bluuebunny/crossref_metadata_2025 huggingface dataset:
Antibacterial properties of mesoporous silica coated with cerium oxide nanoparticles in dental resin composite
Authors: Byun Sung-Yun , Han A Ruem , Kim Kwang-Mahn , Kwon Jae-Sung
Published: April 2024

Cerium oxide nanoparticles are known for their antibacterial effects resulting from Ce3+ to Ce4+ conversion. Application of such cerium oxide nanoparticles in dentistry has been previously considered but limited due to deterioration of mechanical properties. Hence, this study aimed to examine mesoporous silica (MCM-41) coated with cerium oxide nanoparticles and evaluate the antibacterial effects and mechanical properties when applied to dental composite resin. Cerium oxide nanoparticles were coated on the MCM-41 surface using the sol-gel method by adding cerium oxide nanoparticle precursor to the MCM-41 dispersion. The samples were tested for antibacterial activity against Streptococcus mutans via CFU and MTT assays. The mechanical properties were assessed by flexural strength and depth of cure according to ISO 4049. Data were analyzed using a t-test, one-way ANOVA, and Tukey’s post-hoc test (p = 0.05). The experimental group showed significantly increased antibacterial properties compared to the control groups (p < 0.005). The flexural strength exhibited a decreasing trend as the amount of cerium oxide nanoparticle-coated MCM-41 increased. However, the flexural strength and depth of cure values of the silane group met the ISO 4049 standard. Antibacterial properties increased with increasing amounts of cerium oxide nanoparticles. Although the mechanical properties decreased, silane treatment overcame this drawback. Hence, the cerium oxide nanoparticles coated on MCM-41 may be used for dental resin composite.
Effect of Exposure to Crude Oil Polluted Environment on Hematological and Serological Indices in Chickens: Variability in Breed Sensitivity
Authors: Oleforuh-Okoleh Vivian U. , Fakae Lenu B. , Obianwuna Uchechukwu E. , Kakulu Iyenemi I. , Onu Patience N. , Sikiru Akeem B. , Ollor Ollor A. , Emeka Onyinyechi C.
Published: April 2024

Industrial petrochemical activities pose a significant threat to the ecosystem and could cause health issues in chickens reared within vulnerable areas such as the Niger Delta region of Nigeria. This study investigated the differential responses of four chicken breeds (FUNAAB Alpha FAC, Ross 308 broilers AB, native chickens-origin of crude oil exploration communities HP, and native chickens-origin of non-crude oil exploration communities NHP) to crude oil flaring using blood-borne parameters. At five weeks of age, 256 chicks were randomly assigned to two groups: control and exposed, each had four replicates (eight birds/replicate). Birds in the exposed group inhaled gaseous emissions from crude oil flared in their enclosure (three hours daily on alternate days for 35 days). Haematological indices were influenced by a decrease (p<0.05) in packed cell volume and red blood cell count in the exposed group compared with the control. A remarkable rise (p<0.05) in inflammatory markers (platelet count, erythrocyte sedimentation rate, and interleukin-6 levels (IL-6) was also observed in most breeds. The AB showed no significant changes in haematological indices or inflammatory markers, save for IL-6. For most breeds, the exposed group had higher serum levels of aspartate aminotransaminase, alanine aminotransaminase, alkaline phosphatase, creatinine, total protein, and uric acid. Evidence of oxidative stress, as indicated by increased serum malondialdehyde (p<0.05) and reduced enzymatic antioxidant defense levels of glutathione peroxidase and superoxide dismutase activity, was recorded. Our study revealed marked variations in blood parameters among breeds, with the AB(broiler) showing more resilience to hydrocarbon toxicity than breeds with indigenous genes.
Electric Potential Energy Optimized 3D Radial Sampling Trajectories for MRI
Authors: Huynh Christopher , Goolaub Datta Singh , Macgowan Christopher K.
Published: April 2024

The purpose of this work was to develop and analyze a novel method for creating “golden” 3D center-out radial MRI sampling trajectories, called ELECTRO (ELECTRic potential energy Optimized). This method is based on using repulsive forces to minimize electric potential energy. An objective function G(S) was proposed that contains the electric potential energies of all subsets of consecutive readouts in a 3D radial trajectory. G(S) and its reduced form were minimized using a multi-stage optimization strategy. A new measure called Normalized Mean Nearest neighbor Angular distance (NMNA) was proposed for describing distributions of points on a sphere. ELECTRO and other relevant golden trajectories were compared in silico using NMNA and point spread function analysis.
This work demonstrated that any subset of consecutive readouts from an ELECTRO trajectory were well spread out, as indicated by the consistency of NMNA values across sphere sizes (σNMNA=0.005) and between regions on the sphere (NMNA ≈ 1.49 over most regions). Conversely, the commonly used supergolden trajectory had poor consistency in NMNA values (σNMNA=0.090) and had severe clustering of readouts (for instance, NMNA = 1.28 at the pole with 40,000 readouts) that lead to structured aliasing artifact in the point spread function. Compared to performing the optimization all in a single stage, a multi-stage optimization strategy was faster and obtained lower values of G(S) (eg, 0.87 vs. 0.91, for a sphere size of 40). Minimizing a reduced version of G(S) can significantly reduce computation time but may result in a more uneven readout distribution.
In conclusion, ELECTRO trajectories are more golden than other 3D center-out radial trajectories, making them a suitable candidate for dynamic 3D MR imaging.
Machine learning-based diagnostic prediction of IgA nephropathy: model development and validation study
Authors: Noda Ryunosuke , Ichikawa Daisuke , Shibagaki Yugo
Published: April 2024

IgA nephropathy progresses to kidney failure, making early detection important. However, definitive diagnosis depends on invasive kidney biopsy. This study aimed to develop non-invasive prediction models for IgA nephropathy using machine learning. We collected retrospective data on demographic characteristics, blood tests, and urine tests of the patients who underwent kidney biopsy. The dataset was divided into derivation and validation cohorts, with temporal validation. We employed four machine learning models—eXtreme Gradient Boosting (XGBoost), LightGBM, Random Forest, and Artificial Neural Networks—and logistic regression, evaluating performance via the area under the receiver operating characteristic curve (AUROC) and explored variable importance through SHapley Additive exPlanations method. The study included 1268 participants, with 353 (28%) diagnosed with IgA nephropathy. In the derivation cohort, LightGBM achieved the highest AUROC of 0.913 (95% CI 0.906–0.917), significantly higher than logistic regression and Artificial Neural Network, not significantly different from XGBoost and Random Forest. In the validation cohort, XGBoost demonstrated the highest AUROC of 0.894 (95% CI 0.850–0.935), maintaining its robust performance from the derivation phase. Key predictors identified were age, serum albumin, serum IgA/C3 ratio, and urine red blood cells, aligning with existing clinical insights. Machine learning can be a valuable non-invasive tool for IgA nephropathy.
Adsorption and aggregation behavior of oley alcohal based extended surfactant and its mixtures
Authors: Li Ping , Ren Peiyu , Wang Shuoyi , Wang Jiangshan , Sun Zidan , Sun Jiayi , Gu Weibo
Published: April 2024

Oley alcohal based extended surfactant, sodium oleyl polyethylene oxide -polypropylene oxide sulfate (OE3P3S), was synthesized and identified by FT-IR and 1H NMR. The adsorption and aggregation behavior of OE3P3S and its mixture with cationic surfactant alkyltrimethylammoniumbromide (ATAB) under different molar ratios were investigated. The static surface tension analysis indicates that the critical micellization concentration(cmc) and the critical surface tension (γcmc) of OE3P3S was 0.72mmol/L, and 36.16mN/m, respectively. The cmc and γcmc values of the binary system were much lower than that of the individual component. And the cmc values of OE3P3S/ATAB=6:4 mixtures decreased with the increase of chain length of the cationic surfactant in the binary system. It was found from the dynamic surface tension that there was a slower diffusion rate of binary system compared to the pure surfactant, and the adsorption processes for OE3P3S/ATAB =6:4 were mixed diffusion-kinetic adsorption mechanism. With a combination of DLS data and TEM measurements, formations of vesicles in OE3P3S/ATAB =6:4 solutions appeared to occur at a concentration of 0.05mmol/L. By studying the formation of liquid crystal structures in emulsion prepared with OE3P3S as the surfactant, it was found that the shape of acquired oil droplets being spherical and homogeneous, and the rheological properties revealed that the emulsion had good storage stability and shear thinning properties.
Hirayama Disease as a rare cause of cervical myelopathy of the young. A meta-analysis comparing conservative and surgical treatment
Authors: Paolini Federica , Gerardi Rosa Maria , Giardina Kevin , Buscemi Felice , Biancardino Antonio Alessandro , Porzio Massimiliano , Benigno Umberto Emanuele , Maniscalco Laura , Matranga Domenica , Maugeri Rosario , Iacopino Domenico Gerardo
Published: April 2024

Background:Hirayama disease is a rare form of cervical myelopathy exacerbated by flexion-extension movements of the neck. It affects mainly young male patients. The scarcity of cases implies uncertainty when it comes to choose the best treatment between conservative and surgical approach.
Methods:A systematic review of the current literature was performed following the PRISMA guidelines. A meta-analytic comparison of patients’ outcome in terms of clinical and radiological data has derived.
Results: From our meta-analysis, clinical and radiological improvement was obtained in both surgical and conservative treatment, with different percentages. Radiological improvement was seen in 91% of the population undergoing surgical treatment vs 57% of conservative treatment. Moreover, clinical improvement was obtained in 92% of surgical patients vs 78% of patients wearing a collar. Our hypothesis is related to the compliance of patients forced to wear a cervical collar 24h a day for 2-3 years.
Conclusions: While findings from pertinent literature are conflicting, results from our meta-analysis seems to lean on surgical treatment as best alternative to offer clinical and radiological improvements (92% and 91%, respectively). our study hint both surgery and conservative management as equally valuable. Nevertheless, conservative treatment is able to achieve clinical and radiological improvement in 78% and 57% of patients respectively.
A Retrospective Analysis of Short-Term Outcomes of Robotic and Laparoscopic Cholecystectomy: First Indian Experience
Authors: Ray Udipta , Dhar Rahul
Published: April 2024

Background
There has been a gradual adoption of general surgery robotic programs in India. However, we still do not have a single comparative study reporting the initial experience of robotic-assisted cholecystectomy (RC) compared to laparoscopic cholecystectomy (LC). This retrospective study is aimed at addressing this clinical data gap.
Methods
This is a retrospective medical chart review where data related to patient demographics, intraoperative and postoperative outcomes was collected. All patients underwent either RC or LC for gallstone disease, performed by a single surgeon from January 2020 to September 2023.
Results
A total of 100 cases (RC- 50, LC- 50) were collected. Baseline parameters like age, sex, body mass index (BMI), and co-morbidities were comparable. There were no conversions from the planned procedure in either of the groups (0% vs 0%). There were no intraoperative complications such as bleeding or common bile duct injury (0% vs 0%). The rates of surgical site infections were numerically lower in the robotic group, 2% vs 6% (P = 0.3099). There were no postoperative complications in the robotic group, whereas 1 patient in the laparoscopic group experienced port side bleeding (0% vs 2%, P = 0.3173). The mean length of hospital stay was 1 day in both groups. The mean pain score 24- hours after the surgery was 1.78 ± 0.68 in the robotic group and 3.3 ± 1.2 in the laparoscopic group (P = < 0.001). At 14 days post-surgery, these scores decreased in both the groups, the robotic group- mean 1 and the laparoscopic group – mean 2. None of the patients required opioid analgesics in the robotic group whereas 20% of patients in the laparoscopic group needed at least one dose of opioid analgesics (P = 0.0009). There were no re-operations reported in the robotic group, whereas the laparoscopic group reported 1 case. The 30-day mortality was nil in both groups.
Conclusion
RC is feasible in Indian settings. Compared to LC, it does not increase morbidity. The improvement in acute postoperative pain can potentially allow early ambulation and recovery. A larger multicentric study, comparing RC to LC in India will validate our initial experience.
Characterization of Heatwave Patterns and Its Long-run Predictions Using CMIP6 Model in Western and North-Western Climatic Zones of Bangladesh
Authors: Ahmad Rayhan , Hasan Md. Khalid , Jahan Chow. M. Sarwar
Published: April 2024

Globally, the hazards related to climate change effect such as tropical cyclones, storm surges, coastal flooding, river erosion, floods, droughts, heatwave, cold wave etc. are burning challenge that drastically effects people’s food security, health, ecosystems and society as a whole. In recent decade, rising trend of unusually prolong high temperature or heatwave episode is a burning concern. Present study area address the heatwave patterns in western climatic zone (E), and north-western climatic zone (D) in the north-western part of Bangladesh. Using historical maximum temperature (TMAX) data during the period of 1996-2014, and model-projected TMAX data (2015- 2022) have collected. Moreover, two shared socio-economic tools such as SSP_245 and SSP_585 have used in present study along with projected data for the years of 2024–2050. The study uses heatwave alerts from the Bangladesh Meteorological Department (BMD) to classify heatwave days into four categories: mild, moderate, severe, and extreme. To improve accuracy, four general circulation models (GCMs) from the Coupled Model Inter-comparison Project phase 6 (CMIP6) have assessed following bias correction, and merged using an ensemble technique. The median has used to reduce extreme value sensitivity. According to the BMD criteria, the results show that severe and exceptional hot days have occurred often in recent years. This tendency could continue into the future, putting a sizable population at risk. The heatwave days are significantly more common under SSP_585 than they are under SSP_245, demonstrating the straightforward influence of human activity on heatwave regularity. To lessen the negative effects of heatwaves, fair and practical measures for preparing for and responding to them should be developed, and will be facilitated by this thorough analysis of heatwave projections. The results of present study highlight the urgency of taking immediate action to improve heat wave readiness. These study results are expected to enhance the accomplishment of the Sustainable Development Goals (SDG 3, SDG 11, and SDG 13) by guiding proactive steps to mitigate the consequences of severe heat wave days.
Relationship between the triglyceride–glucose index, blood uric acid levels, and prevalence of gout in Korean adults: Eighth Korean National Health and Nutrition Examination Survey (2019–2021)
Authors: Ahn Taejin , Kim Young-Sang , Hur Yang-Im , Kim Moon Jong , Haam Ji-Hee
Published: April 2024

Background: The triglyceride and glucose (TyG) index is a useful marker of insulin resistance and metabolic syndrome. Several studies have reported a link between this index and serum uric acid levels. However, few studies have shown a concrete association between the TyG index, uric acid levels, and prevalence of gout. The objective of this study was to investigate the correlation between this index and uric acid levels, as well as their potential associations with the incidence of gout.
Methods: Data derived from the Eighth Korea National Health and Nutrition Examination Survey conducted from 2019 to 2021 were used. The study population included adults >19 years of age andconsisted of 16,340 participants who were subjected to blood tests to measure their fasting blood glucose and triglyceride levels. Additionally, the participants responded to a questionnaire regarding the diagnosis of gout, making them eligible for inclusion in the study. The TyG index was categorized into quartiles.
Results: Of the 16,340 total subjects, 321(2.1 %) were diagnosed with gout. After an adjustment for age and metabolic parameters, the TyG index was positively related to serum uric acid levels (β = 0.247, p < 0.001). Compared to the risk in the lowest quartile group, as a reference, the adjusted odd ratio, with a 95 % confidence interval, for the incidence of gout was 2.002 (1.157–3.465) in the highest quartile group.
Conclusion: An elevated TyG index is associated with increased blood uric acid levels, and the TyG index is also associated with the prevalence of gout.
Harmonically M-convex Set-valued Function
Authors: Santana Gabriel Alberto , Valera-López Maira
Published: April 2024

This research aimed to introduce the concept of harmonically m-convex set-valued functions, which is obtained from the combination of two definitions: harmonically m-convex functions and setvalued functions. In this work some properties and characteristics are developed, as well as a inequality of the Hermite-Hadamard type for such functions.
Investigation into Radioactivity Levels in Soil Samples from Wheat Cultivation Sites in Kapchorwa District Uganda
Authors: Sead Sead Mohamed , Uzorka Afam , Olaniyan Ademola Olatide
Published: April 2024

Since the earth's formation, radioactivity has existed in our surroundings on a naturally occurring basis. Radionuclides of uranium, thorium, and potassium are found in quite large amounts in rocks and soils. The overuse of fertilizers and other poor farming practices cause radioactive materials to build up in the soil. These radionuclides are considered exposure hazards because of their radiation, which can lead to health problems including cancer in people who are exposed. As a result, worries about the potential health effects of this type of exposure to naturally occurring radiation sources in our surroundings are growing. Using a NaI(Tl) gamma ray spectrometer, the activity concentrations of three natural radionuclides, 238U, 232Th, and 40K, were assessed for soil samples taken from various locations within the Kapchorwa district wheat plantation region. The average values found for 238U, 232Th, and 40K are 47.8±4.1 Bqkg-1, 61.0±3.8 Bqkg-1, and 1339.05±65.3 Bqkg-1, respectively, all of which were above world average values. Radiological health hazard indices were calculated, including radium equivalent activity, absorbed dose rate, annual effective dose equivalent, external and internal health hazard indices, as well as gamma and alpha indices. The findings revealed that the annual effective dose equivalent (HR) and absorbed dose rate (DR) are respectively 0.58±0.03 mSvy-1 and 118.1±7.7 nGyh-1, and the mean value of radium equivalent activity is 246.9±10.4 Bqkg-1. The gamma and alpha health hazard indices have values of 0.93±0.05 and 0.25±0.02, respectively, whereas the external and internal health hazard indices have values of 0.66±0.04 and 0.79±0.04, respectively. The findings showed that although the soil's radioactivity levels were higher than acceptable limits established by international standards, the computed hazard indices were lower than acceptable limits established by international standards, indicating a low risk of radiation contamination in the region. Important information about the natural radioactivity levels in agricultural soils and their effects on the environment and public health in Kapchorwa District and surrounding areas is provided by this study.
Physical and chemical soil quality and litter stock in agroforestry systems in the Eastern Amazon
Authors: de Souza Francisco Elves Duarte , Santos Jesus de Nazaré dos , Martins Walmer Bruno Rocha , Santos Cassio Rafael Costa dos , Ferreira Eric Victor de Oliveira , Silva Raimundo Thiago Lima da , de Paula Manoel Tavares , Alves José Darlon Nascimento , de Oliveira José Sebastião Romano , Rodrigues Julia Isabella de Matos
Published: April 2024

The influence of biodiversity and age of agroforestry systems (AFS) on the provision of ecosystem services, such as nutrient cycling, needs to be better understood to support management practices that promote such services. This study aimed to quantify and compare litter stock and the physical and chemical attributes of soil in four AFSs with different ages and arrangements to a secondary forest (FLO) in the Eastern Amazon. Litter stock did not differ among the AFSs, but the youngest AFS was lower (5.73 ± 1.04 Mg ha− 1) than in FLO (11.42 ± 2.44 Mg ha− 1). Similarities were found between FLO and the oldest AFS for most of the soil chemical attributes. The soil pH in AFSs was higher than in FLO in the surface layer, and the organic matter content of FLO did not differ from 2 and 51-year-old AFSs. The Al content and aluminum saturation of younger and 26 years-old AFSs were lower than in FLO. Particle density and total porosity did not differ among ecosystems, while soil density in the two younger AFSs was higher than in FLO. According to PCA results, variables such as organic matter, CECpH7, H + Al, Al content, and m % tended to be higher in FLO and oldest AFS. It was evident that the maturity and diversity of AFSs are relevant factors for Amazonian agroforests, as they offer positive impacts on ecosystem functionality, such as nutrient cycling and water retention.
Injecting domain knowledge into graph neural networks for protein-protein interactions
Authors: Balbi Laura , Sousa Rita , Cotovio Pedro , Pesquita Catia
Published: April 2024

Most machine learning methods that explore protein-protein interactions rely exclusively on the network of protein interactions as input data. However, protein repositories are rich in information describing multiple protein aspects, and ignoring this wealth of information may be detrimental to predictive performance. In this paper, we investigate how injecting domain knowledge – the molecular functions proteins perform, the biological processes they are involved in and their cellular location – impacts the performance of graph neural networks on two fundamental predictive tasks: protein-protein interaction prediction and protein function prediction. We propose a novel approach that injects protein-level information in the form of knowledge graph embeddings computed over the Gene Ontology into state-of-the-art graph neural networks, replacing ad hoc strategies for node features.
We assessed the impact of our knowledge injection approach in two popular benchmarks: the Open Graph Benchmark (based on STRING) and the Human Reference Interactome. Experiments conducted with ten state-of-the-art graph neural network approaches and five representative knowledge graph embedding methods demonstrated that domain knowledge injection significantly improves performance on graph neural networks in both protein function and protein-protein interaction prediction.
Surgical Intervention and Long-Term Renal Outcomes of Congenital Ureteropelvic Junction Obstruction in a Young Adult Cohort
Authors: Stewart Alexandra , Olson Stephen , Lechner Brent , Watson Maura , Yuan Christina , Nee Robert
Published: April 2024

Purpose To evaluate the impact of surgical intervention on long-term renal outcomes for adult patients with congenital ureteropelvic junction obstruction (UPJO).Methods We queried service members diagnosed with UPJO from the United States Military Health System electronic health records from 2005 to 2020. We assessed demographic, laboratory, radiology, surgical intervention, and outcome data. We evaluated the impact of surgical intervention on renal function based on the estimated glomerular filtration rate (eGFR), hypertension (HTN, defined as any prescription for blood pressure [BP] medication and/or average of two BP readings ≥ 130/80mmHg more than 2 weeks apart), and changes in renal excretory function on radionuclide scans.Results We identified 108 individuals diagnosed with congenital UPJO; mean follow-up of 7 years. Mean age at diagnosis was 25 years; 95% male; 69% White, 15% Black. At diagnosis, median BP was 130/78mmHg and mean eGFR 93ml/min/1.73m2. Subsequently, 85% had pyeloplasty and 23% had stent placement. There were no significant differences in mean eGFR pre- and post-intervention (94 vs 93 ml/min/1.73m2, respectively; p = 0.15) and prevalence of defined HTN (59% vs. 61%, respectively; p = 0.20). Surgical intervention for right-sided UPJO significantly reduced the proportion of patients with delayed cortical excretion (54% pre vs. 35% post, p = 0.01) and T½ emptying time (35 min vs. 19 min, p = 0.009). Similar trends occurred with left-sided UPJO but were not significant.Conclusion Surgical intervention was not associated with significant differences in the long-term outcomes of kidney function and HTN prevalence in our young adult cohort. However, renal excretory function improved on radionuclide scans.
Observation of Atmospheric and Ionospheric Anomalies before the Nepal Earthquakes on 25th April and 12th May 2015
Authors: Simha C.Prasanna , Rao K. Madhusudhana , Dumka Rakesh. K.
Published: April 2024

Identifying pre-seismic atmospheric and ionospheric anomalies holds significant research importance but is fraught with challenges, particularly for earthquakes characterized by diverse magnitudes, focal depths, and focal mechanisms. This study investigates atmospheric-ionospheric disturbances associated with the Nepal earthquakes of April 25, 2015 (M=7.8) and May 12, 2015 (M=7.3), utilizing atmospheric and ionospheric parameters. Ionospheric parameters such as vertical total electron content (VTEC) and atmospheric parameters including outgoing long-wave radiation (OLR), cloud cover, and vertical temperature gradient (VTG) were collected from IGS GPS stations and INSAT 3D data provided by the Indian Meteorological Department (IMD). Notable VTEC anomalies were detected 3 and 10 days prior to the April 25, 2015 event and 2 and 6 days before the May 12, 2015 event. The study employed the inter-quartile range (IQR) and running median over one day to establish upper limit references for VTEC signatures during the 51-day period surrounding the Nepal earthquakes. The analysis revealed pronounced increases in VTEC near the earthquake epicentre, such as at stations LCK-4 and LHAZ, compared to more distant stations like IISC, HYDE, SGOC, and URUM. Prior to the earthquakes, a 54‒60% relative amplitude increase in VTEC was observed at these upper bound (UB) stations. Furthermore, examination of the global planetary index (Kp) and storm time disturbance index (Dst) over the 51-day period did not reveal any geomagnetic signatures attributable to geomagnetic storms during the seismic activity. OLR ranged from 240 to 340 watts/m2, observed four days preceding the event, while the vertical temperature gradient varied from 4.3 to 23.2°K. Daily OLR variations over the 51-day period exhibited significant anomalous atmospheric responses a few days prior to the earthquakes. The shallow depth of the earthquakes facilitated enhanced energy release from the seismic zones, potentially contributing to the augmentation of anomalous VTEC patterns.
Gossypiboma Mimicking an Ovarian Cyst, Discovered Two Years Post- Cesarean Section: A Case Report
Authors: OSMAN HAGIR , Masoud M. Sayed , MohamedAli Khattab Saeed Elkhazin , Fadl Hiba Awadelkareem Osman , Hamza Abdelrahman , Basheer Hind Abashar Mohamed , alfaraja Mohamed
Published: April 2024

This case report presents a unique instance of gossypiboma, a surgical complication characterized by the unintentional retention of foreign objects such as gauze or sponges within the peritoneal cavity. Despite its rarity, gossypiboma poses significant risks, including intestinal obstruction and abscess formation. We describe the case of a 37-year-old multiparous female who presented with abdominal pain two years post-cesarean section, initially diagnosed with an ovarian cyst. However, intraoperative exploration revealed a gauze-filled cyst adherent to the ovary and jejunum, highlighting the diagnostic challenge and the need for meticulous surgical evaluation. This is the first reported case of gossypiboma in Sudan in 2024, emphasizing the global prevalence of this medical error. Root cause analysis and curriculum modifications are essential to address this issue. Multidisciplinary collaboration is crucial for successful management, emphasizing the importance of prompt recognition and intervention. This case underscores the diagnostic complexities and the necessity for enhanced protocols to prevent similar occurrences, advocating for improved communication among healthcare teams to ensure optimal patient outcomes
Robust Distributed Learning under Least Squares Approximation
Authors: Zhang Zhaodu , Chao Yue , Ma Xuejun
Published: April 2024

Massive datasets pose a serious challenge to traditional statistical methods. Modal regression has greater robustness and high inference efficiency compared to mean regression and likelihood-based methods. In this paper, we present a robust distributed least squares approximation (RDLSA) method for heterogeneously distributed massive datasets under the modal regression framework. Specifically, we first approximate the local objective function for each worker/server/machine by using the Taylor expansion, where it is necessary to remain the main quadratic term. Then, each of local machines calculate their corresponding estimates and upload them to a master machine for obtaining the approximated aggregated estimator. This process yields a one-step global estimator such that one round of communication is required. Correspondingly, the consistency and asymptotic normality of the estimator are rigorously established under some mild conditions. To further reduce the estimation bias, we perform one Newton-Raphson iteration to obtain a two-step global aggregated estimator. In addition, we develop a variable selection procedure for the distributed modal regression under the robust least squares approximation procedure. Finally, we provide simulation experiments and a real data application to verify the superiority of our method.
A resilient type-III broken gap Ga 2 O 3 /SiC van der Waals heterogeneous bilayer with band-to-band tunneling effect and tunable electronic property
Authors: Ferdous Naim , Islam Md. Sherajul , Park Jeongwon
Published: April 2024

The potential of van der Waals (vdW) heterostructure to incorporate the outstanding features of stacked materials to meet a variety of application requirements has drawn considerable attention. Due to the unique quantum tunneling mechanisms, a type-III broken-gap obtained from vdW heterostructure is a promising design strategy for tunneling field-effect transistors. Herein, a unique Ga2O3/SiC vdW bilayer heterostructure with inherent type-III broken gap band alignment has been revealed through first-principles calculation. The underlying physical mechanism to form the broken gap band alignment is thoroughly studied. Due to the overlapping band structures, a tunneling window of 0.609 eV has been created, which enables the charges to tunnel from the VBM of the SiC layer to the CBM of the Ga2O3 layer and fulfills the required condition for band-to-band tunneling. External electric field and strain can be applied to tailor the electronic behavior of the bilayer heterostructure. Positive external electric field and compressive vertical strain enlarge the tunneling window and enhance the band-to-band tunneling (BTBT) scheme while negative electric field and tensile vertical strain shorten the BTBT window. Under external electric field as well as vertical and biaxial strain, the Ga2O3/SiC vdW hetero-bilayer maintains the type-III band alignment, revealing its capability to tolerate the external electric field and strain with resilience. All these results provide a compelling platform of the Ga2O3/SiC vdW bilayer to design high performance tunneling field effect transistor.
DQM Analysis of multi-Directional FGM Micro Plats for buckling and vibration
Authors: Rajasekaran Sundaramoorthy
Published: April 2024

In the realm of Micro Electro-Mechanical Systems (MEMS) ,comprehending their behaviour is paramount importance for practical applications. Analsing these structures often becomes intricate due to size effets,rendering traditional methods like Finite Element Analysis inadequate. This study aims to address this challenge by developing a micro-plate model integrating the modified couple stress theory, which capturesinherent size effects in MEMS. The primary objective is to investigate critical loads and resonant frequencies of mirco-plates through meticulous parametric and comparative analysis, considering length scale parameters, material gradient indices, and aspect ratios as per the modified couple stress theory. The research focuses on multi-layer multi-directional functionally graded sandwich thin rectangular microplates under mechanical loading, employing the principle of virtual displacement and Kirchhoff's hypothesis. Physical properties across thickness, length and width diections, along side various boundary conditions are examined usig Power law, Exponential and Sigmoidal law functions. This study models various types of functionally graded thin micro plates depending on the material variation in axial, depth and multi-directions using the modified differential quadrature method showing effectiveness, simplicity, and high accuracy. The results presented herein serve as a benchmark for validating future experimental findings. The notable advantage of using sandwich plates is the mitigation odelamination issues typically encountered in composite structures. Micro plate of complexgeometry with curved boundary has also been analyzed.
Inquisitive Motion Generation System based on a Free-Energy Model of Curiosity and Interest
Authors: Honda Shimon , Yanagisawa Hideyoshi
Published: April 2024

Product motion is a crucial design element, blending functionality with aesthetic appeal. Such motions establish an emotional bond between the product and its user. Engaging with the product stimulates curiosity and interest in its motion, encouraging repeated use. This study aims to formulate indicators for curiosity and interest in motion and to implement a computational system to generate motions that provoke inquiry. This study situates curiosity and interest as emotions crucial to the inquiry cycle, proposing that optimal prediction error (deviation from expected motion patterns) cultivates interest, while fluctuations in prediction error spark curiosity. Our analysis is based on the inquiry cycle, a mathematical model of emotions rooted in the free energy principle of brain function. We developed curiosity, motion, and interest measures from the model based on prediction error variation and reduction. The developed system can independently control prediction errors and their variations for a given open-loop mechanism. This system generates motions that control the magnitude of prediction errors by deviating from the trajectory of energy-minimizing motions. Using the semantic differential method and eye-tracking experiments measuring gaze duration, we found that interest correlates with prediction error in an upward-convex manner, and its variability induces curiosity. These results align with our model. The novelty of this study lies in experimentally verifying that applying moderate prediction errors and fluctuations in prediction errors is effective in increasing interest and curiosity in motion design. This research contributes design insights for engineers and designers seeking to enhance the appeal of product motions.
Combined with the insulin resistance index in assessing subclinical systolic function in newly diagnosed type 2 diabetes mellitus:An analysis based on automated functional imaging echocardiography
Authors: Li Shengnan , Chen Run , Cao Yan , Hu Zhongshun , Ni Danfeng , Du Zihui , Zhang Chaoxue
Published: April 2024

Background: In recent years, simpler and more practical indicators based on routine biochemical tests or anthropometric measurements have been widely utilized for the assessment of insulin sensitivity. However, limited research has been conducted to investigate the predictive value of these novel simplified measures in relation to subclinical left ventricular systolic dysfunction.
Methods: A total of 160 newly diagnosed patients with type 2 diabetes mellitus (T2DM) and 70 healthy subjects matched by age and sex were included in the study. Left ventricular function parameters were assessed using AFI echocardiography. Four indicators of insulin resistance (IR) were computed: Triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-c), the product of fasting triglycerides and glucose levels(TyG), TyG multiplied by the body mass index(TyG-BMI)and the Insulin resistance metabolic score(METS-IR). The binary logistic regression analysis identified clinical and ultrasonic risk factors associated with abnormal GLPS-AVG in patients with T2DM. Develop a multiple-index-based log P model for integrated application. The diagnostic efficacy of the log P model in predicting left ventricular systolic function impairment was assessed using ROC analysis.
Results: Competing risk regression revealed that BMI, IVSD, SBP and LA were significant risk factors for the reduction of GLPS-AVG in individuals with T2DM. Additionally, two IR index models were found to be closely associated with abnormal GLPS-AVG: TyG-BMI (6.227,p=0.000); METS-IR(7.436,p=0.000). ROC analysis results indicate that TyG-BMI, METS-IR, IVSD, SBP, LA and a combination of five other indexes have demonstrated certain efficacy in predicting and evaluating diabetic heart function reduction. Its ROC-AUC (0.95CI) are 0.750 (0.564 ~ 0.934), 0.774 (0.582 ~ 0.944), 0.702 (0.461 ~ 0.948), 0.737 (0.478 ~ 0.983), 0.726 (0.483 ~ 0.951), 0.878 (0.770 ~ 0.987) respectively.
Conclusion: Approximately 20% of newly diagnosed patients with T2DM exhibit early-stage left ventricular systolic dysfunction.The Log P model exhibited the highest predictive efficiency when applied in combination, with significantly higher sensitivity, specificity and accuracy than each individual application.
A Comparative Investigation of Disease Detection in Plant Pathology: A Study on the YOLOv3 and Gaussian YOLOv3Models
Authors: Haripriya M. , Radhika A. , Jeslin J.
Published: April 2024

Leaf disease detection is a critical task in precision agriculture, aiming to monitor and control the spread of plant diseases for sustainable crop management. Object detection models have shown promise in accurately identifying and localizing diseases on plant leaves in recent years. This paper explores the effectiveness of YOLOv3 (You Only Look Once) and a variant known as Gaussian YOLOv3 in the context of leaf disease detection. YOLOv3 is known for its real-time object detection capabilities and high accuracy. However, it may face challenges in accurately localizing subtle disease patterns and handling uncertainties in complex leaf images. To address these challenges, Gaussian YOLOv3 incorporates Gaussian components to model uncertainty and improves localization accuracy. The comparative analysis involves evaluating the performance of YOLOv3 and Gaussian YOLOv3 in terms of localization accuracy, speed, adaptability to diverse conditions, and training requirements. Experiments are conducted using a dataset comprising various leaf diseases under different environmental conditions. They enable timely interventions and agricultural decision-making, reducing crop losses and ensuring effective disease management.
Adaptive Multi-Scale Feature Fusion with Spatial Translation for semantic Segmentation
Authors: Wang Hongru , Wang Haoyu
Published: April 2024

In image segmentation tasks,the extraction of multi-scale features enables models to better adapt to targets of diverse scales and capture semantic information more comprehensively. Additionally, the rational utilization of receptive fields assists models in better comprehending both local and global image structures.In this work, we combine the advantages of these two approaches and propose a novel adaptive module termed the MFFM. Module similar to the human eye’s visual system adaptively adjusts the focus and perceptual range to maximize the capture of target features. However, fixed-size convolutional kernels may result in information loss or confusion, leading to inaccuracies in segmentation outcomes, especially when dealing with highly similar images. To address this issue,we introduce spatial shift mechanism to perform pixel-level translation of the feature map,and by taking into account the relative relationship between pixels, the network can learn more discriminative features, thereby enhancing segmentation accuracy. Based on this, we propose a network model called AMFFNet. We demonstrate the effectiveness of the proposed model on PASCAL VOC 2012 and ADE20K datasets, achieving the test set performance of 91.7% and 46.76% MIoU without any post-processing.
The Association Between Adolescent Adhd and Callous-unemotional Traits is Moderated by Electrophysiological Reinforcement Sensitivity
Authors: Koppány Domonkos , Hámori György , Réthelyi János M. , Bunford Nóra
Published: April 2024

Reward processing is a hypothesized ADHD intermediate phenotype and, as such, is suggested to improve prediction of relevant outcomes, above and beyond the clinical phenotype. Although both reward and punishment processing and ADHD are associated with CU traits, gaps in knowledge remain about adolescents, electrophysiological indices, and longitudinal relations. We examined, in N = 297 adolescents, whether accounting for ODD and sex, ERPs to gain and loss moderate the prospective association between ADHD symptoms and CU traits and whether any moderational effects are driven by ADHD risk status and domain of symptoms. Findings indicated ADHD symptoms were positively associated with Uncaring traits at low (b = .255, SE = .109, p = .020; 95% CI[.040, .469]), but not at moderate (b = .136, SE = .078, p = .085; 95% CI[-.019, .291]) or high (b = .016, SE = .080, p = .842; 95% CI[-.142, .174]) levels of Target P3, with this moderational effect apparent in adolescents at-risk for ADHD, for inattention symptoms (F(6, 92) = 2.299, ΔR2 = .138, p = .010). Electrophysiological reward and punishment processing improves prediction of CU traits above and beyond the ADHD clinical phenotype; in adolescents at-risk for ADHD, low electrophysiological response links elevated inattention symptoms to greater Uncaring traits whereas moderate and higher response may be protective.
Exploring the Interactive Effects of ZDDP, Metal Sulfides, and Carbon Nanotubes on the Lubrication Performance of a PAO Oil
Authors: Prieto Germán , Abdelnabe Juan Pablo , Ovando Enzo , Cárdenas Ignacio Silva , Antonelli María Mercedes , Tuckart Walter Roberto
Published: April 2024

This study investigates the frictional behavior and wear protection capacity of polyalphaolephin (PAO) oils additivated with combinations of zinc dialkyldithiophosphate (ZDDP), metal sulfides, and carbon nanotubes (CNTs) on steel surfaces. Various oil formulations, comprising PAO base oil with differing proportions of ZDDP, metal sulfides, and CNTs, were utilized to lubricate steel-steel contacts in block-on-ring tests. Both the blocks and rings were made of SAE 52100 bearing steel. The testing conditions selected for all the tests were 1 GPa of Hertzian contact stress, 1 m/s of sliding speed, and a total sliding distance of 3,600 m. Surface analysis was performed by means of SEM-EDS, laser confocal microscopy, and Raman microspectrometry. Results indicated that combining metal sulfides or CNTs with ZDDP notably reduced friction compared to ZDDP-only oil, with reductions ranging from 24 to 60%, depending on the formulation. However, wear rates varied considerably among formulations. Those containing ZDDP and Bi2S3 exhibited significant wear rate increases of 160 to 180% compared to ZDDP-only oil. Optimal wear protection for steel surfaces was achieved with ZDDP + CNTs and ZDDP + MoS2 combinations, resulting in wear rate reductions of 19 to 14% respectively.
Platelet (PLT), eosinophil (EOS), and albumin (ALB) are useful indicators for evaluating the risk of developing lupus nephritis (LN) in patients with systemic lupus erythematosus (SLE) Running head: indicators for evaluating the risk of developing lupus nephritis
Authors: Zeng Wanxin , Huang Cancan , Yi Sha , Xiong Xia , Zhong Guishu , Chen Yan
Published: April 2024

Objectives Although there have been extensive investigations of platelet (PLT), eosinophil (EOS), and albumin (ALB) in many diseases, their roles in systemic lupus erythematosus (SLE) with lupus nephritis (LN) remain unclear. Thus, the present study aimed to evaluate the value of PLT, EOS, and ALB levels and provide guidance for the clinical application of PLT, EOS, and ALB detection in Chinese SLE patients with LN. Methods Among 2060 enrolled SLE patients undergoing hospitalization, we included a total of 73 patients diagnosed with LN and 325 SLE patients without LN who completed the measurement of blood and LN screening between 2018 and 2022. All clinical characteristics and the blood measurement information of SLE patients were extracted and analyzed from the medical records. Univariate and multivariate logistic regression analyses were used to evaluate the possible relationship of PLT, EOS, and ALB to LN. Receiver operating characteristic (ROC) curve analysis was also performed to assess the discriminative ability of three ratios in predicting LN. The nomogram was performed to facilitate an individualized estimation of the risk of lupus nephritis in SLE patients. Results The LN group had lower PLT, EOS, and ALB levels than the SLE group (P < 0.01). Univariate logistic regression analysis indicated that three risk factors for LN were identified, including PLT (OR = 0.393, 95% CI 0.172–0.896,P = 0.026), EOS (OR = 0.108, 95% CI 0.027–0.439,P = 0.002), and ALB (OR = 0.351, 95% CI 0.127–0.972,P = 0.044). Multivariate logistic regression analysis also showed that, compared with the low groups, the high PLT group, high EOS group, and high ALB group had a lower risk of LN. In addition, ROC analysis and the nomogram comprised of PLT, EOS, and ALB revealed that these three predictors were determined as predictive indicators of LN in SLE patients and exhibited sufficient predictive accuracy, with the area under the characteristic curve (AUC) of 0.720 [95% confidence interval (CI) 0.658–0.782]. Conclusions Decreased levels of PLT, EOS, and ALB might be correlated with an increased risk of LN in Chinese SLE patients.
A novel capsule neural network for identification of rice leaf disease
Authors: Chen Yahong , Xiao Qingquan , Tang Huazhu , Xie Quan
Published: April 2024

A novel network model (RESCapsNet) for identification of rice leaf diseases was proposed by combining the traditional convolutional neural network and capsule networks. The results show the identification accuracy and F1_score of the proposed RESCapsNet is 99.63% and 99.6% on the public dataset from Kaggle, respectively. The accuracy of RESCapsNet is improved by 12.54% compared to the capsule network (CapsNet), although CapsNet only required 110 epochs to reach its optimal state, RESCapsNet required training 140 epochs to reach its optimal state. This method is effective in identifying and classifying rice leaf diseases, as shown by the experimental results, and can achieve early defense against rice leaf diseases.