bluuebunny/crossref_metadata_2025 huggingface dataset:
Factors Affecting Colorectal Cancer Screening in Primary Care Physician Practices in Ukraine
Authors: Dzhemiliev Ali , Kizub Darya , Wanis Kerollos Nashat , Allar Benjamin G. , Vus Vadym , Malovanna Anna , Huivaniuk Inesa , Kopetskyi Viacheslav , Beznosenko Andriy , Shabat Galyna , Antoniv Marta , Suprun Ulana , Melnitchouk Nelya
Published: August 2024

PURPOSE

This study aims to identify the factors influencing colorectal cancer (CRC) screening practices, along with the barriers and facilitators from the perspective of primary care physicians (PCPs) in Ukraine. Considering health care system challenges, including those posed by the ongoing war, this research seeks to inform improvements in CRC screening and outcomes in Ukraine and other low- and middle-income countries (LMICs).

METHODS

A survey was designed and distributed electronically to Ukrainian PCPs, focusing on CRC screening practices, beliefs, and barriers. The survey incorporated questions adapted from established cancer screening surveys and frameworks. Complete responses were collected from 740 PCPs. Sample statistics were computed, and population-level perceptions and associations with CRC screening practices were estimated by standardizing responses to national PCP demographics.

RESULTS

The majority of respondents were women (91%) and specialized in family medicine (84%). Respondents believed in the effectiveness of colonoscopy for reducing CRC mortality (80%), with 75% of PCPs referring patients for this screening modality. Major barriers identified include inadequate training of PCPs in screening and lack of resources. Respondents reported high utilization of fecal occult blood test and colonoscopy for screening when these tests were said to be available in their practices. Self-reported familiarity with CRC screening guidelines and participation in educational workshops were positively associated with screening referrals.

CONCLUSION

The study highlights the role of access to CRC screening tests and awareness of screening guidelines in enhancing CRC screening practices among Ukrainian PCPs. Addressing training and resource barriers, alongside public health interventions targeting patient-related barriers, is essential. These findings offer valuable insights for LMICs facing similar challenges, emphasizing the need for tailored strategies to improve cancer screening in these health care settings.
Germline Susceptibility to Renal Cell Carcinoma and Implications for Genetic Screening
Authors: Glennon Kate I. , Endo Mikiko , Usui Yoshiaki , Iwasaki Yusuke , Breau Rodney H. , Kapoor Anil , Lathrop Mark , Tanguay Simon , Momozawa Yukihide , Riazalhosseini Yasser
Published: August 2024

PURPOSE

Genetic susceptibility to nonsyndromic renal cell carcinoma (RCC) remains poorly understood, especially for different histological subtypes, as does variations in genetic predisposition in different populations. The objectives of this study were to identify risk genes for RCC in the Canadian population, investigate their clinical significance, and evaluate variations in germline pathogenic variants (PVs) among patients with RCC across the globe.

MATERIALS AND METHODS

We conducted targeted sequencing of 19 RCC-related and 27 cancer predisposition genes for 960 patients with RCC from Canada and identified genes enriched in rare germline PVs in RCC compared with cancer-free controls. We combined our results with those reported for patients from Japan, the United Kingdom, and the United States to investigate PV variations in different populations. Furthermore, we evaluated the performance of referral criteria for genetic screening for including patients with rare PVs.

RESULTS

We identified 39 germline PVs in 56 patients (5.8%) from the Canadian cohort. Compared with cancer-free controls, PVs in CHEK2 (odds ratio [OR], 4.8 [95% CI, 2.7 to 7.9], P = 3.94 × 10−5) and ATM (OR, 4.5 [95% CI, 2.0 to 8.7], P = .016) were significantly enriched in patients with clear cell, whereas PVs in FH (OR, 215.1 [95% CI, 64.4 to 597.8], P = 6.14 × 10−9) were enriched in patients with non-clear cell RCCs. PVs in BRCA1, BRCA2, and ATM were associated with metastasis ( P = .003). Comparative analyses showed an enrichment of TP53 PVs in patients from Japan, of CHEK2 and ATM in patients from Canada, the United States and the United Kingdom, and of FH and BAP1 in the United States.

CONCLUSION

CHEK2, ATM, and FH are risk genes for RCC in the Canadian population, whereas PVs in BRCA1/ 2 and ATM are associated with risk of metastasis. Globally, clinical guidelines for genetic screening in RCC fail to include more than 70% of patients with rare germline PVs.
Is There an Association Between Endometriosis, Early Menopause, and Cardiovascular Disease?
Authors: Younis Johnny S , Taylor Hugh S
Published: August 2024

Large-scale studies show endometriosis linked to earlier menopause onset. Recent research targeting women with laparoscopically diagnosed endometriosis found an increase in cases of early natural menopause. Furthermore, recent large-scale cohort studies have found a correlation between endometriosis and an increased risk of cardiovascular disease (CVD). Understanding the causality of early menopause, particularly natural menopause, and cardiovascular risks in women with endometriosis could help medical professionals develop effective strategies for early prevention and new therapies. Endometriosis, early menopause, and cardiovascular risks may be linked by primary or secondary mechanisms. Primary mechanisms involve shared pathways that can lead to all morbidities, while secondary occur due to delayed consequences of management strategies. In these large-scale cohort studies, relevant risk and confounding factors, such as oophorectomy, were considered to refine estimates of associations. However, none of the studies considered endometriotic cystectomy, a globally accepted treatment for endometriosis-associated pelvic pain and infertility, as a mediating factor. There is substantial evidence to indicate that endometriotic cystectomy harms ovarian reserve and may lead to early menopause in cases of multiple surgeries or bilateral cases. Early menopause is a well-established risk factor for CVD. To thoroughly examine the link between endometriosis and early menopause, particularly natural menopause, and their connection with cardiovascular risks, it is imperative to consider all the possible factors that may affect the results, such as endometriotic cystectomy. This will enable us to obtain the most accurate and adjusted hazard ratio.
Non Typical Type 1 Diabetes Mellitus Onset in a Child With Salt-Wasting Congenital Adrenal Hyperplasia
Authors: Rodofile Federica , Franco Francesca , Buccino Nicoletta , Cogo Paola
Published: August 2024

Type 1 diabetes mellitus (T1DM) and congenital adrenal hyperplasia (CAH) are 2 complex endocrine disorders with neighboring genetic loci. We present a case of T1DM onset in a 6-year-old child, already affected by 21-hydroxylase deficiency (salt-wasting CAH) diagnosed at 18 days of age, who was referred to our clinic because of typical symptoms of diabetes despite nondiagnostic fasting blood glucose values. Further analysis revealed elevated glycated hemoglobin (HbA1c), low C-peptide, and specific autoantibodies suggesting the diagnosis of T1DM. Although he only started with rapid-acting insulin analogue before meals, he presented spontaneous episodes of hypoglycemia just before the morning hydrocortisone dose, due to an underdosed glucocorticoid intake. Based on continuous glycemic monitoring (CGM), his morning dose was increased and given earlier; then we decided to apply an advanced hybrid closed-loop insulin pump to maintain glycemic time in range above 70%. Fasting glucose in CAH patients can be lower due to underdosed glucocorticoid replacement therapy. HbA1c and CGM can help recognize T1DM onset and evaluate the correct dosage of corticosteroid therapy in CAH patients. New studies are needed to understand the therapeutic approach for a more specific treatment in case of coexistence of these diseases.
Resistance to Thyroid Hormone Beta Due to THRB Mutation in a Patient Misdiagnosed With TSH-Secreting Pituitary Adenoma
Authors: Liao Wenjun , Waisayanand Nipawan , Fanhchaksai Kanda , Visser W Edward , Meima Marcel E , Wejaphikul Karn
Published: August 2024

Elevated concentrations of T3 and T4 concomitant with nonsuppressed TSH are found in both TSH-producing tumors and resistance to thyroid hormone beta (RTHβ), posing a diagnostic challenge. We demonstrate here a 54-year-old female who presented with palpitations, goiter, and elevated free T4 with nonsuppressed TSH concentrations (TSH 2.2 mIU/L [normal range, NR 0.27-4.2 mIU/L] and FT4 59.08 pmol/L [NR 12.0-22.0 pmol/L]). Because magnetic resonance imaging revealed a pituitary microadenoma (4 mm), she was diagnosed with TSH-secreting pituitary adenoma and underwent transsphenoidal surgery. Pathological reports showed no tumor cells. Subsequent genetic testing revealed a pathogenic variant in the THRB gene resulting in a His435Arg amino acid substitution in the T3 receptor isoform beta 1 (TRβ1), suggestive of RTHβ. In vitro and ex vivo studies revealed that the His435Arg mutated TRβ1 (TRβ1-H435R) completely abolishes the T3-induced transcriptional activation, nuclear receptor corepressor 1 release, steroid receptor coactivator 1 recruitment, and T3-induced thyroid hormone target gene expression, confirming the pathogenicity of this variant. The identification of a pituitary microadenoma in a patient with RTHβ led to a misdiagnosis of a TSH-producing tumor and unnecessary surgery. Genetic testing proved pivotal for an accurate diagnosis, suggesting earlier consideration in similar clinical scenarios.
A Scientific Study on the Raw Material Characteristics and Production Techniques of Early Celadon Excavated from the Sindeok-ri Kiln in Haenam, Korea
Authors: Koo Na Young , Kim Gyu Ho
Published: August 2024

This study cond ucted a scientific analysis of the celadon excavated from Sind eok-ri No. 3-4 and No. 20 sites, and compared the two sites based on the results to obtain information related to the raw material characteristics and production technology of celadon by region and identify differences. In terms of raw material characteristics, The body flux No. 3-4 has low MgO and Na2O content. The g laze flux has lower MgO in No. 3 -4, and the color developer h as lower MnO in No. 3-4. As for the production technology, both kilns were fired at a high temperature where Cristobalite was identified, and No. 20 had a high rate of oxidation. It is estimated that No. 3-4 had a longer cooling time after firing. Both kilns used Lime and High-Lime glazes. It is presumed that as time passed from No. 3-4 to No. 20, ash from trees with high manganese content was used, and then changed to ash from other trees, or a mixture of various types of ash was used. The celadon of No. 3-4 is classified as high quality in Haenam, and the reasons for this seem to be the high brightness of the body, the relatively low rate of oxidation firing, the sufficient cooling process after firing, and differences in glaze materials. The analysis data was compared with the celadon of Gangjin Yongun-ri No. 63, which was operated in a similar region and period. As a result, it is judged that the body characteristics of the two regions are different.
Analysis of Material Properties of Wallpaper and Blue-dyed Paper Used for Banja Ceiling at Main Hall of Jongmyo Shrine
Authors: Kim Ji Won , Jeong Seon Hwa
Published: August 2024

In this study, we collected wallpaper covering the Banja ceiling in chambers 4, 13, 15, and 17 at Jeongjeon Hall of Jongmyo Shrine, and conducted a scientific analysis of the paper material and dye. We carried out fiber identification and physical property analysis such as basis weight, thickness and density for a total of 24 specimens. As finding nine pieces of them were blue-dyed papers, we attempted to analyze the blue substances used as the stain through ultraviolet-visible light(UV-Vis) spectroscopy and gas chromatography(GC). During the layer separation process, we discovered a lotus flower pattern and a swatika pattern were on blue-dyed papers. As the result of analysis, it was confirmed that the fiber of 24 wallpapers was made of bast fiber. And result of basic physical property analysis and averaging, the basis weight was 65.4 g/m2(StDev22.1), the thickness was 0.1523 mm(StDev0.0447), and the density was 0.4428 g/cm3(StDev 0.1358) confirmed. As a result of analyzing blue dye using UV-Vis and GC on blue-dyed paper, components indicating ‘natural indigo’ were commonly detected. So It was determined that ‘Jjok(natural indigo)’ used to dye the blue-dyed paper used for papered royal palace in the Joseon Dynasty period.
A rare cause of erectile dysfunction: Bilateral thrombosed internal iliac artery aneurysms
Authors: Üntan İbrahim , Çil Ahmed Said
Published: August 2024

Internal iliac artery aneurysms are a relatively uncommon condition that can have serious consequences if left untreated. This paper presents a case of erectile dysfunction caused by thrombosis of the internal iliac artery aneurysms in a 52-years-old male patient with common iliac and internal iliac artery aneurysms. Following the intracavernous self-injection treatment, the patient’s complaints about erectile dysfunction ceased. Aneurysms were monitored closely. To the best of our knowledge, this represents the first case of erectile dysfunction being presented as a consequence of thrombosed iliac artery aneurysms. Erectile dysfunction itself is not a life-threatening condition. However, it should be highlighted that erectile dysfunction can be a sign of life-threatening iliac artery diseases, as in this case. Therefore, it is crucial to recognize the potential seriousness of this condition and to investigate it thoroughly.
doi: https://doi.org/10.12669/pjms.40.8.9005
How to cite this: Untan I, Cil AS. A rare cause of erectile dysfunction: Bilateral thrombosed internal iliac artery aneurysms. Pak J Med Sci. 2024;40(8):---------. doi: https://doi.org/10.12669/pjms.40.8.9005
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Σχεδιασμός του διαθεματικού εκπαιδευτικού προγράμματος «Ελιά, ελαιόλαδο και υγεία» με τη χρήση της μεθόδου project για το Νηπιαγωγείο
Authors: ΤΟΔΑΣ ΑΛΕΞΑΝΔΡΟΣ , Κατσούρης Γεωργιος
Published: August 2024

Το συγκεκριμένο άρθρο αφορά στην πρόταση ενός διαθεματικού project με θέμα: «Ελιά, ελαιόλαδο και υγεία». Το συγκεκριμένο project προτείνεται να εφαρμοστεί στα Νηπιαγωγεία και σε μικρές τάξεις Δημοτικού. Η εφαρμογή του συγκεκριμένου project θα βοηθήσει τους μαθητές/τριες να αναπτύξουν βασικές επιστημονικές γνώσεις για το ελαιόλαδο, να αναπτύξουν δεξιότητες για την έρευνά του, αλλά και ευρύτερες δεξιότητες οικονομικού, λαογραφικού, περιβαλλοντικού και διατροφικού χαρακτήρα, μέσα από την αναζήτηση και την μελέτη της ελιάς.
Η Διδασκαλία της Τέχνης της Βιβλιοδεσίας στη Νεοελληνική εκπαίδευση (1829-1933)
Authors: Σουλιώτη Μάγδα
Published: August 2024

Η συσχέτιση βιβλιοδεσίας και ελληνικού εκπαιδευτικού συστήματος μπορεί να φαίνεται νεωτερική, άτοπη ή και άνευ ουσίας για τους περισσότερους, ωστόσο η ιστορική έρευνα στο εκπαιδευτικό σύστημα της χώρας έδειξε ότι η βιβλιοδεσία σε παλαιότερους καιρούς αποτέλεσε διδασκόμενο μάθημα της αναπτυσσόμενης τότε νεοελληνικής εκπαίδευσης.
Η Συμβολή του Παραμυθιού στην Ανάπτυξη του Παιδιού
Authors: Σταθέα Μαρία Παρ.
Published: August 2024

Μια θεωρία για την προέλευση των παραμυθιών υποστηρίζει ότι προέρχονται από την Ινδία και τους ηλιακούς μύθους και άλλη πως οι ινδικοί μύθοι προήλθαν από τους Ελληνικούς μύθους του Αισώπου. Τα παραμύθια τα μετέφεραν οι τσιγγάνοι σε όλον τον κόσμο, ενώ πριν από τον 10ον αιώνα μ.Χ. διαδίδονταν μέσω των Μογγόλων στην Ευρώπη. Στην αρχαία Ελλάδα απόγονοι των παλαιών παραμυθάδων θεωρούνται οι αοιδοί, ενώ στους Ελληνιστικούς χρόνους υπήρχαν επαγγελματίες αφηγητές, οι λεγόμενοι «αρετολόγοι».
Validation and Testing of Novel Underwater Sensors at the Hydrothermal Vent Field of Milos
Authors: Siltzovalis Georgios , Madesis Ioannis , Lagaki Varvara , Krassakis Pavlos , Nikolopoulos Konstantinos , Mertzimekis Theo J.
Published: August 2024

A prototype mobile underwater CdZnTe-based spectrometer was tested under realistic environmental conditions under the scope of the RAMONES Research Programme. Field measurements took place on the island of Milos, which is characterized by the extended hydrothermal vents. A combination of static and dynamic in situ measurements along with analysis of sand and sediment samples, allowed for evaluation of the instrument and will guide its ongoing optimization. Furthermore, a prototype Risk Information System is being developed, allowing easy access for the local stakeholders and scientific community to radioactivity data collected from the instruments of RAMONES.
Elastic scattering of 8B+90Zr at sub-barrier energies
Authors: Palli K. , Pakou A. , Moro A. M. , O'Malley P. D. , Acosta L. , Sántzez-Bénitez A. , Souliotis G. , Aguilera E. F. , Andrade E. , Godos D. , Sgouros O. , Soukeras V. , Agodi C. , Bailey T. L. , Bardayan D. W. , Boomershine C. , Brodeur M. , Cappuzzello F. , Caramichael S. , Cavallaro M. , Dede S. , Dueñas J. A. , Henning J. , Lee K. , Porter W. S. , Rivero F. , Von Seeger W
Published: August 2024

Elastic scattering measurements for the reaction 8B+90Zr at the sub-barrier energy of 26.5 MeV (~ 0.9 VC.B.) were carried out in a recent experiment, realized at the TriSol radioactive beam facility of the University of Notre Dame. This experiment was performed in continuation of our previous work studying 8B on the heavier target 208Pb, alongside with breakup measurements for the same reaction. Final goal is the determination of total reaction and breakup cross sections and the deduction of the direct to total cross section ratio. Preliminary experimental data for elastic scattering will be presented and compared with OMP and CDCC calculations.
Supramassive dark objects with neutron star origin
Authors: Vikiaris Michael , Moustakidis Charalambos , Vlasios Petousis  , Veselsky Martin
Published: August 2024

Till today, the nature of dark matter remains elusive despite all our efforts. This missing matter of the universe has not been observed by the already operating dark matter direct-detection exper- iments, but we can infer its gravitational effects. Galaxies and clusters of galaxies are most likely to contain dark matter trapped to their gravitational field. This leads us to the natural assumption that compact objects might contain dark matter too. Among the compact objects exist in galaxies, neutron stars considered as natural laboratories, where theories can be tested, and observational data can be received. Thus, many models of dark matter they have proposed it’s presence in those stars. By employing the two fluid model, we discovered a stable area in the M-R diagram of a celestial formation consisting of neutron and dark matter that is substantial in size and vast in di- mensions. This formation spans hundreds of kilometers in diameter and possesses a mass equivalent to 100 or more times that of our sun. To elucidate, this entity resembles an enormous celestial body of dark matter, with a neutron star at its core. This implies that a supramassive stellar compact entity can exist without encountering any issues of stability and without undergoing a collapse into a black hole. In any case, the present theoretical prediction can, if combined with corresponding observations, shed light on the existence of dark matter and even more on its basic properties.
Absorbed Dose Distribution in Boron Neutron Capture Therapy for the Treatment of Brain Cancer
Authors: Koukouletsou Ioanna , Kalef Ezra John , Pantelis Evaggelos , Kalamara Antigoni , Stamatelatos Ion
Published: August 2024

Boron Neutron Capture Therapy (BNCT) is a promising re-emerging therapeutic approach for brain tumors, such as glioblastoma multiforme, where conventional treatments have limited efficacy. BNCT is based on neutron irradiation of tumors to selectively kill malignant cells that have accumulated boron compounds with high LET particles produced from the thermal neutron absorption reaction in 10B. Two sets of simulations were performed using the MCNP6.1 code. The first involves the study of the dose components as a function of depth in a cylindrical head phantom consisting of water. The second one deals with the estimation of macroscopic dosimetric quantities to the critical structures in the voxelized Zubal anthropomorphic head/neck phantom. Simulations were performed for different neutron energy spectra, beam radii, as well as boron concentrations in the tumor and the surrounding healthy tissues. The findings contribute to the optimized irradiation of the target in BNCT, while sparing of the patient’s surrounding healthy tissues.
Microdosimetric Modelling of Neutron Capture Therapy Effectiveness
Authors: Georgiou Sofia , Kalef-Ezra John , Kalamara Antigoni , Karavasilis Efstratios , Stamatelatos Ion Evangelos
Published: August 2024

Monte Carlo simulations were carried out using the MCNP 6.1 code to predict the energy deposition at microscopic level in in vitro Neutron Capture Therapy studies. Irradiations with neutron beams of energies from 25 meV to 14.2 MeV of small spherical targets loaded with either 1000 ppm natB (200 ppm 10B) or natGd (156 ppm 157Gd) and located at the center of a small phantom were simulated.  ENDF/B-VII.1 and TENDL-2017 libraries, as well as INCL4/ABLA and Bertini models were tested using published experimental data as benchmark, i.e. a spherical proportional counter that simulated a 1 μm in diameter tissue equivalent site irradiated with 13.9 MeV neutrons. The methodology, as developed, was applied to assess the microdistribution spectra to the target in terms of yd(y), yF, yD and the kerma to flux ratio for the prediction of the biological response of in vitro cells irradiations.
Lifetime measurement in 182W using the Differential Decay Curve Method
Authors: Zyriliou Aikaterini , Mertzimekis Theodoros , Vasileiou Polytimos , Mavrommatis Eirini , Chalil Achment , Efstathiou Margarita , Karadimas Angelos , Bonatsos Dennis , Martinou Andriana , Minkov Nikolay , Marginean Nicolae , Mihai Constantin , Florea Nicoleta , Borcea Ruxandra , Ujeniuc Sorin , Turturica Andrei , Costache Cristian , Mihai Radu , Stan Lucian , Filipescu Dan , Toma Sebastian , Gheorghe Ioana , Dinescu Irina , Ionescu Alina , Stoica Liviu , Calinescu Stefana , Oprea Andreea , Stoica Alexandru , Sotty Christophe , Clisu Cristina , Nita Cristina , Neacsu Catalin , Boromiza Marian , Marginean Radu , Bucurescu Dorel , Lica Razvan , Stroe Lucian , Suvaila Rares
Published: August 2024

This work focuses on the lifetime measurement and spectroscopic properties of 182W. The mass region around this nucleus is of significant interest due to its unexplored nature and the presence of intriguing structural phenomena, including deformation, shape changes, and shape coexistence. Experimental measurements were conducted in the National Laboratory IFIN-HH in Romania, focused on the spectroscopic study of 182W isotope using the Differential Decay Curve Method (DDCM), a similar approach for the Recoil Distance Doppler Shift (RDDS) method. This experiment provided valuable data on the energy levels, lifetimes, and decay properties of the excited states in the 182W and neighboring nuclei. The measurements were performed using the ROSPHERE detector array, loaded with HPGe and particle identification detectors, and a plunger device. As a result, the lifetime for the 61+ in 182W obtained for the first time via the fusion evaporation reaction 181Ta(11B, 10Be)182W and the DDCM at 47 MeV, and was found to agree well with earlier measurements.
Neutron Induced Reactions on 203Tl at 15.7MeV, 16.0MeV and 18.0MeV
Authors: Kagioglou Maria , Vlastou Rosa , Diakaki Maria , Kokkoris Michail , Chasapoglou Sotirios , Bari Zoi , Axiotis Michail , Lagogiannis Anastasios
Published: August 2024

The aim of the present work is to study the potential channels that result from the interaction of 203Tl with neutrons by bombarding natural TlCl pellet targets with neutron beams at 15.7, 16.0 and 18.0 MeV. The monoenergetic neutron beams were produced at the 5.5 MV Tandem Van de Graff accelerator laboratory of NCSR "Demokritos" by means of the 3H(d,n)4He reaction. The cross section measurements were based on the activation technique and deduced with respect to the 197Au(n,2n)196Au and 27Al(n,α)24Na reference reactions. After the end of the irradiations, the induced activity in the target and reference foils was measured by γ-ray spectroscopy, using High Purity Germanium detectors (HPGe).
Micromegas detector response test at the new EAR2 neutron beam of n_TOF facility in view of the 243Am(n,f) measurement
Authors: Kyritsis Nikolaos , Diakaki Maria , Michalopoulou Veatriki , Eleme Zinovia , Patronis Nikolaos , Kokkoris Michael , Vlastou Roza , N_TOF collaboration
Published: August 2024

A key ingredient of the design of advanced nuclear systems, such as Generation IV reactors and accelerator driven systems, is the study of neutron induced fission reactions. Accurate cross-section data on key actinides is needed both for their operation and the handling of the nuclear waste. 243Am is among the long-lived isotopes present in nuclear wastes, that contribute to the long-term radiotoxicity, and the respective fission cross-section data are needed with high accuracies. Consequently, an experiment was planned to measure the neutron induced fission cross section of 243Am in experimental areas EAR1 and EAR2 the n_TOF facility at CERN. However, due to the change of the lead spallation target of the n_TOF facility, which led to significant changes in the characteristics of the neutron beam of experimental area EAR2, as well as to the increased complexity of the setup compared to similar past experiments, a preliminary experiment to test the setup in the new conditions was deemed necessary. In this work, we will describe the experimental setup and examine the test results.
Case Report: An unusual case of severe autoimmune hemolytic anemia in untreated hepatitis C viral infection
Authors: Debbabi H , Chakroun A , Elloumi H , Yacoub H , Ben Azouz S , Marouani R
Published: August 2024

Patients with hepatitis C share a variety of anemia, including bleeding, nutritional deficiencies, and anemia of chronic disease. Autoimmune hemolytic anemia (AIHA) is usually reported with interferon-alpha and/or ribavirin treatment in hepatitis C virus (HCV) infections. We report an unusual case of AIHA occurring in a49-year-old patient with untreated hepatitis C infection who presented with functional anemia syndrome. Monospecific direct antiglobulin test showed the presence of anti-complement (C3d++). Cold agglutinin titer was 1/16 at 4°C. The patient improved following blood transfusion, steroid therapy and direct acting antivirals.
Visual field changes in patients receiving antitubercular therapy: A prospective cross-sectional study from South India
Authors: Pagadala Tejaswi , Kamath Gurudutt , Mendonca Teena Mariet , Rodrigues Gladys , Kamath Ajay
Published: August 2024

Objective Tuberculosis is a global health challenge with one-third of the world’s population infected by it. Although ocular side effects of Anti-tubercular drugs are well known, the patients generally report late in the course which can result in irreversible vision loss. The purpose of this study was to study the visual field changes during the time course of anti-tubercular therapy (ATT). Methods A total of 48 patients were studied in this prospective type of study. All patients newly diagnosed with TB and started on treatment were included in the study. Baseline examination which included visual acuity, color vision, anterior segment, IOP, Amsler grid, fundus, and visual field test were performed before starting ATT and at 6-month follow-up. Results The mean age of the study population was 35.90 ± 10.2 years. 35 (72.9%) were males and 13 (27.1%) females. 32(66.6%) had pulmonary TB and the rest 16 (33.3%) had extrapulmonary TB. MDR TB was diagnosed in 27 (56.3%) of the patients with the rest 21 (43.8%) being drug sensitive. The baseline examination was normal in all 48 patients. 3(6.3%) out of 45 patients presented with visual complaints after the treatment initiation. Altogether 7 patients out of 48, had visual field defects at the 6-month follow-up. The incidence of visual field defects in our study was 14.6% with the value being significant (0.016). 8.3% had peripheral constriction of visual fields, 2.1% with Severe generalized depression of visual fields and 2.1% with central scotoma. Out of the 45 patients with no visual complaints at 6-month follow-up, 4 (8.33%) showed peripheral field constriction. Conclusion Visual field defects caused by ATT can precede clinical symptoms. Visual field evaluation can be an important tool for the early detection of optic neuropathy in patients receiving ATT in clinical settings where Visual evoked potential testing and RNFL-OCT are not available.
Health care-seeking behavior for childhood illnesses in western Kenya: Qualitative findings from the Child Health and Mortality Prevention Surveillance (CHAMPS) Study
Authors: Ngere Sarah , Maixenchs Maria , Khagayi Sammy , Otieno Peter , Ochola Kennedy , Akoth Kelvin , Igunza Aggrey , Ochieng Benard , Onyango Dickens , Akelo Victor , Blevins John , Barr Beth A. Tippett
Published: August 2024

Background Child mortality in Kenya is 41 per 1,000 live births, despite extensive investment in maternal, newborn, and child health interventions. Caregivers’ health-seeking for childhood illness is an important determinant of child survival, and delayed healthcare is associated with high child mortality. We explore determinants of health-seeking decisions for childhood illnesses among caregivers in western Kenya. Methods We conducted a qualitative study of 88 community members between April 2017 and February 2018 using purposive sampling in an informal urban settlement in Kisumu County, and in rural Siaya County. Key informant interviews, semi-structured interviews and focus group discussions were performed. We adopted the Partners for Applied Social Sciences model focusing on factors that influence the decision-making process to seek healthcare for sick infants and children. The discussions were audio-recorded and transcribed. Data management was completed on Nvivo® software. Iterative analysis process was utilized and themes were identified and collated. Results Our findings reveal four thematic areas: Illness interpretation, the role of social relationship on illness recognition and response, medical pluralism and healthcare access. Participants reported some illnesses are caused by supernatural powers and some by biological factors, and that the illness etiology would determine the health-seeking pathway. It was common to seek consensus from respected community members on the diagnosis and therefore presumed cause and necessary treatment for a child’s illness. Medical pluralism was commonly practiced and caregivers would alternate between biomedicine and traditional medicine. Accessibility of healthcare may determine the health seeking pathway. Caregivers unable to afford biomedical care may choose traditional medicine as a cheaper alternative. Conclusion Health seeking behavior was driven by illness interpretation, financial cost associated with healthcare and advice from extended family and community. These findings enrich the perspectives of health education programs to develop health messages that address factors that hinder prompt health care seeking.
A Vision-Based Analog Meter Reading Method for Inspection Robots
Authors: Li Jiacheng , Wang Honglei , Zhu Xishuo , Liu Sijian , Zhang Junsheng
Published: August 2024

Computer vision technology has been widely applied in reading recognition of analog meters. However, it is still a challenge to quickly and accurately read various types of analog meters under different environmental conditions. We propose a fast-reading method for analog meters based on keypoint detection, which is applied to inspection robots. First, we use the YOLOv5s network to locate the analog meter. Second, the HRNet network is used to detect the keypoints of the pointer and scale on the dial. Third, an objective image quality assessment method that includes multiple indicators is established to select the optimal image for reading recognition. Finally, we calculate the reading of the analog meter based on the deflection angle of the pointer. The experiment shows that our method can accurately read the readings of analog meters, with an average reading error of 3.81%. It can be effectively applied to inspection robots to read analog meter readings.
Copyright Protection and Risk Assessment Based on Information Extraction and Machine Learning: The Case of Online Literary Works
Authors: Lin Xudong
Published: August 2024

With the proliferation of digital platforms, the dissemination of literary works has encountered unprecedented challenges, particularly concerning copyright infringement and unauthorized use. This study introduces a comprehensive framework for copyright protection and risk assessment, specifically tailored to online literary works. The framework employs advanced CNN based information extraction (IE) techniques coupled with machine learning (ML) algorithms to identify, classify, and protect literary content against copyright violations. Firstly, we delineate a novel CNN-Decision tree-based IE methodology that systematically harvests metadata and textual content from various online repositories. This process is designed to detect and index online literary works, extracting pertinent features such as authorship, publication date, and textual patterns. Following the extraction, the study utilizes natural language processing (NLP) to analyze and compare content, pinpointing potential instances of copyright infringement by identifying significant overlaps and stylistic similarities with registered works. Subsequently, we introduce a risk assessment model developed through supervised machine learning. This model is trained on a labelled dataset comprising instances of both copyrighted and non-copyrighted works, along with known cases of copyright infringement. By analyzing the extracted features, the model assesses the probability of infringement, categorizing risks into high, medium, and low categories. This stratification allows stakeholders to prioritize enforcement actions and resources efficiently. The study further explores the implementation of various ML algorithms, including decision trees, support vector machines, and neural networks, to determine the most effective approach for copyright protection in the literary domain. We evaluate the models based on accuracy, precision, recall, and F1-score metrics, emphasizing their capacity to generalize and operate in dynamic, real-world environments.
Missing Data Imputation for Health Care Big Data using Denoising Autoencoder with Generative Adversarial Network
Authors: Zhang Yinbing
Published: August 2024

Missing data imputation is a key topic in healthcare that covers the issues and strategies involved in dealing with partial data in medical records, clinical trials, and health surveys. Data in healthcare might be missing for a variety of reasons, including non-response in surveys, data entry problems, or unrecorded information during therapeutic appointments. This paper introduces a novel approach to impute missing data utilizing a hybrid model that integrates denoising autoencoders with generative adversarial networks (GANs). We begin by highlighting the prevalence of missing data in health care datasets and the potential impact on analytical outcomes. The proposed methodology leverages the denoising autoencoder’s ability to reconstruct data from noisy inputs, coupled with the GAN’s proficiency in generating synthetic data that is indistinguishable from real data. By combining these two neural network architectures, our model demonstrates an enhanced capability to predict and fill in missing data points effectively. To validate our approach, we conducted experiments on several large-scale health care datasets with varying degrees of artificially introduced missingness. The performance of our model was benchmarked against traditional imputation methods such as mean imputation and k-nearest neighbors, as well as against standalone denoising autoencoders and GANs. Our results indicate a significant improvement in imputation accuracy, as measured by root mean square error (RMSE) and mean absolute error (MAE), confirming the efficacy of the hybrid model in handling missing data in a robust manner.
Next-Generation Connectivity: A Holistic Review of Cooperative NOMA in Dynamic Vehicular Networks for Intelligent Transportation Systems
Authors: Sravani Potula , Sreenivasa Rao Ijjada
Published: August 2024

Intelligent Transportation Systems are witnessing a paradigm shift with the integration of Cooperative Vehicular Networks. The transformations in Intelligent Transportation system in the realistic scenario has posed many research challenges to be addressed. This paper explores a profound survey on impact of vehicles’ mobility within the context of real-time scenarios in Cooperative vehicular networks. The dynamic nature of vehicular mobility introduces unique challenges and opportunities for the design and implementation of cooperative systems. It delves into the key components that play a pivotal role for harnessing the full potential of Cooperative vehicular networks such as C-NOMA, Two-Way relaying, cluster formation and collaborative decision-making algorithms for improving latency, link reliability, cluster formation, and interference reduction etc. This paper outlines few surveys on each amalgamated technologies in Vehicular communication and conclude with the research problems in ITS due to vehicles mobility for real time scenarios.
Driver Drowsiness Detection
Authors: Zeki Ablahd Ann , Qusay Aloraibi Alyaa , Abd Dawwod Suhair
Published: August 2024

The state of the driver of being extremely tired or sleepy through the operation of the vehicle is called driver drowsiness. Different factors caused this state such as alcohol, lack of sleep, and the side effect of some medication. The drowsiness of drivers is a serious safety lead to accidents or fatalities on external and internal roads. The increased number of road accidents resulted from drowsy driving. A special smart, reliable, and accurate system, Using Python language 3.6 for Windows, was designed to build an alert system for drivers in detecting drowsiness driver. This system is crucial in reducing accidents road by the ability to concentrate, react quickly, and produce sound decisions through driving. This system implements a real-time detector that can monitor the states of drivers through driving.Smart cameras with 16-megapixel were used to ensure that capturing photos have a high quality. These cameras were used in gathering the driver’s dataset in different alertness states, including both alert states and drowsy. The collected dataset is processed by extracting all relevant features such as head movement, yawning, and eye closure, which were used in identifying the driver’s drowsiness. Python’s libraries such as TensorFlow, OpenCV, Keras, and Pygame are used for extracting all the above features. Viola-Jones algorithm is used in face eye region detecting and extracting from the image of the face in the proposed system. A Support Vector Machine (SVM) algorithm was used in classifying between drowsy and non-drowsy drivers. The system is tested and evaluated in the real world, to ensure that the system is reliable and robust; it has high performance and accuracy, and the accuracy is about 99.1%. This system can be used in manufacturing vehicles.
Ensemble Transfer Learning for Botnet Detection in the Internet of Things
Authors: Aalsaud Ali , Kareem Shahab Wahhab , Zuhair Yousif Raghad , Salahuddin Mohammed Ahmed
Published: August 2024

Botnet attacks are just one security scalability problem that nearly comes as a default with each and every new IoT system launched into the real world. IoT devices, in particular, are tricky to locate on a network with standard methods of botnet detection due to their inherent volatility and system constraint developments. To this aim, we propose an ensemble method for botnet detection based on transfer learning that mitigates those drawbacks. The representation learning-based method is used to deliver a domain-adapt transfer of data between two domains (one that has traditional network data and other that contains IoT devices). Ensemble Method — This technique improves the detection accuracy and robustness by employing pre-trained models and customizing them to the target IoT environment using many models working together. The ensemble transfer learning system includes low-level base classifiers (e.g., AlexNet, VGG16, inceptionV3, Mobile Net) that are trained on various IoT data and features. To utilize the domain-specific information effectively, the authors investigate model stacking and domain adaptation as two transfer learning strategies. The authors also consider feature engineering methods to determine signatures of IoT behavior and aid their models to distinguish between normal device behavior and botnet activities. The authors also perform extensive experiments on real-world IoT datasets to show the efficacy of the proposed ensemble transfer learning approach. In comparison to single-model techniques, the results show considerable gains in botnet detection accuracy, sensitivity, and specificity. The ensemble technique is also resilient to different IoT device types and network circumstances, making it appropriate for real-time deployment in various IoT contexts. In comparison to single-model techniques, the results show considerable gains in botnet detection accuracy, sensitivity, and specificity. The ensemble technique is also resilient to different IoT device types and network circumstances, making it appropriate for real-time deployment in various IoT contexts.
Multi Channel Electronic Communication Signal Parameters based on Nonlinear Phase Principle Modulation and Deep Learning
Authors: Yan Xiaoqing
Published: August 2024

In order to solve the problem of high sampling rate and large number of sampling points required by current phase modulation signal parameter estimation methods, a parameter modulation method for multi-channel electronic communication signals based on nonlinear phase principle and deep learning is proposed. Firstly, classify and introduce the modulation methods, and propose a new algorithm for identifying instantaneous feature parameters. The author conducted nonlinear phase principle modulation recognition on seven typical digital signals: 2ASK, 4ASK, 2FSK, 4FSK, 2PSK, 4PSK, and 16QAM. Using the author’s algorithm, experiments were conducted on the recognition of seven digital nonlinear phase modulation signals under different signal-to-noise ratios. As can be seen from the results, when the signal-to-noise ratio is greater than or equal to 10dB, the recognition accuracy of the seven digital nonlinear phase modulation signals can reach 100%, verifying that the new algorithm proposed by the author improves the recognition accuracy.
A Machine Intelligence Evaluation System Based on Internet Automation Technology and Deep Learning
Authors: Liu Hongchuan
Published: August 2024

To realize the machine intelligence evaluation system, a method based on Internet automation technology is proposed. Firstly, then extracted and optimized, and finally combined with each other. A BP neural machine evaluation system is designed to compare the results of machine evaluation with the average value of teachers’ independent evaluation by selecting 20 students’ test paper translation samples from a class randomly. The test results show that by selecting a random class of 20 students, the comparison of machine evaluation results and teacher independent evaluation shows that the error range of the evaluation results of 20 samples is-5.6% -6.7%, which is within the allowable range of translation evaluation and meets the requirements of teaching evaluation. It is proved that the Chinese-English machine translation evaluation system based on Internet automation technology has excellent performance, which can improve the reliability and accuracy of the evaluation and reduce the degree of human intervention and misjudgment rate of the Chinese translation evaluation.
Prediction Method of Rate of Penetration based on Fuzzy Support Vector Regression
Authors: Yang Li , Wang Lishen , Bai Lili , Sun Wenfeng
Published: August 2024

Predicting the rate of penetration (ROP) is important for optimizing drilling parameters, improving drilling efficiency, and optimizing economic benefits throughout the drilling process. The current prediction model of ROP based on machine learning algorithms does not consider the interference of outliers. Therefore, in this study, we propose a method to predict ROP based on fuzzy support vector regression (FSVR). First, appropriate input parameters were selected from the controllable parameters. Second, based on the local outlier factor, a fuzzy membership degree was assigned to each sample. Finally, the sample with the fuzzy membership value was input into the model for ROP prediction. The results demonstrated that the goodness of fit (R2) of the improved FSVR model is 0.9634, and the mean absolute error is 0.1974. Compared with standard SVR and other models, the improved FSVR model has a stronger anti-interference ability, smaller prediction error for normal samples, and higher accuracy.
Analysis of Frozen Data Anomaly and Update Method of Electromechanical Energy Meter Terminal based on Deep Learning
Authors: Yao Fang , Tan Libin
Published: August 2024

In view of the lack of advanced and mature substation fault detection and facility detection technology, combined with the characteristics of the actual application environment of substation, a substation operating equipment autonomous monitoring and fault diagnosis detection system based on deep learning intelligent detection robot is proposed. That is, the deep learning algorithm, Big data analysis technology and patrol robot with HD camera are organically combined. The image information collected by the high-definition camera is fused with the data information collected by a variety of sensors, and then the fault tree and Big data analysis algorithm are used to carry out real-time intelligent detection and analysis of all equipment in the substation, and the early warning can be sent to the relevant equipment maintenance personnel in a timely manner. The experimental results indicate that, the number of input nodes in the fault tree is 7, the number of output nodes is 2, the number of center vectors is 14, the number of nodes in the basis function layer is 7, and the threshold of the basis function is set to 0.8257. In actual training, after 31 iterations, the training results can quickly converge to the target value, the training error meets the requirements, and the fault diagnosis accuracy reaches over 90%. It has been proven that the diagnostic performance of the system is good, achieving the expected design effect.