Design, the desired quality target product profile, critical quality attributes, risk assessment by Failure Mode Effects Analysis was determined that the number of excipients affects the pharmaco-technological parameters. It was found that sponges that contain 2% medical gelatin, 1% propyleneglycol, and 0.75% formaldehyde, are the best in composition, in terms of pH, the percentage of water absorption, the degree of in vitro degradation, thickness, the time of complete dissolution, in comparison with all other compositions.
Patients’ acceptance of video consultations in the mental health services: A systematic review and synthesis of qualitative research

Background Clinical effectiveness of video consultations in the mental health services is comparable with in-person consultations. Acceptance has typically been rated in surveys that do not give a deeper understanding behind the phenomenon. The aim of this synthesis is to explore mental health patients’ perceptions of factors that influence their acceptance of video consultations viewed from the perspective of the patient. Methods A literature search in scientific databases was conducted. Peer-reviewed reports of qualitative research exploring patients’ experiences with video consultations from the patients’ perspectives were included. Then a meta-summary and a taxonomic analysis were conducted. Results A total of 11 reports met the inclusion criteria. Through the analysis, a model was generated with five factors that precede each other and interact with each other. Patients thought video consultations were acceptable when (1) they experienced barriers and inconvenience to accessing the location of services, (2) they had already established a trustful relationship with their therapist, (3) technical interferences were minor and problems were resolved quickly, (4) patients expected a less personal meeting, and (5) the degree of the patients’ issues were less complex. Discussion This model is intended to help clinicians identify circumstances where offering video consultations make best sense to patients and help sustain meaningful use prospectively. When patients encounter barriers to in-person services, clinicians should consider offering video consultations when the technology is adequately integrated in practice, and it is perceived not to intervene with treatment or the therapeutic process.
DEVELOPMENT AND VALIDATION OF RAMIPRIL ESTIMATION FROM CAPSULES USING VISIBLE SPECTROPHOTOMETRIC METHOD

A simple, rapid, sensitive, extraction free and cost effective visible spectrophotometric method has been developed for the determination of Ramipril in bulk and capsule formulations. The proposed method is based on the formation of yellowish brown coloured species by the drug with Folin reagent and exhibits ג max at 456.5 nm. The calibration graph is linear over the concentration range of 16‐48µg/ml with Molar absorptivity of 4.98783X103 l/mol/cm and Sandell’s sensitivity of 0.08351 µg/cm2 0.001 abs. unit. The proposed method is applied to commercial available capsules and the results are statistically compared with those obtained by the UV reference method and validated by recovery studies. The results are found satisfactory and reproducible. The method is applied successfully for the estimation of the Ramipril in capsule formulations without the interference of excipients.
Design and analysis of rotating field eddy current probe for tube inspection

DESIGN AND ANALYSIS OF ROTATING FIELD EDDY CURRENT PROBE FOR TUBE INSPECTION By Junjun Xin Steam generator unit in nuclear power plant comprise thousands of heat exchange tubes whereby heat from primary coolant is transferred to water circulating on the secondary side. A variety of tube degradation due to mechanical vibration and chemical interactions compromises the integrity of steam generator tubes. The rupture of these tubes may result in leakage of radioactive water to the environment. Periodic inspections aimed at timely detection and characterization of the degradation is a key element for ensuring tube integrity and safe operation of nuclear power plant. Eddy current testing has proved to be an effective technique to detect defects occurring in the tube wall. In the past two decades, three types eddy current probes developed for steam generator tube inspection include bobbin coil probe, rotating probe and array probe. Each of these probes has their own limitations. The bobbin coil probe is insensitive to circumferential cracks, and rotating probe is slow and involves complex mechanical rotation whereas the array probe has poor resolution and high cost of instrumentation. This dissertation presents the design and validation of a new rotating field eddy current probe. The probe is composed of three phase rectangular windings and pickup sensor, that can be chosen to be a simple bobbin coil or a GMR array sensor placed at the probe center. The probe avoids mechanical rotation and has fast scan speed. The rotating field probe is sensitive to all orientation defects. The axial component of magnetic field along the tubing due to a defect is measured by the pickup sensor. The probe design and performance are evaluated using an experimental validated finite element model. A reduced magnetic vector potential formulation is used for simulating the different commercial probe as well as the proposed new probe design. A probe prototype is built to validate the simulation results with respect to different defects. A parametric study is conducted using the model to optimize the design and evaluate its performance. An encircling rotating field eddy current probe utilizing similar principles is also studied in this research. A design of a rotating field probe that encircles a cylindrical sample is presented and studied. Differences in the performance in cases of magnetic and nonmagnetic tube materials are described. Initial results show the feasibility of rotating field probes to detect a variety of defect geometries.
Nanophytomedicine in Clinical Management: An Introductory Evidence-based Review

Introduction: Herbal medicines are an important ingredient of traditional and alternative medicinal system and thus being used since ancient times. Owing to their characteristic of having lesser side effects and potential therapeutic effect they have drawn attention of pharmaceutical scientists from across the globe. Herbal medicines have now strongly captured a whooping US $62 billion market globally. Herbal medicines have been widely accepted of their potential to treat chronic diseases, low toxicity profile, cheap and wide availability etc. Methods: The Safety and efficacy of herbal drugs have played an important part in their successful commercialization. With the emergence and application of nanotechnology the bioavailability and bioactivity of herbal medicines have improved drastically. Results: Development of nano-phytomedicines by reducing their size to nano scale range, attaching it with polymers and by modifying their surface properties, solubility, permeability, eventually enhances the bioavailability of herbal formulations. Conclusion: Novel formulations like niosomes, liposomes, nanospheres, phytosomes etc. can be exploited in this area. However, novel nano-phytomedicines comes with its own pros and cons. This article extensively reviews herbal nano-medicines with its reported success and failures.
Machine-Learning-Algorithm to predict the High-Performance concrete compressive strength using multiple data

Purpose The compressive strength of concrete depends on many interdependent parameters; its exact prediction is not that simple because of complex processes involved in strength development. This study aims to predict the compressive strength of normal concrete and high-performance concrete using four datasets. Design/methodology/approach In this paper, five established individual Machine Learning (ML) regression models have been compared: Decision Regression Tree, Random Forest Regression, Lasso Regression, Ridge Regression and Multiple-Linear regression. Four datasets were studied, two of which are previous research datasets, and two datasets are from the sophisticated lab using five established individual ML regression models. Findings The five statistical indicators like coefficient of determination (R2), mean absolute error, root mean squared error, Nash–Sutcliffe efficiency and mean absolute percentage error have been used to compare the performance of the models. The models are further compared using statistical indicators with previous studies. Lastly, to understand the variable effect of the predictor, the sensitivity and parametric analysis were carried out to find the performance of the variable. Originality/value The findings of this paper will allow readers to understand the factors involved in identifying the machine learning models and concrete datasets. In so doing, we hope that this research advances the toolset needed to predict compressive strength.
Sensory Evaluation of Grip Using Cylindrical Objects

In order to clarify the grasping mechanism of tools and machine handles, sensory tests to evaluate the optimum grasping diameter have been performed on forty-three people from age seven to fifty-three. It was confirmed that the sensory evaluation of the optimum grasping diameter was difficult for children under age ten due to insufficient growth of skeletal structure. The optimum grasping diameter was evaluated for persons above age ten. The optimum grasping diameter depended on the hand size, and the dependency was marked for children under eleven. In the case of adults, the optimum grasping diameter depended on the dimensions concerned with the length of the hand but only depended slightly on the hand breadth or fist. The optimum grasping diameters evaluated for males were 30∼40mm, which were about 10% larger than those evaluated for females. As a result of investigating above data, it was found that the tube could be grasped well by a human hand if all fingertips and the entire palm area contact it.
A Multi-Center Study of CT-Based Neck Nodal Radiomics for Predicting an Adaptive Radiotherapy Trigger of Ill-Fitted Thermoplastic Masks in Patients with Nasopharyngeal Carcinoma

Significant lymph node shrinkage is common in patients with nasopharyngeal carcinoma (NPC) throughout radiotherapy (RT) treatment, causing ill-fitted thermoplastic masks (IfTMs). To deal with this, an ad hoc adaptive radiotherapy (ART) may be required to ensure accurate and safe radiation delivery and to maintain treatment efficacy. Presently, the entire procedure for evaluating an eligible ART candidate is time-consuming, resource-demanding, and highly inefficient. In the artificial intelligence paradigm, the pre-treatment identification of NPC patients at risk for IfTMs has become greatly demanding for achieving efficient ART eligibility screening, while no relevant studies have been reported. Hence, we aimed to investigate the capability of computed tomography (CT)-based neck nodal radiomics for predicting IfTM-triggered ART events in NPC patients via a multi-center setting. Contrast-enhanced CT and the clinical data of 124 and 58 NPC patients from Queen Elizabeth Hospital (QEH) and Queen Mary Hospital (QMH), respectively, were retrospectively analyzed. Radiomic (R), clinical (C), and combined (RC) models were developed using the ridge algorithm in the QEH cohort and evaluated in the QMH cohort using the median area under the receiver operating characteristics curve (AUC). Delong’s test was employed for model comparison. Model performance was further assessed on 1000 replicates in both cohorts separately via bootstrapping. The R model yielded the highest “corrected” AUC of 0.784 (BCa 95%CI: 0.673–0.859) and 0.723 (BCa 95%CI: 0.534–0.859) in the QEH and QMH cohort following bootstrapping, respectively. Delong’s test indicated that the R model performed significantly better than the C model in the QMH cohort (p < 0.0001), while demonstrating no significant difference compared to the RC model (p = 0.5773). To conclude, CT-based neck nodal radiomics was capable of predicting IfTM-triggered ART events in NPC patients in this multi-center study, outperforming the traditional clinical model. The findings of this study provide valuable insights for future study into developing an effective screening strategy for ART eligibility in NPC patients in the long run, ultimately alleviating the workload of clinical practitioners, streamlining ART procedural efficiency in clinics, and achieving personalized RT for NPC patients in the future.