Miracle-dz/UniFAR-FTUs huggingface dataset:
HDFCN: A Robust Hybrid Deep Network Based on Feature Concatenation for Cervical Cancer Diagnosis on WSI Pap Smear Slides

Cervical cancer is a critical imperilment to a female's health due to its malignancy and fatality rate. The disease can be thoroughly cured by locating and treating the infected tissues in the preliminary phase. The traditional practice for screening cervical cancer is the examination of cervix tissues using the Papanicolaou (Pap) test. Manual inspection of pap smears involves false-negative outcomes due to human error even in the presence of the infected sample. Automated computer vision diagnosis revamps this obstacle and plays a substantial role in screening abnormal tissues affected due to cervical cancer. Here, in this paper, we propose a hybrid deep feature concatenated network (HDFCN) following two-step data augmentation to detect cervical cancer for binary and multiclass classification on the Pap smear images. This network carries out the classification of malignant samples for whole slide images (WSI) of the openly accessible SIPaKMeD database by utilizing the concatenation of features extracted from the fine-tuning of the deep learning (DL) models, namely, VGG-16, ResNet-152, and DenseNet-169, pretrained on the ImageNet dataset. The performance outcomes of the proposed model are compared with the individual performances of the aforementioned DL networks using transfer learning (TL). Our proposed model achieved an accuracy of 97.45% and 99.29% for 5-class and 2-class classifications, respectively. Additionally, the experiment is performed to classify liquid-based cytology (LBC) WSI data containing pap smear images.
Physical Inactivity and Sedentary Behaviour among Panamanian Adults: Results from the National Health Survey of Panama (ENSPA) 2019

Physical inactivity (PI) has been described as an independent risk factor for a large number of major non-communicable diseases and is associated with an increased risk of premature death. Additionally, sedentary behaviour has been associated with increased overall mortality. We estimated the national prevalence of PI and sedentary behaviour using the Global Physical Activity Questionnaire version 2. Using unconditional logistic regressions, the possible risk factors for PI were assessed. Over half of the people included in this study (54.9%; 95% CI: 54.1–57.3%) were physically inactive, with the median time spent engaged in sedentary behaviour being 120 min per day. Statistically significant associations with PI were observed with regard to sex, living area, and alcohol consumption. PI prevalence in Panama was elevated and showed a sex difference (women: 64.7%, 95% CI: 63.7–66.7%; men: 43.4%, 95% CI: 41.5–47.5%). According to our analysis of three-domain-related physical activities, the main contribution to the total estimated energy expenditure of physical activity/week came from the transport domain, followed by the work/household domain, and the least significant contributor was consistently the domain of exercise- and sports-related physical activities.
A Surge in Malaria Cases in the Eastern Health Region of Saudi Arabia During the COVID-19 Pandemic

Background Malaria transmission was stopped on most of the vast area of the Kingdom of Saudi Arabia. However, the pandemic of coronavirus disease (COVID-19) has negatively affected the efforts to control malaria. For instance, COVID-19 was reported to induce a relapse of malaria that is caused by Plasmodium vivax. Furthermore, physicians’ attention toward COVID-19 can only result in neglect and delayed diagnosis of complicated malaria cases. These factors, among others, might have contributed to an increase of malaria cases in Dammam, Saudi Arabia. Thus, this study was conducted to examine the effects of COVID-19 on malarial cases. Methods The medical records of all patients who were treated at Dammam Medical Complex for malaria between July 1, 2018, and June 30, 2022, were reviewed. Malaria cases were compared between the pre-COVID-19 period (between July 1, 2018, and June 30, 2020) and the COVID-19 period (between July 1, 2020, and June 30, 2022). Results A total of 92 malaria cases occurred in the total study period. There were 60 cases of malaria in the COVID-19 period as opposed to only 32 cases in the pre-COVID-19 period. All the cases were imported from the endemic Saudi southern areas or from outside the country. Eighty-two patients (89.1%) were males. Most of them were Sundaneses (39 patients, 42.4%), Saudis (21 patients, 22.8%), and tribal peoples (14 patients, 15.2%). Fifty-four patients (58.7%) were infected with Plasmodium falciparum. Seventeen patients (18.5%) were infected with Plasmodium vivax. Another 17 patients (18.5%) had a mixed infection with both Plasmodium falciparum and Plasmodium vivax. A trend toward more infected stateless tribal patients was observed in the COVID-19 period compared to the pre-COVID-19 period (21.7% vs 3.1%). A similar trend was noticed for mixed malarial infections with both Plasmodium falciparum and Plasmodium vivax (29.8% vs 0%) with a P value of less than 0.01. Conclusion Malaria cases were almost doubled during the COVID-19 pandemic as compared to the pre-pandemic era signifying the negative effects of the pandemic on malaria epidemiology. The cases increased for a variety of causes that include alternation of health-seeking behaviors, changes in healthcare structures and regulations, and the interruption of malaria preventive services. Future research is needed to study the long-term effects of the changes imposed by the COVID-19 pandemic and to mitigate the effects of any future pandemic on malaria control. As two patients from our cohort were diagnosed with malaria based on blood smears, although they had negative rapid detection tests (RDTs), we recommend testing all the patients who are suspected to have malaria with both RDTs and peripheral blood smears.
A magnetic lattice and macroscopic entanglement of a BEC on an atom chip

Atom chips provide a convenient platform to study ultracold quantum gases and their interactions with electromagnetic fields, surfaces, micro-magnetic structures, superconducting circuits and nanomechanical systems. The research work presented in this thesis is classified in two major categories. The first part is focused on the development and construction of a permanent magnetic lattice on an atom chip and the study of trapped atoms in the permanent magnetic lattice potential. In the second part, a new experiment is proposed to create a macroscopic entanglement between the flux state of a superconducting loop and a Bose-Einstein condensate (BEC) on a superconducting atom chip. The permanent magnetic lattice potential is produced by applying a uniform bias magnetic field to a grooved silicon structure coated with a permanent magnetic film. The magnetic film consists of a multilayer structure of GdTbFeCo with perpendicular intrinsic magnetization. The permanent magnetic structure is mounted beneath a current carrying wire structure glued to a ceramic insulator. The current carrying wires assist in the preparation of the ultracold atoms and for loading into the magnetic lattice. In addition, the current carrying wires are used to produce a BEC in a Zwire magnetic trap. The magnetic lattice potential is produced by a one-dimensional array of highly anisotropic and extremely tight magnetic microtraps of period 10 μm. A detailed study of the reflection dynamics of atoms in the magnetic lattice potential is presented along with numerical simulations. Finally, the trapping of atoms in the permanent magnetic lattice at a distance less than 5 μm from the surface of the atom
Adaptive Load Shedding as Part of Primary Frequency Response To Support Networked Microgrid Operations

Global changes in the deployment of distributed energy resources, control and communications technologies, business models, and regulatory policy are increasing the operational options for future distribution systems. One such option is the coordinated operation of distributed resources to form microgrids and networks of microgrids to support traditional bulk power systems during normal operations and critical end-use loads during outages. While individual standalone microgrids have been extensively studied and deployed, the coordinated operation of networked microgrids is operationally more challenging due to the dynamic boundaries and changing mix of generation resources. This paper presents a method of using a distributed control architecture to support primary frequency response in networked microgrids operations. The support of primary frequency response is accomplished using the Open Field Message Bus reference architecture and Grid Friendly Appliance controllers.
Numerical Gradients and Extremum Estimation with U-statistics

U-statistics are often used in semiparametric estimation in a variety of settings. An important obstacle to their widespread use is the computational cost | particularly when the kernel of the U-statistic is non-smooth (and smoothing is not desirable since it further increases computational complexity). In this paper we study the properties of an alternative procedure: nite-dierence derivative approximations to evaluate the derivatives of U-statistic based objective functions and the use of these approximations in gradient-based optimization routines. We nd that the existing guidelines in the literature for the choice of the step size for numerical dierentiation are excessively conservative. While most analyses employing U-statistics suggest a choice of the step size of order n 1=4 , our ndings show that uniform consistency of estimated derivatives (and the consistency of the resulting extremum estimator) is maintained even when the step size is chosen to be of order log n 2 =n 2 . This implies that the step size can be chosen to approach to zero at a rate that is faster than the sample size. We illustrate our results with a Monte-Carlo study of a U-statistic based estimator for a semiparametric model with random censoring.
Effect of Decoration of C@TiO2 Core-Shell Composites with Nano-Ag Particles on Photocatalytic Activity in 4-Nitrophenol Degradation

Photoactive TiO2 materials based on a C@TiO2 core-shell structure synthesized according to the bottom-up strategy using a spherical resin core were presented in relation to commercial TiO2 (P25) used as a reference material. The studied TiO2 materials were modified with Ag nanoparticles using two alternative methods: impregnation and precipitation. Depending on the deposition technique used, different distributions of the Ag modifier were achieved within the TiO2 structure. As confirmed by X-ray diffraction (XRD) and scanning electron microscopy (SEM) measurements, the precipitation technique resulted in the formation of almost twice smaller, highly dispersed Ag nanoparticles compared to impregnation. Furthermore, the effect of the performed modification on the textural properties (low-temperature N2 adsorption) and surface composition (X-ray photoelectron spectroscopy) was determined. The phase composition of the TiO2 support as well as the dispersion of the Ag modifier significantly affected the energy gap determined from UV–Vis spectra and, consequently, their performance in the process photodegradation of 4-nitrophenol tested as a model molecule. In the case of the @TiO2 material modified with highly dispersed Ag, significantly higher photoactivity in the visible light range was observed than in the presence of analogous P25-based materials.
A greedy approach based algorithm for the vertex cover problem

The vertex cover problem is NP complete problem; we use approximation algorithms to find near optimal solution of the vertex cover problem. In this paper we are presenting a greedy algorithm for finding a near optimal cover for a given graph G = (V, E). The development of the algorithm is based on greedy approach and the graph is represented in form of its adjacency matrix. The proposed algorithm finds a minimum vertex cover in all known examples of graphs.
An Acute Bout of Endurance Exercise Does Not Prevent the Inhibitory Effect of Caffeine on Glucose Tolerance the following Morning

Caffeine reduces glucose tolerance, whereas exercise training improves glucose homeostasis. The aim of the present study was to investigate the effect of caffeine on glucose tolerance the morning after an acute bout of aerobic exercise. Methods: The study had a 2 × 2 factorial design. Oral glucose tolerance tests (OGTT) were performed after overnight fasting with/without caffeine and with/without exercise the evening before. Eight healthy young active males were included (Age 25.5 ± 1.5 years; 83.9 ± 9.0 kg; VO2max: 54.3 ± 7.0 mL·kg−1·min−1). The exercise session consisted of 30 min cycling at 71% of VO2max followed by four 5 min intervals at 84% with 3 min of cycling at 40% of VO2max between intervals. The exercise was performed at 17:00 h. Energy expenditure at each session was ~976 kcal. Lactate increased to ~8 mM during the exercise sessions. Participants arrived at the laboratory the following morning at 7.00 AM after an overnight fast. Resting blood samples were taken before blood pressure and heart rate variability (HRV) were measured. Caffeine (3 mg/kg bodyweight) or placebo (similar taste/flavor) was ingested, and blood samples, blood pressure and HRV were measured after 30 min. Next, the OGTTs were initiated (75 g glucose dissolved in 3 dL water) and blood was sampled. Blood pressure and HRV were measured during the OGTT. Caffeine increased the area under curve (AUC) for glucose independently of whether exercise was done the evening before (p = 0.03; Two-way ANOVA; Interaction: p = 0.835). Caffeine did not significantly increase AUC for C-peptides compared to placebo (p = 0.096), and C-peptide response was not influenced by exercise. The acute bout of exercise did not significantly improve glucose tolerance the following morning. Diastolic blood pressure during the OGTT was slightly higher after intake of caffeine, independent of whether exercise was performed the evening before or not. Neither caffeine nor exercise the evening before significantly influenced HRV. In conclusion, caffeine reduced glucose tolerance independently of whether endurance exercise was performed the evening before. The low dose of caffeine did not influence heart rate variability but increased diastolic blood pressure slightly.
Assessment of the Diagnostic Utility of GeneXpert Mycobacterium tuberculosis/Rifampicin (MTB/RIF) Assay in the Suspected Cases of Tuberculous Meningitis

Introduction: Tuberculous meningitis (TBM) is a manifestation of extrapulmonary tuberculosis (EPTB) caused by Mycobacterium tuberculosis (MTB). The central nervous system is involved in about 1%-2% of all current tuberculosis (TB) cases and about 7%-8% of all EPTB. if not treated early, TBM leads to a high rate of neurological sequelae and mortality. Objective: This study aimed to assess the diagnostic performance of the GeneXpert MTB/rifampicin (RIF) assay in patients with TBM. Methods: A total of 100 suspected TBM cases were enrolled from various departments at tertiary care hospital, Bhopal, Madhya Pradesh, India, and classified as definite, possible, or probable TBM. The clinical samples were tested for microbiological and other cerebrospinal fluid (CSF) testing. Results: Out of 100 cases, 14 (14%) were classified as definite TBM, 15 (15%) were having probable TBM, and 71 (71%) were having possible TBM. Out of a total of 100 participants, all were negative for acid-fast bacilli (AFB) staining. Of the 100 cases, 11 (11%) were positive by mycobacterium growth indicator tube (MGIT) culture, of which only four (36.36%) were positive by GeneXpert MTB/RIF. GeneXpert MTB/RIF detected three (3%) cases that were negative by MGIT culture. Ten (90.9%) of the 11 MGIT-positive culture isolates were found to be RIF sensitive while one (9.1%) was found to be RIF resistant. Three cases tested positive/sensitive by the GeneXpert MTB/RIF but negative by MGIT culture. Six (85%) of the seven GeneXpert MTB/RIF positive cases were RIF sensitive while one (15%) was RIF resistant. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy were 36.36% (95% Confidence Interval (CI) (10.93% to 69.21%)), 96.63% (95% CI (90.46% to 99.30%)), 57.14% (95% CI (25.50% to 83.85%)), 92.47% (95% CI (88.70% to 95.06%)) and 90% (95% CI (82.38% to 95.10%)) for GeneXpert MTB/RIF assay, compared with MGIT culture as the reference standard. Conclusion: Our study found that the sensitivity is lower when compared to culture, so using GeneXpert MTB/RIF alone is not recommended. Overall performance of GeneXpert MTB/RIF assay is noteworthy. The GeneXpert MTB/RIF assay is a potentially accepted test for obtaining an earlier diagnosis, and if it tested positive, the treatment should begin immediately. However, culture must be performed in GeneXpert MTB/RIF negative cases.
Study on Optimal Regular Deployment Patterns of Wireless Sensor Network

Wireless sensor network is a popular technology nowadays, having a wide range of application in many fields. The deployment of sensor nodes is a key problem of the technology, it has a great important influence on the network's function and life. The regular deployment is a common one of the node deployment patterns, classical regular deployment includes regular triangle, square, rhombus and equilateral hexagon, but now there is little research into the unregular equilateral hexagon in equilateral hexagon pattern. We investigated the unregular equilateral hexagon in this study. On the basis of the existing research findings, we made derivation to a conclusion that which pattern is the best when the sensing radius and the communication radius have a different proportion and did the simulation.
Extended Kalman Filter on SE(3) for Geometric Control of a Quadrotor UAV

An extended Kalman filter (EKF) is developed on the special Euclidean group, SE(3) for geometric control of a quadrotor UAV. It is obtained by performing an extensive linearization on SE(3) to estimate the state of the quadrotor from noisy measurements. Proposed estimator considers all the coupling effects between rotational and translational dynamics, and it is developed in a coordinate-free fashion. The desirable features of the proposed EKF are illustrated by numerical examples and experimental results for several scenarios. The proposed estimation scheme on SE(3) has been unprecedented and these results can be particularly useful for aggressive maneuvers in GPS denied environments or in situations where parts of onboard sensors fail.
Knowledge, attitude, and practice of healthcare providers regarding the Hepatitis B infection and vaccine at Al-Salama Hospital-Ameria, Baghdad City, October-November 2022, cross-sectional study

Background: One of the deadliest forms of viral hepatitis, the hepatitis B virus, poses a severe threat to human health. Because they frequently come into contact with bodily secretions, especially blood, that are contaminated with the virus, health providers are frequently deals with that secretions. Precautions like personal safety measures and vaccinations can be avoided. Objective: To determine the health providers knowledge, attitude, and practice about avoiding hepatitis B infection and getting the immunization against infection in Al- Salama-Amriya hospital, Baghdad. Materials and Methods: A cross-sectional study including (154) health providers how work in different health institution in Amira Baghdad city included (Al Salama hospital (90 persons), primary care (44 persons) and specialist dental care centers (20 persons), During October and November 2022,. The information was collected by Using a questionnaire, included the information about the knowledge, attitude, and practice of health provider regarding the infection by Hepatitis B, immunization and demographic information. The study data were presented using a descriptive summary created in the excel software's 10 window utilizing frequencies, proportions, and percentages. Each subject gave their verbal consent, and the study kept the individuals' identities anonymous. Results: Our study including (154) health providers are medical staff (59) and (95) paramedical staff, the overall knowledge scoring of them is (68%), overall attitude scoring is (75%), and the overall practice is (58%), among the medical staffs only (15%) had undergone screening for HBV, and (67%) had completed the three doses in other side the paramedical without history of screening for HBV with (37%) had completed the three doses. Conclusion: Over all attitude of health providers is more than the knowledge and practice (75%), (68%) and (58%) respectively with low rate of vaccination specially paramedical staff.
The AI Learns to Lie to Please You: Preventing Biased Feedback Loops in Machine-Assisted Intelligence Analysis

Researchers are starting to design AI-powered systems to automatically select and summarize the reports most relevant to each analyst, which raises the issue of bias in the information presented. This article focuses on the selection of relevant reports without an explicit query, a task known as recommendation. Drawing on previous work documenting the existence of human-machine feedback loops in recommender systems, this article reviews potential biases and mitigations in the context of intelligence analysis. Such loops can arise when behavioral “engagement” signals such as clicks or user ratings are used to infer the value of displayed information. Even worse, there can be feedback loops in the collection of intelligence information because users may also be responsible for tasking collection. Avoiding misalignment feedback loops requires an alternate, ongoing, non-engagement signal of information quality. Existing evaluation scales for intelligence product quality and rigor, such as the IC Rating Scale, could provide ground-truth feedback. This sparse data can be used in two ways: for human supervision of average performance and to build models that predict human survey ratings for use at recommendation time. Both techniques are widely used today by social media platforms. Open problems include the design of an ideal human evaluation method, the cost of skilled human labor, and the sparsity of the resulting data.
Teor da informação partilhada: Do discurso à documentação na tomada de decisão clínica em enfermagem

Background : Quality of care depends on the information shared orally during shift handovers and documented in the clinical records. Objective : To analyze the verbal and written information shared in shift handovers and its impact on clinical decision-making in nursing and the continuity of care in a pediatric emergency ward, as well as identify the emerging paradigm for care. Methodology : Qualitative approach, based on Yin’s case study process, using three methods: transcription of the shift handover, documented process
Bacterial Detection and Differentiation of Staphylococcus aureus and Escherichia coli Utilizing Long-Period Fiber Gratings Functionalized with Nanoporous Coated Structures

A biosensor utilizing long-period fiber gratings (LPFG) functionalized with nanoporous coated structures was developed for the rapid detection of Staphylococcus aureus (S. aureus) bacteria. The nanoporous structure coatings on the LPFG surface facilitated specific adhesion and interaction with S. aureus, resulting in an instantaneous shift in the resonance wavelength (RW) in the transmission spectrum of the LPFG. The LPFG with nanoporous polyelectrolyte coatings exhibited an approximately seven-fold RW shift compared to the bare LPFG under the optimal experiment conditions. By tracking the RW shifts, we were able to monitor the real-time S. aureus adhesion to study the interaction process in detail. The bacterial differentiation and S. aureus specificity of the method was confirmed through a series of studies using Escherichia coli (E. coli). This nanoporous structure-enabled LPFG-based biosensor scheme holds significant promise for rapid, reliable, and low-cost detection of S. aureus for biomedical applications.