bluuebunny/crossref_metadata_2025 huggingface dataset:
Robust Bluetooth AOA Estimation for Indoor Localization Using Particle Filter Fusion
Authors: Qiu Kaiyue , Chen Ruizhi , Wu Yuan , Guo Guangyi , Li Wei
Published: May 2024

With the growing demand for positioning services, angle-of-arrival (AoA) estimation or direction-finding (DF) has been widely investigated for applications in fifth-generation (5G) technologies. Many existing AoA estimation algorithms only require the measurement of the direction of the incident wave at the transmitter to obtain correct results. However, for most of the cellular systems such as Bluetooth indoor positioning system due to multipath and non-line-of-sight (NLOS) propagation, the indoor positioning accuracy is severely affected. In this paper a comprehensive algorithm is investigated that combines radio measurements from Bluetooth AoA local navigation systems with indoor position estimates obtained using particle filtering, which allows us to explore new optimised methods to reduce estimation errors in indoor positioning. First, particle filtering is used to predict the rough position of a moving target. Then, an algorithm with robust beam weighting is used to estimate the AoA of the multipath components. Based on this, a system of pseudo-linear equations for target positioning based on the probabilistic framework of PF and AoA measurement is derived. Theoretical analysis and simulation results show that the algorithm can improve the positioning accuracy by about 25.7% on average.
Climate Change and the Single Cell
Authors: Lamport Derek T
Published: May 2024

The power of movement in plants” by Charles Darwin details many examples of oscillatory growth exemplified more recently at the single cell level by pollen tube tip oscillations and associated ion fluxes, particularly Ca2+and H+. That implies an underlying growth oscillator based on the recent discovery that classical AGPs bind Ca2+ at the cell surface. The juxtaposition of AGPs with three other components embedded in the plasma membrane is evidence of a Ca2+ cycle that generates cytosolic Ca2+. It involves Ca2+ channels, auxin efflux “PIN” proteins and an auxin-activated proton pump that dissociates AGP-Ca2+ on demand. While the apparent simplicity of this system satisfies Occam’s Razor its hypothetical role as a global growth oscillator demands rigorous experimental appraisal. The wide ramifications extend from pollen tubes to stomatal guard cells. Stomata act as crucial components of a water hypercycle that contributes to homeostasis of a warming planet by regulating evaporative cooling, reflective cloud cover generated by vast forests and the high albedo of snow-capped mountains including polar ice-caps . The Gaia hypothesis of James Lovelock and Lynn Margulis is a brilliant metaphor.
Application of Machine Learning to Forecast Drought Index for the Mekong Delta
Authors: Duong Ha Hai , Phong Nguyen Duc , Ha Thuan Luong , Tang Thang Duc , Trinh Thang Ngoc , Nguyen Tien Minh , Nguyen Tu Minh
Published: May 2024

Droughts have a substantial effect on water resources, agriculture, and ecosystems on a worldwide scale. In the Mekong Delta of Vietnam, droughts exacerbated by climate change are significantly endangering the region's agricultural sustainability and output. Conventional forecasting techniques frequently do not capture the intricate dynamics of meteorological phenomena associated to drought effectively, prompting the exploration of more advanced methodologies. This work utilises artificial intelligence, par-ticularly machine learning methods like Gradient Boosting and Extreme Gradient Boosting (XGBoost), to enhance drought pre-diction in the Mekong Delta. The study utilises data from 11 meteorological stations spanning from 1990 to 2022 to create and evaluate Machine Learning models based on several climatic factors. We utilise Gradient Boosting and XGBoost algorithms to estimate the Standardised Precipitation-Evapotranspiration Index (SPEI) and evaluate their effectiveness in comparison to con-ventional forecasting techniques. The results show that Machine Learning, particularly XGBoost, surpasses traditional approaches in predicting SPEI accuracy at various time scales. XGBoost demonstrates skill in understanding the complex relationships between climatic factors, with R² values falling between 0.90 and 0.94 for 1-month forecasts. The progress highlights the potential of Machine Learning in improving drought management and adaptation tactics, proposing the incorporation of Machine Learning forecasting models into decision-making processes to enhance drought resistance in susceptible areas.
Impact of Shaking Exercise on Functional Recovery in Patients with Chronic Post-Stroke Upper Limb Paralysis: A Multicenter, Open-Label, Quasi-Randomized Controlled Trial
Authors: Hada Takuya , Hamaguchi Toyohiro , Abo Masahiro
Published: May 2024

Stroke causes disability and significantly affects patient quality of life. Post-stroke rehabilitation of upper limb function is crucial, as it affects daily activities and individual autonomy. Traditional rehabilitation methods often require frequent visits to specialized centers, which can be costly and challenging. This study investigated the effectiveness of a home-based self-training device, "Kenko Yusuri," in improving upper limb function in patients with chronic stroke. This multicenter prospective intervention study used a quasi-randomized controlled trial design. Ninety-three outpatients from five hospitals in Japan were enrolled and assigned to either the intervention group who used the "Kenko Yusuri" device or the control group who underwent conventional rehabilitation. All patients received botulinum toxin type A (BoNT-A) injections to treat upper limb spasticity. The primary outcome measure was the Fugl-Meyer Assessment (FMA) of upper-extremity motor function. Secondary outcomes included the modified Ashworth scale (MAS) score, range of motion (ROM), and chronic pain assessments. The intervention group demonstrated significantly greater improvements in FMA total scores than the control group. Patients with moderate paralysis experienced the greatest benefits from the intervention. There were no significant between-group differences in MAS scores or ROM measurements. Pain and wrist ROM showed improvement in the intervention group. Home-based training with a shaking device significantly improved upper limb function in patients with moderate chronic post-stroke paralysis. This approach aligns with the principles of use-dependent plasticity and offers a feasible and cost-effective alternative to traditional rehabilitation methods.
Parameter Identification of Flexible Link Manipulators Using Evolutionary Algorithms
Authors: Lara-Molina Fabian Andres
Published: May 2024

This paper addresses the parameter identification of a one-link flexible manipulator based on the experimental measurement of the inputs/outputs, the finite element model, and the application of evolutionary algorithms. A novel approach is proposed to find the values of inertia, stiffness, and damping parameters by minimizing the difference between the numerical model’s outputs and the testbed’s outputs, considering the joint position and acceleration of the link’s tip. The dynamic model is initially obtained using the finite element method and the Lagrange principle. A prototype of a single one-link flexible manipulator is used in the experimental application wherein the servomotor applies the input torque, and the outputs are the joint angle and the link’s tip acceleration. Then, an optimization problem minimizes the difference between numerical and experimental outputs to determine the set of parameters using evolutionary algorithms. A comparative analysis to obtain the identified parameters is established using genetic algorithms, particle swarm optimization, and differential evolution. The proposed identification approach permitted the determination of the dynamic parameters based on the complete dynamic model of the flexible-link manipulator, which is different from the approaches reported in the literature that identify a simplified model. This information is essential for the design of the motion and vibration control laws.
Sustainability of Palm Oil Business Partnerships through the Role of Social Capital and Local Wisdom: Evidence from Palm Oil Plantations in Indonesia
Authors: Baka Wa Kuasa , Rianse Ilma Sarimustaqiyma , La Zulfikar Zulfikar
Published: May 2024

Sustainable development can only be realised when the social, economic and environmental dimensions are considered altogether. Social capital and local wisdom offer important contributions to the development process and the capabilities of individuals and groups as development actors. This study analyses the role of social capital and local wisdom in managing business partnerships between farmers and palm oil plantation companies in North Konawe, Indonesia. Data were collected via in-depth interviews, field observations and focus group discussions and were analysed descriptively and qualitatively. Results underscore the importance of social capital and local wisdom in organising institutional programmes for strengthening palm oil business partnerships. Trust, social networks and participation negatively affect the sustainability of these partnerships, whilst local wisdom and social solidarity positively influence institutional strengthening. Inconsistency and lack of openness by companies can lead to a trust crisis that can threaten the sustainable operations of palm oil companies. Building a good cooperative commitment and maintaining collaboration play key roles in enhancing community welfare and increasing company profits. The social capital and local wisdom of farmer institutions in villages are expected to significantly contribute to the establishment of sustainable palm oil business partnerships.
Cholecalciferol Effects on Lipid Profile of Experimental Animals: A Scoping Review
Authors: Veonika Dea Anenta , Wiboworini Budiyanti , Muthmainah Muthmainah
Published: May 2024

Vitamin D is an essential nutrient that has various beneficial effects on the human body. The results of cholecalciferol supplementation are varied, and there has yet to be a comprehensive review regarding its effect on animal models. Therefore, this scoping review aims to summarize the evidence regarding the effect of cholecalciferol (vitamin D3) supplementation on the lipid profiles of animal subjects. PubMed, Scopus, and DOAJ were searched for original research articles published until 2022. Studies were included if they were experimental studies, cholecalciferol was used as a supplement, and the changes in the lipid profile were analyzed. A total of 260 articles were collected, of which 250 articles were excluded, and 10 articles were included for qualitative synthesis. All studies used oral routes to supplement cholecalciferol with various doses and duration ranging from several weeks to several months. Most studies reported reduced lipid parameters in serum or organ-specific animals supplemented with cholecalciferol. As conclusion, cholecalciferol reduces lipid content in animal subjects and may have a beneficial effect on populations with metabolic diseases such as diabetes and dyslipidemia. Further research is required to explore the mechanism of how cholecalciferol affects the lipid profiles of experimental animals.
Antidiabetic Potential and Metabolite Profile of Leaf and Stem Extract of Castanopsis tungurrut (Blume) A.DC.
Authors: Nabila Bilqis Zahra , Surya Muhammad Imam , Lailaty Intani Quarta , Damayanti Frisca , Nuringtyas Tri Rini
Published: May 2024

Diabetes mellitus is a metabolic disorder caused by high blood sugar levels. One species in the Castanopsis genus is proven with a hypoglycemic effect. Therefore, the study aimed to discover the potential of Castanopsis tungurrut as an antidiabetic. Sample extraction, α-amylase inhibition, glucose diffusion analysis, GC-MS analysis, and molecular docking were applied in this study. Maceration of the leaf ethanol extract showed the highest yield value of 21.08%, while the stem extract was 14.04%. Leaf ethanol extract and stem ethyl acetate extract showed the highest inhibiting α-amylase activity with an inhibition value of 33.74%±1.54 and 34.45%±1.08 at 1 mg/mL concentration. The glucose entrapment assay showed that these two extracts could inhibit the diffusion of glucose in the dialysis bag. The final result was glucose concentration in dialysate for the two extracts of 0.114±0.001 mg/mL and 0.116±0.001 mg/mL which was lower than acarbose in 0.120±0.004 mg/mL. GC-MS analysis showed 6 metabolites in leaf ethanol extract and 22 metabolites in stems ethyl acetate extract from an alkane, salicylic, cinnamic, terpene, steroid, and fatty acid. Molecular docking resulting between the compounds with α-amylase enzymes complex showed γ-sitosterol and ß-bisabolene from C. tungurrut extract have the potential to be developed as an antidiabetic drug due to its good inhibitory activity with binding affinity values of -9.1 and -6.9 that considered better and quite close to acarbose as control of -7.7.
RAPD Markers Distinguish Ground Beetle Species Using Genetic Polymorphism
Authors: Humadi Ashwak T. , Sultan Ammar Ahmed , Khaled Shifaa Walee
Published: May 2024

This study focuses on differentiating between two ground beetle species, Oryctes rhinoceros and Allomyrina dichotoma, using RAPD markers due to the limitations of phenotypic methods. Ten RAPD primers were employed to identify polymorphic markers. Results showed a total of 41 polymorphic bands, with primers OP-C06 and OP-C15 displaying significant variation in polymorphism percentages, 100% and 16.7% respectively. Primer OP-A08 demonstrated the highest efficiency rate (17.07%) and effectively distinguished between the two beetle species, unlike primers OP-B09, OP-B14, and OP-C10, which showed zero polymorphism. This study underscores the utility of RAPD markers, particularly OP-A08, in accurately identifying insect species, thereby advancing genetic classification techniques.
Highlights:

Effective Distinction: OP-A08 distinguished Oryctes rhinoceros and Allomyrina dichotoma.
High Efficiency: OP-A08 had the highest efficiency rate at 17.07%.
Reliable Classification: RAPD markers outperform phenotypic methods for insect identification.

Keywords: RAPD Markers, Genetic Polymorphism, Ground Beetles, Insect Classification, Molecular Genetics
The Alvezaúah properties of crude oil and associated water and the relationship with qualities Alheidrocorpunat resulting Fertile Mkami and central Iraq
Authors: Al-Obaidi Ryad Y.Q. , Farhan Ahlam M. , Al-Ameri THamer Khazal
Published: May 2024

Conducted Althilelat chemical models of crude oil back to the reservoir Fertile from the fields of Baghdad and Kut and models of crude oil back to the reservoir ??????? of Haklbe Tikrit and Baghdad were calculated their properties Alvezaúah Kalkthaqh and weight, quality and degree of August j (API) and know the quality Nfothma that was light or heavy and make the comparison between Alinvtin also conducted chemical analyzes of the two models of Almia associated with each of the oil above Almkmnin and measured Ktvthma and Zojithma and concentrations of some dissolved salts in them and clarify the relationship between the oil reservoir and water associated with oil fields...
Expand bandwidth high reflectivity of the far infrared region
Authors: Ghazi R Hayfa
Published: May 2024

Was expanded display high reflectivity of the spectral remote infrared (m j 14-8) adoption order Alcolmtin ????????? thickness optical northeastern quarter wavelength and compared with results of previous studies based Aldrashalhalah on Ndharah matrix distinctive amended and fall of light close to the vertical arrangement multilayer materials buffer and in thin films homogeneous and uniform properties deposited on germanium basis results showed that the best choice for governments and their kills to expand bandwidth high reflectivity is much easier for the infrared than the area visible in addition to the order of these stacks is the cornerstone of the filters other visual...
Incidence of nutritional anemia in baghdad and baquba
Authors: Al-Omar Mothana Abdul-Razaq , Al-Temimi Salem Saleh , Jafer Bahera Mahmmod
Published: May 2024

Anaemia is one of the most important problems of malnutrition in the world, especially in countries developing and anemia is associated inextricably important public health and HIV and morbidity and reduced mental capacity This study aims to determine the incidence of anemia for the period 1999-2000 among healthy adults outwardly and its relationship with some variablesjob related study sample included 200 male and 200 Antymn but the cities of Baghdad and Baquba reviewers for central labs
Seasonal occurence of aquatic fungi in tigris river during 2002
Authors: Al-Robaie Enaam Alii Slman , Ali Battol Z , Hassan Khaleed Faleh , Sabti Hossen Ali
Published: May 2024

Studied Seen fungi water in nine stations or selected sites along the Tigris River began from the city of Mosul in the north to Qurna in episodes were measured some chemical agents and Alvezaúah water ranged pH values ??(11p) between 7.0 to 8.3 either temperatures ranged between 10to 28 m study showed isolated 22 species of 14 genera of fungi
Spectral studies of Nickel(II) and Chromium(III)
Authors: Mjid Yahya A.
Published: May 2024

Complexes of Cr(III)andNi(II) ions with phthalate sulphanilate snthranillate hippurte and glycinate ions have been preparcd then the Nephelauxetic
A study copepoda invertebrates ecology in lower Zab
Authors: Al-Lami Ali Abed Al-Zahra , AbdulJabar R.A , Abdullah S.A. , Ali E.H
Published: May 2024

The samples were collected monthly crustaceans Mjmafah foot of two stations in tributary Zab down and two others in the Tigris River for one year with effect from November 2001 until October 2002 recorded during the study period the current 41 units taxonomic and were higher density of Mjmafah foot Guy Tigris River before the mouth of the tributary
Developing of bacterial mutagenic assay system for detection
Authors: Al-azawi Gaith lotfi , M. Zahra , Al-Khfaji Zahra M , Al-Mashadani Warkaa y , Al-Hassan Atheer A-M.
Published: May 2024

Been Antkhav three isolates of soil classified as follows: Bacillus G3 consists of spores, G12, G27 led Pal NTG treatment to kill part of the cells of the three isolates varying degrees treatment also led to mutations urged resistance to streptomycin and rifampicin and double mutations
Preparation and diagnosis rules Leno complexes with Ortho Hyderoxa Benzldaaan
Authors: Saleh Abbas Ali
Published: May 2024

I attended the new chief base of bilateral interaction Para Amino like 1 Phenyl 4 Bayrosolin 5 Online with Alsalesl Aldehid someone Allicand by careful analysis of the elements and infrared spectrum
Synthesis and some of the electrical properties of the polymer Mosul poly Berrol
Authors: Al-Mafraji Dr.Salah AbdAllah Hason
Published: May 2024

Thin films were prepared from poly Berrol way Ketrrukemaaih pole of platinum concentrations both Albaarol and salt in the electrolytic Alastontrel using positive effort of 7 volts on the pole and the electrical wiring of the membrane record
some Chemical effects on growth of azotobacter chroococcum wild-type and it's mutant-44
Authors: Al-Mofraji Talib K. , Al-Kubaisi Sanaa S.K.
Published: May 2024

the effecth of some chemicals on growth of two azotobacter chroococcum and aniline caused significant increase of growth
the effect of doping ratio on the opical properties
Authors: AL-Fawadi E.M.N.
Published: May 2024

the films of cdse pure and doped with copper ratio glass substrate effect od cucomcentration technique thikness doped with copper is an anonmg and the density of state increases
An experimental analysis of human motion based data collected from smartphones' accelerometers
Authors: Sao Neelabh , Dubey Sipi
Published: May 2024

In recent years, numerous studies have employed smartphone accelerometer data to identify human activities, leading to the development of increasingly complex and sophisticated algorithms. These evaluations acknowledge human actions. Commonly included in experimental evaluations are sitting, stair climbing, running, and walking. The topics of bicycling and driving are covered in some research. Activity recognition affects system performance and precision. The algorithm and model selection for human activity recognition during experimental evaluation is crucial. This is possible through the use of Support vector machine, k-nearest neighbours, decision tree, and deep learning algorithms such as CNNs and RNNs (RNNs). The algorithms and models will be determined by the type and complexity of the actions to be recognised and the available computational resources. CNN is used for experimentation in this paper. The accelerometer data are cleaned and transformed prior to evaluation processing. After training the system with pre-processed data, its performance is assessed using accuracy, recall, precision, and F1-score.
PDE6G inhibits the expression of CD71 in erythroid progenitor cells through the PDE6G/BHLHE40/miR144-3p/CD71 pathway, leading to red cell production obstacles and ultimately causing anemia in myelofibrosis
Authors: Wu Yong , Zhehan Luo
Published: May 2024

Myelofibrosis(MF) is a haematological malignancy. Most patients with MF will develop mild to moderate anemia. The MF-related anemia results from multifactorial factors. At present, the molecular mechanisms leading to MF-related anemia are still not fully understood. This study aimed to explore the role of PDE6G in MF-related anemia, verify its effect on the differentiation of erythroid progenitors, and reveal the molecular mechanism of action. This study examined PDE6G expression in bone marrow samples from Philadelphia chromosome-negative MPN and patients with MF without anemia, followed by mechanism studies using the HEL cell line (with JAK2V617F mutation) model and validation in human bone marrow specimens. We found that PDE6G expression was significantly higher in bone marrow samples from MF patients with anemia than in patients without anemia, and PDE6G inhibited the expression of CD71 in erythroid progenitors through the PDE6G/BHLHE40/miR-144-3p/CD71 pathway, leading to impaired erythroid production and ultimately myelofibrosis anemia. In conclusion, this study revealed the important mechanism of PDE6G in MF-related anemia, providing new ideas for research and treatment in this field, and is expected to provide a theoretical basis for the treatment of MF-related anemia.
Homologous relationship between FabG involved in fatty acid biosynthesis and SDR on chromosome II in the multi-chromosome pathogen Vibrio anguillarum
Authors: Kim Dong-Gyun , Park So Young , Rafquzzaman S. M. , Lee Jong Min
Published: May 2024

Vibrio anguillarum threatens fish and larval farming industries and human health worldwide. The fatty acids of cell membrane phospholipids are crucial to bacterial response to diverse environments and survival. Previously, short-chain dehydrogenase/reductase (SDR) was identified on chromosome II of the multichromosomal V. anguillarum. A comparison of SDR and the enzyme FabG-1b (encoded on chromosome I and responsible for the β-ketoacyl acyl carrier protein (ACP) reductase in fatty acid biosynthesis (FAS II)) showed that the amino acid sequence homology was only 33.2%; however, the core of functionality, which includes the NAD(P)-binding domain and the conserved region of the active site, the topologies predicted using sequence-based homology modeling, and the quaternary homotetramer-type structures showed a significant similarity. FabG-1b was specific to the substrates fluorinated and halogenated aliphatic ketones, aromatic ketones, and aromatic β-ketoesters and SDR toward non-fluorinated and non-halogenated aliphatic ketones, aromatic ketones, and non-aromatic β-ketoesters. This complementary catalytic efficiencies of the two enzymes on various substrates conclusively supports the hypothesis that the two enzymes are likely homologs. This is the first study to report potential paralogous enzymes FabG-1b and SDR in Vibrio. This information improves our understanding of bacterial FAS for establishing strategies to overcome infectious diseases caused by pathogenic strains and identify targets for developing new antibacterial agents.
Challenges and innovations in the surgical treatment of advanced Dupuytren disease by percutaneous needle fasciotomy: indications, limitations, and medico-legal implications
Authors: Basile Giuseppe , Amadei Federico , Prevot Luca Bianco , Tronconi Livio Pietro , Ciccarelli Antonello , Bolcato Vittorio , Zaami Simona
Published: May 2024

Background
Dupuytren disease, a chronic thickening and retraction of the palmar aponeurosis of the hands, may result in permanent and progressive flexion of one or more fingers. Percutaneous needle fasciotomy is a simple method that uses a hypodermic needle usually performed under local anaesthesia. The study aim was to report the postoperative results and complications using a percutaneous approach to treat Dupuytren contracture in a consecutive series of patients with advanced Dupuytren disease, also considering the relevant medico-legal implications.
Methods
Retrospective multicentre study of all patients with Tubiana stage 3–4 Dupuytren contracture treated with percutaneous needle aponeurotomy from 2012 to 2022. Patient demographics, disease severity, treatment-related complications, and the incidence of recurrence were identified. An overview of therapeutic treatment options has accounted for 52 relevant sources spanning the 2007–2023 time period.
Results
Overall, 41.7% (N = 200 ) of patients were females, the mean age was 72 years (60–89), the right hand was treated in 54.2% (N = 260 ) of patients. The little finger was involved in 50% of the patients. The 12 months mean PED was 9°, the mean quickDASH was 8, the mean URAM 6. Minor complications were reported in 18.7% (N = 90) of patients, typically skin lacerations (83.3%) with no clinical sequelae, and no major complications were reported. Recurrence occurred in 30% (N = 144) of patients.
Conclusions
Percutaneous needle fasciotomy is safe and reliable even in patients with advanced Dupuytren disease, resulting in predictably acceptable outcome with low risk of complications.
Biological aspects and Molecular Identification of Forensically Relevant Blow Flies under Seasonal Temperature and Humidity Variations in Egypt
Authors: Salem Abeer , Shaurub El-Sayed , Almadiy Abdulrhman , Zaher Eman
Published: May 2024

Blow flies play a crucial role in determining the post-mortem interval (PMI), yet the Egyptian blow fly fauna remains incompletely investigated. Here, we assessed some biological aspects of (Lucilia sericata, Chrysomya albiceps, and Chrysomya megacephala) that had collected from rabbit carcasses in Sharkia Governorate, and then reared in the laboratory under the influence of temperature fluctuation and humidity during spring (16–20°C; 40–60%), summer (23–27°C, 54–73%), autumn (13–17°C, 51–81%) and winter (9–13°C, 47–82%). The identification of these blow was confirmed using a short 5ʹ COI fragment (~ 342 bp). The different biological aspects studied were temperature dependent. The highest number of emerging adults, number of eggs laid per female and egg hatchability were in summer, followed by spring, autumn and winter. Preoviposition period, incubation period, maggot duration and pupal duration were inversely proportional with temperature. Adult females lived longer than males during the four seasons. The longest longevity of male and female of L. sericata was in spring. While, the longest male and female longevity of C. megacephala and C. albiceps was in winter. The phylogenetic analysis revealed 97, 99 and 99% similarity between L. sericata, C. megacephala and C. albiceps and their references.
Characterization of a Turbulent Boundary Layer Downstream of a Micro-Cavity Array
Authors: Severino Gianni F. , Silvestri Anton , Cazzolato Benjamin S. , Arjomandi Maziar
Published: May 2024

A micro-cavity array has been shown to locally reduce sweep and turbulence intensities by 13% and 14% respectively. This paper aims to identify the extent of the effect a micro-cavity array has on a turbulent boundary layer, and to observe the effects on the streamwise domain located significantly downstream of the installed cavity array. A fixed geometry array was investigated across two Reynolds numbers, (Reθ= 2,028 and 3,075) at four downstream locations (800 – 7,500 viscous wall units from the last row of orifices). All velocity data were obtained through single-component hot-wire anemometry and were compared against a canonical flat plate boundary layer at identical locations. At Reθ= 2,028 a reduction in time-averaged turbulence intensity was observed, and by approximately 5,000 wall units downstream the intensity was returned to a canonical flow’s intensity. This trend was not observed at Reθ= 3,075, as the turbulence intensity at 7,500 wall units downstream was 2.4% greater than the canonical counterpart. Sweep event intensities showed initial reductions just downstream of the array, though data on sweep events further downstream of the array are largely inconclusive due to the nature of their variance. The pre-multiplied energy spectra were reduced immediately after the last row of orifices at y+=50 by a maximum of 2% at Reθ=2,028 and 1.8% at Reθ= 3,075. Further downstream, the energy spectra of flow affected by the cavity array showed no signs of recovering to canonically expected values of streamwise turbulent kinetic energy, though these changes were observed in greater proportions in large-scale structures (λ+>4,000).
Development of a turbulent boundary layer over a micro-cavity array
Authors: Severino Gianni F. , Silvestri Anton , Cazzolato Benjamin S. , Arjomandi Maziar
Published: May 2024

A micro-cavity array has been identified as a potential passive boundary layer control device. This paper aims to provide insight into how a turbulent boundary layer develops over the surface of the array by characterizing the streamwise turbulent statistics of the boundary. Eleven distinct locations were investigated over the surface of the array under two free-stream velocity environments. Velocity data was obtained experimentally through single component hot-wire anemometry and under zero-pressure-gradient conditions. The statistics presented in this paper include turbulence intensity, sweep event intensity and pre-multiplied energy spectra, with all statistics normalized by friction velocity. The boundary was characterized for all locations for both a flat plate geometry and for when the array was installed. It was shown that the micro-cavity array was able to successfully attenuate streamwise turbulence statistics with maximum reductions in turbulence intensity and sweep intensity of 5% and 8.5% respectively. The pre-multiplied energy spectra were reduced by a maximum of of 26.9% at 50 wall units above the surface. Once the boundary had progressed approximately 15,000 wall units downstream of the first row of orifices the boundary spontaneously destabilized, resembling an unstable boundary affected by a rough wall.
Fast-CFLB: A Privacy-Preserving Data Sharing System for Internet of Vehicles Using Ternary Federated Learning and Blockchain
Authors: Li Jiaheng , Wu Qinmu
Published: May 2024

Vehicular networking technology using federated learning enhances data privacy and security compared to centralized methods. Yet, it requires further refinement to combat single-point failure and membership inference attacks, privacy concerns, and communication expenses. This paper employs federated differential privacy and blockchain integration to address these challenges, alongside ternary gradient technology and model compression to reduce communication costs. In differential privacy experiments, we have determined that federated differential privacy protection is closer to the accuracy of a no-privacy protection scheme compared to traditional differential privacy protection, especially when C ≥ 2. In ternary gradient experiments, we observed a reduction in training gradients of 14.99×, 15.54×, and 15.97× across three datasets. In layer sensitivity experiments, we found that the accuracy at top = 97%, 94%, and 91% is comparable to that at top = 100% (uncompressed). In blockchain experiments, The training effects and overall trends of blockchain models are similar to those of non-blockchain models.
Development of a Minimal Physiologically-Based Pharmacokinetic Modeling / Machine Learning Framework for Early Target Pharmacology Assessment
Authors: Mavroudis Panteleimon , Patidar Krutika , Pillai Nikhil , Dhakal Saroj , Avery Lindsay
Published: May 2024

Development of antibodies often begins with the assessment and optimizing of their physicochemical properties, and their efficient engagement to the target of interest. Decisions at the early optimization stage are critical for the success of the drug candidate but are constrained due to the limited knowledge of the antibody and target pharmacology. n the present work we propose a model-based target pharmacology assessment framework based on which optimal physicochemical properties of antibodies can be inferred from minimal physiologically based pharmacokinetic (mPBPK) modeling and machine learning (ML). Towards this goal, we aim to perform a high-throughput virtual exploration of physicochemical properties of antibody drug candidates and relate them to target occupancy (TO). We use a mPBPK model previously developed by our group that incorporates a multivariate quantitative relationship between antibodies’ physicochemical properties such as molecular weight (MW), size, charge, and in silico + in vitro derived descriptors with a known relation to PK properties. In this study, we perform an exploration of virtual antibody drug candidates with varying physicochemical properties, and virtual target candidates with varying characteristics to unravel rules for optimal antibody drug candidates and feasible drug-target interaction. We also identify that varying the antibody dose and dosing scheme, target form (soluble or membrane-bound), antibody charge, and site of action had significant effect on the optimal properties for antibody drug candidate selection. By unravelling new design rules for antibody drug properties that are dependent on model-based TO assessment, we deliver a first-in-class model-based framework towards better understanding of the biology-specific PK and ADME processes of antibody drug candidates proteins and reducing the overall time for drug development.
Effect of Variable Parameters on Droplet Icing Process in Delayed Proton Exchange Membrane Fuel Cell Flow
Authors: Yu Yongsheng , Lu Yirui , Jia Hekun , Dong Fei
Published: May 2024

Modifying the characteristics of the flow channel is essential to retard or prevent icing and improve the low-temperature operational performance of proton exchange membrane fuel cells (PEMFCs). This paper presents a two-dimensional transient mathematical model that investigates the influences of surface temperature, wettability, and volume size on the droplet icing process. The findings suggest that raising the surface temperature of the flow channel results in a longer droplet freezing time. Raising the surface temperature from 248.15 K to 268.15 K can delay droplet freezing time by up to 62%. Increasing the surface contact angle from 78° to 150° can delay droplet freezing time by 45%. An increase in droplet volume can also prolong the time required for droplet freezing. Increasing the droplet volume size from 1 µL to 4 µL can delay the droplet freezing time by 35%. Moreover, the optimal parameters for maximizing the duration of droplet freezing are identified using response surface methodology. The corresponding conditions are found to be a surface temperature of 267.96 K, a surface contact angle of 134.08°, and a droplet volume of 3.29 µL. This work offers valuable guidance for enhancing the low-temperature performance of PEMFCs through flow channel design optimization.
Evaluating the efficacy of few-shot learning for GPT-4Vision in neurodegenerative disease histopathology: A comparative analysis with convolutional neural network model
Authors: Ono Daisuke , Dickson Dennis W. , Koga Shunsuke
Published: May 2024

Introduction: Recent advancements in artificial intelligence, particularly with large language models like GPT-4Vision (GPT-4V)—a derivative feature of ChatGPT—have expanded the potential for medical image interpretation. This study evaluates the accuracy of GPT-4V in image classification tasks of histopathological images and compares its performance with traditional convolutional neural network (CNN).
Methods: We utilized 1515 images, including hematoxylin and eosin staining and tau immunohistochemistry, from patients with various neurodegenerative diseases, such as Alzheimer’s disease (AD), progressive supranuclear palsy (PSP), and corticobasal degeneration (CBD). We assessed GPT-4V’s performance using multi-step prompts to determine how textual context influences image interpretation. We also employed few-shot learning to enhance improvements in GPT-4V’s diagnostic accuracy in classifying three specific tau lesions—astrocytic plaques, neuritic plaques, and tufted astrocytes—and compared the outcomes with the CNN model YOLOv8.
Results: GPT-4V accurately recognized staining techniques and tissue origin but struggled with specific lesion identification. The interpretation of images was notably influenced by the provided textual context, which sometimes led to diagnostic inaccuracies. For instance, when presented with images of the motor cortex, the diagnosis shifted inappropriately from AD to CBD or PSP. However, few-shot learning markedly improved GPT-4V’s diagnostic capabilities, enhancing accuracy from 40% in zero-shot learning to 90% with 20-shot learning, matching the performance of YOLOv8, which required 100-shot learning to achieve the same accuracy.
Conclusions: Although GPT-4V faces challenges in independently interpreting histopathological images, few-shot learning significantly improves its accuracy. This approach is especially promising for neuropathology, where acquiring extensive labeled datasets is often challenging.
Adolescence as a Predictor of Adverse Pregnancy Outcomes: A comparative longitudinal study conducted in a national referral hospital in Western Kenya.
Authors: Mokua Veran Kemuma , Mutakha Godfrey Shichenje , Kosgei Wycliffe , Mishra Pallavi
Published: May 2024

Adolescents present with unusual reproductive health, anatomical, psychological, and social characteristics, a situation that predisposes them high-risk pregnancies, necessitating prioritized obstetric services. Therefore, this study compared maternal and fetal outcome between adolescent (15–19 years) and adult (20-30years) pregnant mothers who delivered at Moi Teaching and Referral Hospital (MTRH) in Western Kenya. It adopted a six-month (1st July to 31st December 2021) prospective case-control study (ratio 1:3) among 836 (209 adolescents and 627 adult mothers) expectant mothers admitted at MTRH labour ward for delivery services. Maternal sociodemographic and reproductive characteristics data were collected using an interviewer administered questionnaire. Additionally, pregnancy outcomes data were collected after delivery and documented in the same questionnaire. Statistically, mean and frequencies, tests of association (Fisher’s exact tests), risk ratios and multivariate logistic regression were conducted. Out of 836 participants, 547 (65.4%) were married (54 adolescents and 493 adults) and 289 (34.6%) were single. Level of education was distributed as primary (17.9%; n = 150), secondary (42.5%; n = 355) and Tertiary (39.5%; n = 330) with majority (56.3%: n = 112) of the adolescents being students. The mean antenatal visits were 3.960 ± 1.721 with more than two-thirds (68.1%) attending at least 4 visits. Adolescent mothers were significantly (p < 0.001) more likely (OR = 4.952; 95% CI: 3.313, 7.402) not to have used contraception prior to the current pregnancy, at risk of anaemia at labour (p = 0.008), hypertension in pregnancy (p = 0.011), preterm labour (p = 0.011), perineal trauma (p = 0.004) and having newborns with a low 5-minute Apgar score (RR = 1.601; 95% CI: 1.179, 2.174). In conclusion, expectant adolescent mothers have a significantly increased risk of adverse maternal and fetal outcomes compared to adults, warranting targeted obstetric care.
Malware Reverse Engineering with Large Language Model for Superior Code Comprehensibility and IoC Recommendations
Authors: Williamson Ashley Q. , Beauparlant Michael
Published: May 2024

Malware reverse engineering, the process of dissecting malicious software to understand its functionality and behavior, faces significant challenges due to the complexity and obfuscation techniques employed by modern malware. The application of Gemini Pro for interpreting reverse-engineered malware code introduces a novel and significant approach to enhancing the understanding of complex malware behaviors. By leveraging advanced natural language processing capabilities, the model provides detailed and accurate explanations of malware's functional components, offering substantial improvements over traditional analysis methods. The study demonstrates the model's proficiency in identifying key operational mechanisms and recommending relevant indicators of compromise, which are crucial for effective threat detection and mitigation. A comprehensive comparative analysis reveals that Gemini Pro outperforms conventional static and dynamic analysis tools in terms of clarity, coherence, and time efficiency. Detailed case studies of various malware samples, including Ramnit, Kelihos, and Lollipop, illustrate the model's ability to generate clear and actionable insights, thereby facilitating better decision-making in cybersecurity contexts. The findings underscore the potential of integrating advanced natural language processing models into cybersecurity workflows to significantly enhance the efficiency and effectiveness of malware analysis and mitigation efforts.
Termal Değişimlerin Tinkal Katkılı Kum-Bentonit ve Zeolit-Bentonit Karışımlarının Kayma Dayanımına Etkisi
Authors: Alpaydın Sükran Gizem , Yükselen Aksoy Yeliz
Published: May 2024

Atık depolama alanları ve enerji geo-yapılarında geçirimsiz mühendislik bariyeri olarak kullanılan bentonit içerikli karışımlar zamanla termal etkiler altında değişimlere maruz kalabilirler. Zeminlerin, bu termal değişimler altında mühendislik özelliklerinin bozulmadan uzun süre korunması enerji geo-yapısının performansı ve çevre ve insan sağlığı için oldukça önemlidir. Bu çalışma kapsamında, sıcaklığın (25 ve 80 °C) ve sıcaklık döngülerinin sıkıştırılmış kum-bentonit ve zeolit-bentonit karışımlarının kayma dayanımı davranışı üzerindeki etkisi araştırılmıştır. Ayrıca sıcaklığa karşı direnci yüksek bir bor minerali olan tinkal, karışımlara ilave edilmiş ve bu katkının yüksek sıcaklıklarda karışımların kayma davranışına etkisi incelenmiştir. Karışımların kayma dayanımı genel olarak artan sıcaklıkla %5-%15 aralığında artış göstermiştir. Ayrıca tinkal ilavesi özellikle kum-bentonit karışımları için kayma dayanımı açısından faydalı bulunmuştur.
Enhancing Suspension System Control Performance Using PID Controller Incorporated Low-Pass Filter Optimizated with Genetic Algorithm
Authors: Şenaslan İbrahim , Bilgiç Boğaç
Published: May 2024

In this study, a filter has been incorporated to enhance the performance of the PID controller, which is commonly used for controlling suspension systems. While designing this filter, the insipration has been the low-pass filter used in sliding mode controllers to prevent chattering and uncertainties in system parameters, unlike conventional PID controller filters. Additionally, the filtered force value was combined with the force value obtained from the PID controller using an equation based on a coefficient, and filter coefficients were optimized through genetic algorithms. As a result of the optimization, the designed controller was simulated for various road inputs that could be encountered, and results were obtained. By comparing the results obtained with a PID controller without a filter and without a controller, the performance of the designed controller is clearly shown according to IAE and ISE criteria. Robustness of the controller was evaluated under varying mass conditions and its performance was given as a table.
Uydu Esnek Kanatlarının Artık Titreşim Kontrolüne Yönelik Yapay Arı Kolonisi Ve Guguk Kuşu Optimizasyon Algoritmaları ile LQR Denetleyici Tasarımı
Authors: Kaya Ferhat , Conker Çağlar
Published: May 2024

Sunulan çalışma, esnek bir uydu kanadı için doğrusal kuadratik regülatör (LQR) denetleyici parametrelerinin çok amaçlı optimizasyonunda Yapay Arı Kolonisi ve Guguk Kuşu metasezgisel optimizasyon algoritmalarının tasarımı ve performans analizi hakkında ayrıntılar sunmaktadır. Kontrol yanıtlarının önemli parametreleri göz önünde bulundurularak yeni bir çoklu amaç fonksiyonu tasarlanmış ve Yapay Arı Kolonisi (ABC) ve Guguk Kuşu (CS) metasezgisel algoritmaları ile optimize edilmiştir. Algoritmaların başlangıç değerleri için farklı farklı üçer konfigürasyon belirlenerek bu konfigürasyonlar üç farklı (10,50 ve 100) popülasyon boyutu değerleri için 100 iterasyonda simülasyonlar yapılarak elde edilen sonuçlar karşılaştırılmıştır. Daha başarılı kontrol yanıtlarına ulaşan konfigürasyonlar ile literatürde aynı düzenek ile yapılan bazı çalışmalar karşılaştırılmaktadır. Elde edilen sonuçlar literatürde mevcut bulunan, PSO, m-PSO algoritmaları ve geleneksel tasarlanmış LQR denetleyici çalışmaları ile kıyaslanarak önerilen yaklaşımın etkinliği gösterilmiştir. Önerilen çoklu amaç fonksiyonu ve Guguk Kuşu Algoritması, esnek uydu kanadı sapma açısında PSO algoritmasına kıyasla %37,56 ve m-PSO algoritması ile karşılaştırıldığında ise %61,87 oranında daha üstün bir performans göstermiştir.
Adjustable Friction Force of Elastic Post via Regulating Internal Cavity Pressure
Authors: Eray Turgay
Published: May 2024

The objective of this study is to investigate and obtain an adjustable friction force between an elastic polymeric post with cavity and a rigid, smooth, flat surface. Elastic cylindrical posts made of polymers are generally used as surface texturing components. In this study, the friction force of the elastic cylindrical posts with a flat tip in contact with a smooth and rigid surface was adjusted by a pneumatic-based actuation system. Finite-element based simulation was performed to adjust the friction force of the cylindrical posts by pressurizing the inner cavity of the posts. The frictional contact between the elastic posts and the counter rigid surface was modeled using the Amontons-Coulomb friction law, neglecting the adhesive contribution. The friction force amplitude was calculated with different cavity dimensions of the elastic posts and different cavity pressure values. The results show that the presence of an internal cavity reduces the friction force, and the cavity diameter has more influence on the reduction of the friction force than the cavity height. In conclusion, regulating the cavity pressure was shown to be an effective method of adjusting the friction force.