Miracle-dz/UniFAR-FTUs huggingface dataset:
AN EXFOLIATIVE CYTOLOGICAL STUDY OF QUALITATIVE CHANGES IN BUCCAL MUCOSA CELLS OF TYPE 2 DIABETES PATIENTS IN SOUTH GUJARAT REGION

Corresponding Author: Dr. Neeraj Master, Tutor, Department of Anatomy, Surat Municipal Institute of Medical Education and Research (SMIMER), Surat-395010, Gujarat, India. E-Mail: dr.neerajmaster@yahoo.com Background: Diabetes mellitus is a metabolic disease and affects many organs of the body including oral mucosa. Exfoliative cytology can be used to detect the effects of diabetes on buccal mucosa cells. Aim: The present study will evaluate the qualitative changes (cytomorphology) of buccal mucosal cells in type 2 diabetic patients and compare that with the non-diabetic individuals of South Gujarat region. Materials and Method: Present study was done on 50 type 2 diabetic patients (case) and 50 healthy individuals (control) selected as per exclusion and inclusion criteria. Procedure was explained to the participants and informed written consent was taken. Buccal mucosa smears were taken and stained with Pap’s stain. 100 cells of each Pap stained smear was examined under a research microscope for various cytomorphological changes. Smears were examined for cell morphology like binucleation, pyknosis, perinuclear halo, cytoplasmic granules, karyolysis, karyorrhexis, cytoplsmic vacuoles and micronuclei. All data were noted and subjected to statistical analysis. Results: Mean values of binucleated cells, pyknotic cells, perinuclear halo, cytoplasmic granules, karyolytic cells, karyorrhectic cells, cytoplasmic vacuoles and micronuclei were noted in controls and cases. Significant differences in between non-diabetic control and diabetic cases for mean values of binucleation (p<0.001), pyknosis (p<0.001), perinuclear halo (p<0.001), cytoplasmic granules (p<0.001), karyolysis (p=0.026) and karyorrhexis (p<0.001) was observed. But no significant differences in the mean cells for cytoplasmic vacuoles (p=0.109) and micronuclei (p=0.176) were found between diabetics cases and non-diabetics control. Conclusion: The results of present study showed that buccal mucosa of diabetic case group is associated with significant differences in the mean values of qualitative changes like binucleation, pyknosis, perinuclear halo, cytoplasmic granules, karyolysis and karyorrhexis when compare to non-diabetic control group. Diabetes produces significant qualitative (cytomorphologic) changes in the buccal mucosa cells that can be documented by exfoliative cytology.
Theoretical-based on Learning Goal in E-learning System

E-learning system plays an important role as one of new trends of educational system. It is, however, lack of theory to support each learner's goal. There are a lot of theories that simulate learning environments and design each learner's role in order to achieve his/her own personnel goal. In this paper, we proposed learning goal and shows some examples on applying the goal in e-learning system.
Advanced glycation end products (AGEs)- mediated diabetic vascular complications

Diwesh Chawla*1; Ashok Kumar Tripathi2 ; Meera Sikka3 1Central Research Laboratory, Multi-disciplinary Research Unit, University College of Medical Sciences (University of Delhi) and G.T. B. Hospital, Dilshad Garden, Delhi-110095, India. 2Biochemistry and Immunology Laboratory, Department of Biochemistry, University College of Medical Sciences (University of Delhi) and G.T. B. Hospital, Dilshad Garden, Delhi-110095, India. 3Department of Pathology, University College of Medical Sciences (University of Delhi) and G.T. B. Hospital, Dilshad Garden, Delhi-110095, India. Correspondence to: Diwesh Chawla, Central Research Laboratory, Multi-disciplinary Research Unit, University College of Medical Sciences (University of Delhi) and G.T. B. Hospital, Dilshad Garden, Delhi 110095, India. Email: diweshchawla@yahoo.co.in Chapter 1 Advances in Biochemistry & Applications in Medicine
Reliable and robust automation of Cell Viability Assays with the epMotion® 5075t

Cell viability assays as the Promega® CellTiter-Blue® assay are widely used to determine potential toxic effects of various substances on cultured cells. As one step in characterizing the toxic potential of a certain compound, dose response curves are generated with different cell types, which can be a tedious procedure as it includes compound dilution series, preparing complex patterns of replicates, different compounds etc. Taken together with the fact that often these assays will be performed in 96 or 384 well plate formats to allow a certain throughput, this is a good reason for automating these assays to reduce manual workload and overall variability. In this study a dose response curve for Staurosporine was generated by challenging HepG2 cells grown in three 96 well plates with multiple concentrations of this cell death inducing compound and subsequent conduction of the above mentioned cell viability assay. The direct comparison of a manual procedure with an automated approach using the epMotion 5075t liquid handling system showed that besides the reduced hands on time, the epMotion could increase the robustness of the experiments. In a second set of fully automated experiments, HepG2 and HeLa cells were both treated with different concentrations of Staurosporine and Camptothecin, to show the compatibility of the epMotion system with different test setups. Here all scenarios resulted in an excellent assay robustness as indicated by high Z’-Factor values. The entire workflow – cell seeding, compound dilution plus addition to the cells and the addition of the assay reagents was carried out automatically with the epMotion 5075t liquid handling workstation, allowing to reduce the hands on time to a minimum. In total, these experiments emphasize the usability of the epMotion liquid handling workstation for cell based assays.
Diagnostic Sensitivity and Specificity of Serum Ascites Albumin Gradient (SAAG) in Patients with Ascites

OBJECTIVE: To determine the sensitivity and specificity of SAAG in predicting the presence of esophageal varices and to find out the association between level of SAAG and increase in portal vein diameter. STUDY DESIGN: Prospective-observational study. PLACE AND DURATION OF STUDY: Medical Unit III, JPMC Karachi from August 1999 to March 2000. PATIENTS AND METHODS: Patients with ascites were selected on the basis of selection criteria demonstrated by history, physical examination and ultrasonography. Ascitic fluid aspirated for DR and albumin, and simultaneously blood sample taken for total protein and albumin estimation at the time of paracentasis. After determining the level of SAAG upper GI endoscopy was performed. To determine the cause of ascites detailed history was taken and relevant investigations were carried out. At the end of our study sensitivity and specificity of serum ascites albumin gradient were determined in comparison of endoscopy findings. RESULTS: Among 50 subjects SAAG more than 1.1-g/dl was found in 30 (60%) patients and less than 1.1-g/dl in 20 patients (40%) of total 50 patients. Out of 30 patients with gradient more than 1.1-g/dl oesophageal varices present in 27 patients and portal vein diameter more than 1.3-cm present in 24 patients. The commonest cause of ascites among subjects with SAAG more than 1.1-g/dl was chronic liver disease with portal hypertension and the commonest cause of ascites among SAAG less than 1.1-g/dl was abdominal tuberculosis. The sensitivity and specificity of SAAG were 100% and 87.8% respectively. CONCLUSION: Serum ascites albumin gradient is a reliable marker to differentiate ascites into portal hypertensive and non-portal hypertensive etiology. Based upon our finding we conclude that the presence of oesophageal varices is significantly associated with high SAAG levels.
Impact of Land Use on Bacterial Diversity and Community Structure in Temperate Pine and Indigenous Forest Soils

Soil microbial communities are an important part of ecosystems that possess the capability to improve ecosystem services; however, several aspects of the ecology of forest soil bacterial communities are still unknown. Here, we investigated the impact of land-use change on soil bacterial communities and the soil characteristics. High-throughput sequencing was used to ascertain the bacterial diversity and canonical correspondence analysis was used to determine relationships between the bacterial communities and environmental variables. Our results show spatial heterogeneity in the distribution of the microbial communities and significant relationships between the microbes and soil characteristics (axis 1 of the canonical correspondence analysis (CCA) plot explained 64.55% of the total variance while axis 2 described 24.49%). Knowledge of this is essential as it has direct consequences for the functioning of the soil ecosystem.
Geospatial Analysis of Tree Species for Ecological Economics

Ecological economics requires spatial, biotic, and abiotic data, to be analyzed for management decision-making. The Tachigali Subvelutina, popularly known as charcoaler, is a promising tree species in Brazilian economy to energetic plantation. The charcoaler can be used as an energy source (production of firewood and charcoal), lumber and plump (making fence posts, pillars, construction and packaging), pulp and paper, landscaping and reforestation to recover, and environmental restoration. The aim of this study is to geospatial analyze the potential species distribution of Tachigali Subvelutina to determine areas for reintroduction, and to discover potential areas of conservation and forest management. Results presented five rules that best represented the six physical environment themes of the study.
KINETIC STUDY OF THE ADSORPTION OF 17A-ETHYNYLESTRADIOL (EE2) BY COMMERCIALLY AVAILABLE ACTIVATED CARBON

In recent years, scientists show great concern about the presence of endocrine disrupting compounds (EDCs) in the aquatic environment. EDCs include a family of emerging microcontaminants that have the ability to interact with the endocrine system of the organisms, causing various developmental and reproductive disorders. The occurrence of these substances in aquatic ecosystems may affect the endocrine system of humans and wildlife. EDCs enter the aquatic environment due to their insufficient removal by conventional wastewater treatment plants (WWTPs). The present study demonstrates the potential of activated carbon as adsorbent in removing synthetic estrogen 17α-ethynylestradiol (EE2) from aqueous phase. The adsorption kinetics data were analysed by two commonly used empirical kinetic models, namely the pseudofirst order (PFO) and pseudo-second order (PSO) kinetic adsorption model, using linear and nonlinear regression methods. It was found that PSO kinetic model fitted the adsorption of EE2 on activated carbon much better than PFO model.
The role of human metapneumovirus in pediatric respiratory tract infection in Qatar

Aim: The human metapneumovirus (hMPV) has been recently discovered as an etiological agent of acute respiratory infections in infants and children, with similar clinical symptoms to those caused by respiratory syncytial virus. The aim of this study was to determine the prevalence of hMPV and its potential role as a causative agent of respiratory tract infections in children in Qatar. Methods: In the present study, we examined 84 nasopharyngeal aspirates from children with respiratory tract infections, presenting at Al-Saad Pediatric Emergency Center in Doha, Qatar, as outpatients, for the presence of respiratory viruses. Results: A total of 56 out of 84 (66.7%) cases were positive for the presence of respiratory viruses. Out of the 56 positive cases 54 (96%) contained hMPV; whereas 12 out of 56 (21.4%) contained human parainfluenza virus. A total of 14 out of 56 of the positive patients were infected with more than one virus. hMPV was in samples infected with one or more respiratory tract infection viruse.
A Cascading Bandit Approach To Efficient Mobility Management In Ultra-Dense Networks

Efficient mobility management is a key problem in modern wireless networks with high node density. In this paper, we propose an online learning approach for mobility management in ultra-dense networks, based on the cascading multi-armed bandits model. The proposed Cost-aware Cascading Bandit Neighbor Cell List (CCB-NCL) mobility protocol relies on the active neighbor cell list to assist the user equipment to explore the base station selection sequentially. Simulation results show that the proposed algorithm reduces the handover latency with lower dropped call rate, hence it is a better fit to efficient mobility management.
Satisfaction among pregnant women towards antenatal care in public and private care clinics in Khartoum

This is a cross-sectional study conducted at Khartoum State, Sudan to assess the prevalence of satisfaction and associated factors among pregnant women attending at public and private clinics. The total number of 400 pregnant women were selected randomly, from ten public health care centers and ten private clinics. Trained interviewers visited each ANC unit on randomly selected days to identify the pregnant women. They conducted interviews at the time of exit using a structured and pre-tested questionnaire. Prevalence of full satisfaction was (22%) among pregnant women who visited public Antenatal Care Clinics, compared to (54%) among those who attended Private Antenatal Care clinics. Odds ratio of satisfaction among private clinics attendees was estimated to be approximately four times that in public ANC, P<0.001. There was significant association between satisfaction (the outcome) and factors that included: type of care (public and private), attitude of care provider, assessment of weight of pregnant women, and waiting time (P – values were < 0.001). *Corresponding author: Community Medicine Department, Faculty of medicine, University of Khartoum, Email:drziedan@gmail.com
Design of Multiphase Inverter System for Variable-Speed Applications Based on DSP and FPGA

Multiphase inverters have many beneficial features, such as higher reliability, greater efficiency and so on. High-speed sampling rate and multiple interfaces are necessary for multiphase inverter applications. In order to utilize the advantages of the flexibility and strong parallel computing capabilities of field-programmable gate array (FPGA). A system of multiphase inverter based on digital signal processor (DSP) and FPGA is presented in this paper for variable-speed applications. Simulation and experimental results verify the effectiveness of the system presented.
Analysis and Calculation of Transfer Functions Relating Power Supply Noise to Jitter Based on Output Buffer of LVSTL Interface

As the I/O speed increases up to multi-gigabit data rates, the jitter budget for I/O interface decreases, and precisely estimating jitter has a significant effect on designing communication systems with good robustness. Among all the causes of jitter in high-speed I/O interface, power supply noise is an important jitter source. This paper proposed an analytical calculation method of transfer functions relating power supply noise to jitter for low voltage swing terminated logic (LVSTL) interface of low-power double data rate fourth generation (LPDDR4). The simulation results show that the proposed analytical calculation method is in good agreement with the ADS simulated results.
k-Vectors: An Alternating Minimization Algorithm for Learning Regression Functions

The <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-vectors algorithm for learning regression functions proposed here is akin to the well-known <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-means algorithm. Both algorithms partition the feature space, but unlike the <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-means algorithm, the <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-vectors algorithm aims to reconstruct the response rather than the feature. The partitioning rule of the algorithm is based on maximizing the correlation (inner product) of the feature vector with a set of <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> vectors, and generates polyhedral cells, similar to the ones generated by the nearest-neighbor rule of the <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-means algorithm. Similarly to <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-means, the learning algorithm alternates between two types of steps. In the first type of steps, <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> labels are determined via a centroid-type rule (in the response space), which uses a surrogate hinge-type loss function to the mean squared error loss function. In the second type of steps, the <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> vectors which determine the partition are updated according to a multiclass classification rule, in the spirit of support vector machines. It is proved that both steps of the algorithm only require solving convex optimization problems, and that the algorithm is empirically consistent - as the length of the training sequence increases to infinity, fixed-points of the empirical version of the algorithm tend to fixed points of the population version of the algorithm. Learnability of the predictor class posit by the algorithm is also established.
Vulnerability of Adaptive Strategies of Keystroke Dynamics Based Authentication Against Different Attack Types

The attacks considered for keystroke dynamics study especially adaptive strategies have commonly treated impersonation attempts known as zero-effort attacks. These attacks are generally the acquisition of other users of the same database while typing the same password without intending to impersonate the genuine user account. To deal with more realistic scenarios, we are interested in this paper to study the robustness of an adaptive strategy against four types of imposter attacks: zero-effort, spoof, playback and synthetic applied to the WEBGREYC database. Experimental results show that 1) playback and synthetic attacks are the most dangerous and increase the EER rates compared to the other attacks; 2) we also find that the impact of these attacks is more pronounced when the percentages of imposter samples are greater than those of genuine ones; 3) the spoof attacks achieve alarmingly higher FMR, FNMR, and EER rates compared to zero-effort impostor attacks; 4) FMR, FNMR, and EER are higher when the percentage of attacks increases; 5) the attacks belonging to the same user are more dangerous than those of different users in particular when the percentage of the attacks increases. In light of our results, we point out that the traditional attacks considered in research on keystroke-based authentication must evolve according to the evolution of the attacks of nowadays password-based applications.
Object Recognition System using Deep Learning with Depth Images for Service Robots

In an aging society with fewer children, service robots are expected to play an increasingly important role in people's lives. To realize a future with service robots, a generic object recognition system is necessary to recognize a wide variety of objects with a high degree of accuracy. Therefore, this study employs deep convolutional neural networks for the generic object recognition system. To improve the accuracy of object recognition, both RGB images and depth images can be used effectively. In this paper, we propose a new architecture “Dual Stream - VGG16 (DS-VGG16)” for a deep convolutional neural network to train both the RGB images and depth images, and we also present a new training method for the proposed architecture. The experimental results indicate that the proposed architecture and training method are effective. Finally, we develop an object recognition system based on the proposed method that has an interface of robot operating system for integrating the system into service robots.
A Home Ledger Approach for IoT Enabled Devices

This paper discusses the application of IoT-devices with low energy consumption and high-performance computing capabilities, for processing blockchain data using Neo Virtual Machine (NeoVM). NeoVM is a turing-complete computing machine, designed for Neo Blockchain, specially designed for cryptographic and deterministic (verifiable) computation. A NeoVM program is called a NVM Script (or just Script), and it is often used together with Neo Blockchain application capabilities, being called a Smart Contract. Smart Contracts are already used on other blockchains such as Bitcoin (although not Turing-complete) for value transfers, through the availability of verifiable information, i.e., transactions and transaction blocks, on a global ledger. However, due to the high processing costs and low throughput capabilities of global public chains, most industrial applications of blockchain require the usage of private/permissioned chains, with the goal of providing high-speed and low-cost information persistance. This work proposes an IoT device prototype capable of delivering blockchain private access to home applications (also called a Smart Home), in a new concept defined as Home Ledger. Applications of Home Ledger include: local permissioned access to sensors and home devices (through state-of-the-art cryptography); guaranteed verification of local stored data (through redundancy and byzantine fault tolerance consensus mechanisms); lowcost and high-performance local registry (through usage of lowenergy microcontrollers); auditable cameras and local security on Home Ledger; global availability by interfacing with a global public ledger.
Electric vehicles as a mean for peak power curtailment in micro grids

This paper proposes optimization algorithm for charging and discharging of electrical vehicles, aimed at reducing of peaks in daily energy demand curve, taking into account the usual daily needs and requirements of EV owners. Objective function with set of constraints, which depends on electrical vehicle type, electrical vehicle owner needs and electric vehicle charging infrastructure, is minimized using quadratic programming algorithm. Implementation of this algorithm is done within graphical user interface, enabling input of data and resulting in appropriate solution for peak power curtailment in micro grids. Applying the aforementioned algorithm to the certain micro grid, which is presented in the paper, contributed to the notable reduction of the daily load peak. Required peak power has been successfully reduced from more than 800kW to about 700kW, which means that more than 12% of the required power has been provided by electric vehicles. In addition to simplified way of input data entry, this program has a high speed of calculation for a sizable number of electrical vehicles during a long observed time interval. Considering of long intervals is mandatory, since changes in the configuration of conveying electrical vehicles fleet is present in almost every moment.
Reverse Reconstruction of Anomaly Input Using Autoencoders

Autoencoders (AEs) are used in several applications, including dimension reducers and anomaly detectors. This paper introduces AEs as anomaly detectors. The proposed AEs are trained using both normal and anomalous data in a novel training manner. As a result, the trained AEs reconstruct normal input regularly and anomalous input irregularly, respectively. Consequently, reconstruction errors by anomalous input become increase and it is easy to detect as anomalous input. We implement anomaly detectors with the proposed AEs, and applying it to the MNIST and CIFAR10 datasets.