Miracle-dz/UniFAR-FTUs huggingface dataset:
The importance of defining standards for optical diagnosis

Optical diagnosis has an increasingly important role in current endoscopy practice because of the development of advanced imaging techniques and breakthroughs in artificial intelligence (AI). Accurate optical diagnosis is an important skill to guide clinical decisions in endoscopy [1]. Accurate optical diagnosis helps in choosing the appropriate resection method and surveillance interval, thereby avoiding underand overtreatment, and saving costs. ESGE has developed a core curriculum for optical diagnosis practice across Europe for high quality optical diagnosis training [1, 2]. The development of easy-to-measure competence standards that are focused on Methodological framework for development of competence standards for optical diagnosis in gastrointestinal endoscopy: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement
Soybean pod and grain isoflavones accumulation during the filling period in field conditions

The objective of this work was to determine the isoflavones accumulation in soybean pods and grains during the filling period in field conditions. Pods of the same phenological stage (marked in R5, i.e. beginning of grain filling period) were collected at R5, R6 (full grain), and R7 (beginning of physiological maturity) stages. At each analyzed stage, grains always exceed pods isoflavone concentrations. A decreasing tendency of isoflavone concentration was observed in pods towards the late grain filling. In this maternal tissue, no acetyl glucosides at any stage or aglycones at physiological maturity were detected. In grains, glucosides, malonyl glucosides, and total isoflavones increased and acetyl glucosides decreased from R5 to R7, whereas aglycones increased to R6, but then decreased. It is concluded that grains are the main accumulation tissue of these bioactive compounds, whereas pods seem to contribute to their accumulation in advanced stages of grain development.
A 12-bit 100-ns/bit 1.9-mW CMOS switched-current cyclic A/D converter

This paper presents a high-speed high-resolution low-power CMOS switched-current cyclic analog-to-digital converter (ADC). The high performance is attributed to the use of the following components: (1) a high-performance residual amplifier which takes two clock cycles to double a current; and (2) an efficient cyclic redundant signed-digit algorithm which provides 1.5 bit resolution without using two matched reference currents. Simulation results show that the developed ADC achieves 12-bit resolution and a conversion rate of 100 ns/bit, where the low-cost MOSIS SCAN20 2 /spl mu/m CMOS process and 3.3 V supply voltage are employed. The converter has been fabricated and tested, Experimental results on the test chip are also presented. The test chip achieves 12 bit resolution with differential nonlinearity of 0.6 LSB and the integral nonlinearity of 0.5 LSB when operated at a 0.8 Msample/s conversion rate. The power consumption is 1.9 mW.
Classification and predictions of Lung Diseases from Chest X-rays using MobileNet

— Diagnosis of lung diseases cannot be analyzed only through the symptoms, but at the first level, CXR (Chest X-Rays) play in an important role on identifying the disease affected status. Various modalities such as CT, MRI, PET, etc., are there to analyze the lung diseases, but prominently the Chest X-rays acts as a first step of finding chest diseases due to the fact which is less expensive. The more advanced and effective Deep learning techniques are now emerging, is a boon of medical fields and for detecting the diseases more efficaciously. In this work, we proposed a Classification and prediction of Lung pathologies from Chest X-rays using use case MobileNet model (UCMobN). Through MobileNetmodel, multiple use cases can be designed. In this, the use case model is employed and datasets with the best accuracy of 86 %. In this, the use case model is employed and tested using NIH chest X-rays image datasets with the best accuracy of 86 %. We obtained an Area Under Curve (AUC) of 0.58 for Atelectasis, AUC of 0.67 for consolidation, 0.74 for Edema, AUC of 0.54for Effusion, AUC of 0.54 for Emphysema, AUC of 0.65 for Fibrosis, AUC of 0.57 for Infiltration and AUC of 0.51 for Mass.
SIW/HMSIW Bandpass Filters for Ka Frequency Band Serving Wireless Applications

—This paper describes a novel Substrate Integrated Waveguide (SIW) bandpass filter using Chebyshev approximation and Half Mode Substrate Integrated Waveguide (HMSIW)modeling technique. The developed 3 rd order filter structure uses an inductive iris and an inductive post station in a way it resonates in Ka frequency band serving wireless applications. The paper presents in details steps of the filter design formed by specific analytical equations to extract its different synthesizable parameters including coupling matrix, quality factor and initial geometric dimensions. The ideal frequency response of the filter is determined from an equivalent circuit that uses localized elements developed by AWR Microwave Software. High Frequency Structure Simulator (HFSS) is then employed to model the proposed filter structure and optimize its initial parameters until meeting the target specifications initially fixed in order to provide a high frequency response for the proposed filter design. Finally, the obtained results display a good performance for the proposed filter design and demonstrate a high usefulness for the employed technology that allows a low design volume.
Membership in employers’ associations and collective bargaining coverage in Germany

While there is a strong overlap between membership in employers’ associations and collective bargaining coverage, the overlap is far from being perfect. Using unique firm-level data from Germany, this study estimates the determinants of the membership in employers’ associations and the coverage by industry-level or firm-level agreements. The analysis particularly focuses on the various constellations of membership and collective bargaining status. The results show that firm-level worker representation, foreign ownership, work organization, firm size, age and East–West differences are important determinants. Altogether, the analysis demonstrates that a more differentiated picture of industrial relations can be obtained by considering both membership in employers’ associations and collective bargaining coverage.
Short-term BRT Passenger Flow Prediction with A Deep Learning Method

—Predicting passenger flow accurately can make full use of the existing traffic facilities to prevent emergencies from happening which is caused by heavy passenger flow. However, most of the existing methods to predict short-term passenger flow are shallow architecture, they cannot mine the relationship between short-term passenger and other external factors deeply enough. Therefore, we consider using a deep learning method to predict Bus Rapid Transit (BRT) passenger flow, which is different from previous methods to predict BRT passenger flow. We use a Prediction Stacked Auto Encoder (PSAE) model to mine BRT passenger flow features deeply. The top of the whole model establishes a prediction model for BRT passenger flow prediction from the extracted feature set. It uses a greedy layer-wise algorithm to train model parameters. Experimental results show that this method has good performance for predicting short-term BRT passenger flow.
Usability Issues when Applying Virtual Reality in Education and Training: A Case Study

Virtual Reality (VR) is an innovative technology that has found valuable application in the field of education. However, evaluation of the effectiveness of virtual environments, especially for training and education, is still an open issue. The study described here was performed within the European SAFE Vecwit project (Virtual Environment for Construction Workers Instruction and Training), aimed at the development of a virtual environment for the enhancement of risk perception and the consequent reduction of occupational injuries in construction workplaces. An experiment was carried out to assess system's usability and educational effectiveness of the environment. The evaluation highlights some relevant issues for VR environment design.
Do habitat use and parasitism lead to reinforcement in a flying squirrel hybrid zone?

Northern and southern flying squirrels are sympatric in Ontario due to climate change. In this area of range overlap hybridization occurs. I investigated potential species barriers in this recent hybrid zone. First I examined whether divergence in microhabitat use through time would lead to reinforcement of reproductive isolation. I found microhabitat variables to be weak predictors of trap-level species presence and found no evidence of divergence between species over 18 years. I also found latitude to be the strongest predictor of species occurrence across sites. Second, I tested whether parasite-mediated competition via the parasite, Strongyloides robustus, could maintain species barriers. I found a weak negative effect of S. robustus on northern flying squirrels, but I found a low parasite prevalence in southern flying squirrels compared to northern flying squirrels. Further, I found no evidence that presence of S. robustus would lead to competitive exclusion of northern flying squirrels from woodlots through apparent competition with southern flying squirrels. Therefore, divergence in microhabitat use and parasite-mediated competition do not appear to contribute to reproductive isolation of flying squirrels in Ontario.
Inventory policies and information sharing in multi-echelon supply chains

The aim of this article is to show how to modify a replenishment rule in relation to the operational information shared by suppliers. More specifically, we present a model of an Automatic Pipeline Variable Inventory and Order-Based Production Control System rule for a multi-echelon supply chain characterised by different increasing levels of shared information. A numerical study is presented to underline the performance differences for three variants of the smoothing order rule in terms of bullwhip reduction, inventory stability and operational and customer responsiveness. Results show how the effectiveness of a smoothing replenishment rule depends on the level of information sharing.
Implementing TQM initiatives in public service organisations: case of academic libraries

The paper seeks to discuss the development, main beliefs, and stages of total quality management (TQM) in a case of academic libraries by explaining their present strengths, weaknesses, possibilities and threats while implementing TQM initiatives. It also makes a comparison on how case organisations think about the definition of quality and TQM philosophy along with its applicability within the public sector. The study is qualitative. According to the results the most vital issues in TQM initiatives are its comprehensiveness, and its application in such a way which is appropriate for the organisation, with a logical way of operation and the participation of management and personnel. TQM is seen as quite applicable to the service sector however, it requires being reconciled with strategic management initiatives. The study could be quite valuable from a strategic perspective in providing guidelines to build up a proper plan for TQM initiatives more promptly.
Tunisian Dialect and Modern Standard Arabic Dataset for Sentiment Analysis : Tunisian Election Context.

With the growth in use of social media platform, Sentiment Analysis methods become more and more popular while for classical Arabic there are many datasets available, most of the Arab countries’ Dialects suﬀer from very limited resources for training an automated sys-tem. In this article, we study Sentiment Analysis applied on the Tunisian Dialect and Modern Standard Arabic by providing a manually annotated dataset. On this dataset, we performed feature selection and trained 6 classiﬁers to provide a benchmark for future studies.
Optimization of Wind Energy Penetration into the Grid with AI-based Microgrid Controller

Increased awareness about climate change and the demand for green energy has led to the proliferation of renewable energy generating units (REG) in power systems. The need for better system reliability requires utilities to connect these generating sources close to the load. One of the main problems with sources such as solar, wind turbines, fuel cells, and micro-hydro turbines is their integration into the existing power grid without significantly redesigning the system. An efficient method of solving this is to integrate these units into a microgrid. This method is the first step in the development of a smart grid. This study will study the effect of microgrid penetration controllers to achieve safe maximum instantaneous microgrid energy penetration. The microgrid models involved in this study include wind energy, solar energy, and energy storage integrated into the grid system. The Double Fed Induction Generator (DFIG) type wind turbine used is integrated into the dynamic model of the grid system by considering the turbine governor (TG), as well as the Automatic Voltage Regulator (AVR). The algorithm explicitly assigns the maximum allowable load on each bus. AI-based PSO algorithm has been used in the controller to obtain the maximum safe instantaneous wind penetration limit. The results seem pretty promising when tested on a modified IEEE 14-bus microgrid system.
Uncertainty with a potential Winter Storm : The East Coast Storm of 14 January 2008

The National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) and the NCEP Global Ensemble Forecast System showed the potential for a major East Winter Storm (ECWS) between 0000 UTC 14-15 January 2008. Initial forecasts showed some run-to-run inconsistencies with the cyclone track. This “model jumpiness” was a clear indication of uncertainty associated with this potential storm.
NUMERICAL SIMULATION OF WAVE PROPAGATION IN MIXED POROUS MEDIA USING FINITE ELEMENT METHOD

In this paper we research the problem of acoustics in porous media in three separated subdomains. In each region assumes different physical properties: geometry of the pore, viscosity of fluid places in the middle of the two elastic domains. In this task, we first consider the solution of differential equations. A mathematical model of these physical phenomena described by the initial boundary-value problems for complex systems of differential equations in partial derivatives. Then these equations were solved using two numerical methods: finite element method (FEM) and the traditional finite difference method (FDM). Solutions allows to analyse wave propagation phenomena in porous media. The polynomial functions were used as the interpolation basis-test functions in order to get weak solution for the finite element method. The numerical results of our simulation illustrate the method is obviously effective, especially if we want research physical problems with complex domains in 2D and 3D spaces.
Prenatal Exposure to Early Life Adversity and Neonatal Brain Volumes at Birth

Importance: Exposure to early life adversity alters the structural development of key brain regions underlying neurodevelopmental impairments. The extent that prenatal exposure to life adversity alters structure at birth remains poorly understood. Objective: To determine if prenatal exposure to maternal social advantage and psychosocial distress alters global and regional brain volumes and cortical folding in the first weeks of life. Design: A prospective, longitudinal study of sociodemographically-diverse mothers recruited in the first trimester of pregnancy and their infants who underwent brain magnetic resonance imaging scan in the first weeks of life. Setting: Mothers were recruited from local obstetric clinics from 2017-2020. Participants: Of 399 mother-infant dyads prospectively recruited into the parent study, 280 healthy, term-born infants (47% female, mean postmenstrual age at scan 42 weeks) were eligible for inclusion. Exposures: Maternal social advantage and psychosocial distress in pregnancy. Main Measures and Outcomes: Two measures of latent constructs were created using Confirmatory Factor Analyses spanning Maternal Social Advantage (Income to Needs ratio, Area Deprivation Index, Healthy Eating Index, education level, insurance status) and Psychosocial Stress (Perceived Stress Scale, Edinburgh Postnatal Depression Scale, Everyday Discrimination Scale, Stress and Adversity Inventory). Neonatal cortical and subcortical gray matter, white matter, cerebellar, hippocampus, and amygdala volumes were generated using semi-automated age-specific segmentation pipelines. Results: After covariate adjustment and multiple comparisons correction, greater social disadvantage (i.e., lower Advantage values) was associated with reduced cortical gray matter (p=.03), subcortical gray matter (p=.008), and white matter (p=.004) volumes and cortical folding (p=.001). Psychosocial Stress was not related to neonatal brain metrics. While social disadvantage was associated with smaller absolute volumes of the bilateral hippocampi and amygdalae, after correcting for total brain volume, there were no regional effects. Conclusions and Relevance: Prenatal exposure to social disadvantage is associated with global reductions in brain volumes and cortical folding at birth. No regional specificity for the hippocampus or amygdala was detected. Results highlight that the deleterious effects of poverty begin in utero and are evident in the first weeks of life. These findings emphasize that preventative interventions to support fetal brain development should address socioeconomic hardships for expectant parents.
Fabrication of Cost-Effective Prosthetic Arm Using Electroencephalography Signal

This paper entirely focuses on actuating prosthetic arm using EEG (Electroencephalogram) signal. EEG records the electrical activity of brain in micro-volts. Analyzing these electrical activities, it is possible to predict the generic movement of limbs. Brain-computer interface (BCI), which is a collaboration between a brain and a device, enables signals from the brain to direct some external activity through the actuation of a prosthetic arm in this research. Moreover, the current study attempts modeling a cheaper prosthetic arm and analyzing the accuracy of the arm’s movement.
Spectral Data for Plant Chlorophyll Assessment

An increasing role in plant phytodiagnostics becomes to play different spectrometric techniques used as a part of remote sensing applications. The radiation behavior of land covers and the spectral response to changing conditions lies at the root of these studies. The visible and near infrared (400 900 nm) measurements have proved abilities in vegetation monitoring. The reason is that this wavelength range reveals significant sensitivity to plant biophysical properties. The information is carried by the specific vegetation spectral characteristics which depend on such plant parameters as chlorophyll content, biomass amount, leaf area, etc. These parameters are associated with plant development and stress factors being closely related to vegetation physiological state. In our study, multispectral data of reflected, transmitted and emitted irradiance have been used to show the possibility for plant chlorophyll assessment. Different methods such as vegetation indices, red edge analysis and fluorescence spectra have been applied and compared.
Submicron CMOS technologies for low-noise analog front-end circuits

This paper presents a study of the noise behavior of submicron CMOS transistors, in view of applications to high-density mixed-signal front-end systems for high-granularity detectors. The goal of this work is extending the knowledge in this field, presently focused on 0.25 /spl mu/m processes, to the following generation of CMOS technologies (with 0.18 /spl mu/m minimum gate length). The white component of the noise voltage spectrum, which is most important for fast signal processing, and the 1/f noise contribution are experimentally characterized with noise measurements in a wide frequency range. The results of this analysis are used to establish low-noise design criteria concerning the choice of the polarity and of the channel dimensions (length and width) of the preamplifier input device in low-power operating conditions. A comparison with similar noise measurements on CMOS devices belonging to a 0.35 /spl mu/m process allows estimating the impact of gate-length scaling on both white and 1/f noise components. The noise radiation tolerance is also a key parameter for many front-end systems. It was evaluated by exposing the devices to high doses of ionizing radiation.
New direct torque control of induction motor for minimum torque ripple and constant switching frequency

In this paper, a direct torque control (DTC) method of an induction machine is proposed which enables the minimum torque ripple control, while maintaining constant switching frequency. Some drawbacks of the conventional DTC are the relatively large torque ripple in a low speed range and the variation of switching frequency according to the amplitude of hysteresis bands and the motor operating speed. In the proposed strategy, an RMS torque-ripple equation is derived using instantaneous torque equations and, at each switching cycle, an optimal switching instant which satisfies the minimum torque-ripple condition is determined based on the ripple equation. The proposed strategy improves the performance of the DTC by combining a low-torque-ripple characteristic in steady state with the fast torque dynamics. Experimental results prove the feasibility of the proposed strategy as compared with the conventional method.
Author-sourced capture of pathway knowledge in computable form using Biofactoid

Making the knowledge contained in scientific papers machine-readable and formally computable would allow researchers to take full advantage of this information by enabling integration with other knowledge sources to support data analysis and interpretation. Here we describe Biofactoid, a web-based platform that allows scientists to specify networks of interactions between genes, their products, and chemical compounds, and then translates this information into a representation suitable for computational analysis, search and discovery. We also report the results of a pilot study to encourage the wide adoption of Biofactoid by the scientific community.