bluuebunny/crossref_metadata_2025_split huggingface dataset:
Intelligent Caching and Offloading Technique for Dew-assisted Mobile IoTs: A Distributed Deep Reinforcement Learning Framework
Authors: Mahapatra Abhijeet , Pradhan Rosy , Majhi Santosh Kumar , Mishra Kaushik 
Published: July 2024

Abstract

Cloud computing including mobile IoT devices infrastructure have grown to be a key component of future high-performance computing networks because they can supply distributed, hierarchical, and fine-grained resources. The secret is to combine the optimization of compute offloading and service caching. However, dynamic tasks, heterogeneous resources, and coupled decisions pose three major obstacles to the joint service caching and compute offloading dilemma. In this paper, we study how Dew-assisted mobile IoT devices and Fog-Cloud computing networks can benefit from the simultaneous processing for caching of various services and computational offloading. We formulate the optimization problem specifically as minimizing the NP-hard long-term average service delay. We provide thorough theoretical analysis and divide the topic into two smaller issues, i.e., processing for computation offloading and service caching. To answer the defined problem, where several Dew-assisted mobile IoT devices and a Cloud VM jointly determine the caching-action and offloading-action, respectively, we developed a unique Distributed-Deep Reinforcement Learning (DDRL) technique. The suggested framework beats multiple existing techniques regarding the average service delay across several scenarios, according to the findings of trace-driven simulations. When compared to methods based on reinforcement learning, our framework delivers an impressive 39% reduction in the average service delay and an approximate 37% improvement in convergence based on a practical real-world environment.
The Algebraic Extended Atom-type Graph-Based Model for Precise Ligand--Receptor Binding Affinity Prediction
Authors: Mukta Farjana Tasnim , Rana Md Masud , Meyer Avery , Ellingson Sally , Nguyen Duc D. 
Published: July 2024

Abstract

Accurate prediction of ligand-receptor binding affinity is crucial in structure-based drug design, significantly impacting the development of effective drugs. Recent advances in machine learning (ML)--based scoring functions have improved these predictions, yet challenges remain in modeling complex molecular interactions. This study introduces the AGL-EAT-Score, a scoring function that integrates extended atom-type multiscale weighted colored subgraphs with algebraic graph theory. This approach leverages the eigenvalues and eigenvectors of graph Laplacian and adjacency matrices to capture high-level details of specific atom pairwise interactions. Evaluated against benchmark datasets such as CASF-2016, CASF-2013, and the Cathepsin S dataset, the AGL-EAT-Score demonstrates notable accuracy, outperforming existing traditional and ML-based methods. The model's strength lies in its comprehensive similarity analysis, examining protein sequence, ligand structure, and binding site similarities, thus ensuring minimal bias and over-representation in the training sets. The use of extended atom types in graph coloring enhances the model's capability to capture the intricacies of protein-ligand interactions. The AGL-EAT-Score marks a significant advancement in drug design, offering a tool that could potentially refine and accelerate the drug discovery process.
SPLENIC HAMARTOMA: a case series
Authors: Tirotta Daniela , Lena Claudia , Muratori Paolo 
Published: July 2024

Abstract

Hamartomas are rare and benign tumors of the spleen. Most patients are asymptomatic and splenic hamartomas are usually incidentalomas. The common clinical manifestations are splenomegaly, spontaneous rupture, anemia, thrombocytopenia and digestive symptoms (loss of appetite and abdominal pain). It affects all age, mostly the elderly peoples.
The literature shows a strong association between splenic hamartoma and hematologic and solid malignancies (especially squamous cell carcinoma, renal cell carcinoma, and thymoma) , so when a splenic mass is detected especially in a patient with known malignancy, differential diagnosis is very important . For the same reason, the diagnosis of hamartoma in healthy people, needs to follow-up in order to monitoring possible association with neoplastic diseases.
In this context CEUS is a promising, cost-effective modality , because it shows 3 characteristic features of splenic hamartomas (hypervascularity, heterogenity, reticuloendothelial system detection) .
We described a series of cases of splenic lesions in which the use of CEUS shows typical aspects of hamartomas, observed consecutively in our internal ultrasound clinic in 2023
A systematic review of maternal and perinatal health outcomes in the context of epidemic threats: towards the development of a core outcome set.
Authors: Mazzoni Agustina , Berrueta Mabel , Babinska Magdalena , Nigri Carolina , Ortega Vanesa , Salva Florencia , Ciapponi Agustín , Bonet Mercedes 
Published: July 2024

Abstract

Objective
To systematically identify and classify maternal and perinatal health outcomes reported in research conducted in the epidemic and pandemic context.
Study design and Setting
We conducted a systematic review following Cochrane Methods. We searched MEDLINE, EMBASE, LILACS, SCI-EXPANDED, CINAHL, Cochrane Central Register of Controlled Trials, PsycINFO, AMED, ClinicalTrials.gov and ICTRP, between January 2015 and March 2023. Experimental, quasi-experimental, observational studies, phase IV trials, and post-marketing studies, published protocols and ongoing registered studies reporting maternal and perinatal health outcomes were included. Studies only reporting coverage of interventions, access to routine health services, clinical presentation of infectious diseases, and reviews were excluded. A sampling strategy was used for COVID-19 studies, due to their very high numbers. Outcome verbatims were extracted and categorized in unique outcome, and further classified into domains and subdomains. Frequency of outcome reporting was calculated.
Results
94 maternal and pregnancy and 47 unique neonatal outcomes were identified, from a total of 917 and 657 verbatims, respectively, reported across 440 included studies. At least 20% of included studies reported maternal and pregnancy outcomes of mode of delivery (56.1%), stillbirth (33.0%), preterm birth (28.6%), hypertensive disorders of pregnancy (26.6%), and maternal death (20.7%). These outcomes were identified across all three types of studies identified (epidemiological, product development or post-authorization surveillance). Gestational age at birth (29.8%), congenital malformations of the nervous system (26.1%), birth weight (23.4%), neonatal admission to intensive care unit (23.2%), and neonatal death (19.1%) were the most frequently reported neonatal outcomes.
Conclusions
Our study provides the basis for developing a core outcome set to measure maternal and perinatal health during outbreaks, which would help improve data collection of harmonized data, data synthesis, and timely development of informed public health guidance and clinical care responding to the needs of pregnant women. .
Investigating Deceptive Fairness Attacks on Large Language Models via Prompt Engineering
Authors: Thistleton Emily , Rand Jason 
Published: July 2024

Abstract

Artificial intelligence systems, particularly those employing natural language processing techniques, have increasingly been scrutinized for their potential to propagate and amplify societal biases. Addressing the vulnerability of these systems to deceptive fairness attacks, where subtly crafted prompts manipulate outputs to introduce bias, is both novel and critical in ensuring ethical AI deployment. The research investigates how LLMs can be systematically compromised through deceptive prompt engineering, revealing significant impacts on fairness metrics such as demographic parity, equalized odds, and disparate impact. The experimental design included the development of an extensive dataset of neutral and deceptive prompts, automated interaction with LLMs, and a robust analysis framework to assess the biases in responses. Results demonstrated substantial deviations in fairness metrics under deceptive conditions, highlighting the need for advanced detection and mitigation strategies. Future work should focus on enhancing the resilience of LLMs through real-time detection algorithms, ethical design principles, and continuous monitoring to uphold fairness across diverse applications. The findings emphasize the urgency of addressing bias in AI to prevent the perpetuation of inequality and ensure equitable technology deployment.
Okweraliikirira and Okwenyamira: Idioms of Psychological Distress Among People Living with HIV in Rakai, Uganda
Authors: West Nora S. , Nakubulwa Rosette , Murray Sarah M. , Ddaaki William , Mayambala Denis , Nakyanjo Neema , Nalugoda Fred , Hutton Heidi E. , Surkan Pamela J. , Kennedy Caitlin E. 
Published: July 2024

Abstract

Introduction: Health and illness experiences are positioned within social and cultural contexts. Understanding the mental health and psychological distress of people living with HIV in highly affected communities is critical to addressing their needs and to ensure programming and interventions are targeted and appropriate.
Methods: Grounded in the ethnomedical theoretical perspective, we conducted qualitative interviews to understand the experience and expression of psychological distress by people living with HIV in Rakai, Uganda. Participants included adults living with HIV (n=20), health workers (counselors, peer health workers, nurses, n=10), and key informants (n=12). Interviews were audio recorded, transcribed/translated, coded, and analyzed using thematic analysis.
Results: Two idioms of distress, okweraliikirira (worry/apprehension) and okwenyamira (deep/many thoughts/lots of thoughts) were described as impacting people living with HIV. Both idioms were said to be alleviated by social support or counseling, but if left unaddressed could lead to more severe mental health problems and poor ART adherence.
Conclusion: People living with HIV understand their psychological distress through culturally specific idioms; such distress can have deleterious impacts on well-being. Incorporating idioms of distress into screening and treatment for people living with HIV may improve identification of individuals in need and overall health services to address this need.
Community Composition and Seasonal Dynamics of Microplastic Biota in the Eastern Mediterranean Sea
Authors: Davidov Keren , Marsay Katherine S. , Itzahri Sheli , Rubin-Blum Maxim , Sobral Paula , Kranzler Chana F. , Oren Matan 
Published: July 2024

Abstract

Marine plastic pollution poses a growing environmental threat, with microplastics accumulating in the global oceans. This study profiles the seasonal dynamics and taxonomic composition of the plastisphere, the microplastic ecosystem, in the Eastern Mediterranean Sea. Using long-read 16S and 18S metabarcoding, we analyzed offshore microplastic and whole seawater samples across each season over a two-year period. The analysis revealed a higher richness of prokaryotic communities on microplastics compared to seawater, which was predominantly composed of Proteobacteria and Bacteroidota and exhibited notable seasonal variability. Benthic eukaryotes were enriched on microplastics compared to the surrounding seawater. Diatoms (Bacillariophyceae), in particular, showed significant enrichment within the microplastic eukaryotic community with primarily pennate diatoms of Amphora, Navicula, and Nitzschia genera, whereas the seawater included mostly centric diatoms. Seasonal fluctuations were less pronounced in the microplastic communities than in seawater, highlighting the relative stability of this new human-made ecosystem. These findings underscore the unique ecological niche of microplastic-associated communities in marine environments.
Exploring School Principal Leadership: A Case Study of Upper Secondary School in Northwestern Cambodia
Authors: Sam Rany , Tieng Morin , Yoeng Hak , Thay Sovannpitou , Chiv Sarith 
Published: July 2024

Abstract

This study aims to achieve four main objectives: (1) to identify the characteristics of turnaround leadership among Cambodian upper secondary school principals; (2) to investigate the factors influencing turnaround leadership; (3) to examine principals' roles in implementing turnaround leadership in provincial schools; and (4) to explore actionable recommendations for improving turnaround leadership in low-performing schools. The study uses a qualitative case study approach to investigate the dynamics of turnaround leadership in upper secondary schools across six northwestern provinces of Cambodia: Battambang, Pursat, Pailin, Banteay Meanchey, Oddor Meanchey, and Siem Reap. The data were collected through semi-structured interviews with 21 school principals recognized for their effective turnaround leadership. The findings provide insights into best practices and formulate recommendations to enhance turnaround leadership in Cambodian high schools. The findings provide insights into best practices and formulate recommendations to improve turnaround leadership in Cambodian high schools.
"How will I know the results if I self-test at home?" – At-home HIV self-testing vs. at-clinic HIV testing preference among trans-women in Ghana's Slums. BSGH-015
Authors: Abu-Ba’are Gamji Rabiu , Shamrock Osman Wumpini , Agbemedu George Rudolph Kofi , Dakpui Henry Delali 
Published: July 2024

Abstract

Despite a higher HIV prevalence (28%) among trans-women compared to other groups, no studies have examined HIV testing preferences among trans-women in Ghana. However, they continue to face individual and structural barriers to HIV testing in the country. This study therefore marks the first investigation into the HIV testing or self-testing preferences of trans-women in the country. A community organization used snowballing to recruit trans-women (n=20) to participate in face-to-face interviews about their experiences with testing and perspectives about HIV self-testing in comparison to traditional testing in clinics. Using NVIVO, we coded and conducted a thematic analysis to understand the participants' perspectives. Three categories of preferences emerged: 1) Some shared a preference for HIV self-testing at home because it offers privacy and confidentiality, saves time and transportation costs, and swerves stigmatizing attitudes of health workers. 2) Some prefer testing at a clinic as it offers the availability of professional care; they cannot conduct self-testing and interpret the results successfully, but they can access counseling therapy and other STI testing at healthcare facilities. 3) Others had mixed location preferences, expressing that they could benefit from both and use either option based on availability. The preferences expressed by participants suggest a need for holistic services where trans-women can test using self-testing kits and also have access to additional STI tests or counseling and linkage to care. It also points to the need to focus on fundamental issues such as ensuring privacy and confidentiality and better experiences in healthcare facilities as they remain drivers and deterrents for both testing approaches and potential linkage to care.
Beyond Lateral Expansion: A Multi-parameter Regression-based Model for Inferring Radial Propagation Speeds and Transit Time of Coronal Mass Ejections
Authors: Kyeremateng Kwabena , Hamadab Amr , Elsaidd Ahmed , Mahrousa Ayman 
Published: July 2024

Abstract

Coronal mass ejections (CMEs) have an important kinematic parameter: the propagation speed (Vp), which can be used to determine the transit time of Earth-directed CMEs. This study examines the association between the propagation speed (Vp) and the expansion speeds of 183 interplanetary coronal mass ejections (ICMEs) from 2009 to 2023. We used multiple regression analyses to demonstrate that the Vp of the ICME may be inferred from more than the lateral expansion speed (Vlat). Four regression-based model (RGBM) equations were derived using the solar wind speed (Vsw), the angular width (AW), bulk expansion (Vblk), front expansion (Vfrt), and lateral expansion (Vlat) speeds of the CME to estimate both the Vp and transit times of near-Earth-directed ICMEs/shock. A total of 28 halo ICMEs were used to validate RGBM equations. The most accurate calculation yielded a 6.43-hour mean absolute error (MAE). A feed-forward neural network (FFNN) model was used to estimate the transit times of the 28 halo ICMEs, with an observed MAE of 4.56 hrs. The propagation speed of the RGBM equations that produced the lowest MAE was incorporated into the drag-based model (DBM) to determine the transit times of ICMEs/shocks. The MAE associated with the DBM was found to be 6.03 hrs.
(Almost) everything is a Dicke model - Mapping non-superradiant correlated light-matter systems to the exactly solvable Dicke model
Authors: Schellenberger Andreas , Schmidt Kai Phillip 
Published: July 2024

We investigate classes of interacting quantum spin systems in a single-mode cavity with a Dicke coupling, as a paradigmatic example of strongly correlated light-matter systems. Coming from the limit of weak light-matter couplings and large number of matter entities, we map the relevant low-energy sector of a broad class of models in the non-superradiant phases onto the exactly solvable Dicke model. We apply the outcomes to the Dicke-Ising model as a paradigmatic example [Phys. Rev. Res. 2, 023131 (2020), Sci. Rep. 4, 4083 (2014)], in agreement with results obtained by mean-field theory [Sci. Rep. 4, 4083 (2014)]. We further accompany and verify our findings with finite-size calculations, using exact diagonalization and the series expansion method pcst^{++}++ [Phys. Rev. A 108, 013323 (2023)]
Identification of oil contamination in process water using fluorescence excitation emission matrix (FEEM) and parallel factor analysis (PARAFAC)
Authors: Madhav Heena , Gilmore Adam 
Published: July 2024

ABSTRACT

Fuel oil is widely used within Eskom, a power generation company in South Africa. Eskom's coal-fired power stations use up to 30,000 L of fuel oil per hour during a cold start-up, a consequence of which results in oil leaks to the dams. Oil contamination in water treatment plants causes irreversible membrane fouling, requiring costly replacement. This research work focused on the development of a rapid method for the identification of low concentrations of the water-soluble oil component fraction of crude fuel oil. For the developed method, known volumes of the water-soluble fraction of crude oil were spiked into various matrices of process water. FEEMs were collected using the patented HORIBA Aqualog spectrometer and data were modelled with PARAFAC. The results were well described with a four-component model, which included an oil component and three natural organic matter components, with a split-half validation match of 90%. The oil component was verified using linear regression of the PARAFAC component scores yielding an R2 value of 0.98. From the scores, a qualitative pass/fail test was developed such that process water can be analysed and subjected to the model to indicate the presence of oil contamination beyond a damaging threshold.
Study of Heavy Metal Removal with Porous Nanocomposite Scaffolds based on Hybrid Inorganic/Organic Nanoparticles (MSN@COF)
Authors: Rezaii Ebrahim , Mahkam Mehrdad , Rezaii Mohammad 
Published: July 2024

Introduction:
Hybrid inorganic/organic nanoparticles are used to make nanocomposites. These nanocomposites combine the different properties of the organic polymer and the inorganic nanoparticles, which improves the overall system properties.

Methods:
In this research work, Mesoporous Silica Nanoparticle (MSN), amino-functionalized MSNs, and Covalent Organic Frameworks (COFs) were synthesized using a special approach. In this work, in order to take advantage of the properties and characteristics of both porous nanomaterials and porous nanocomposites of COF-grown MSN were synthesized by a special method and with two approaches, and the porosity of the nanocomposites and synthesized nanomaterials was analyzed by BET analysis.

Results:
The synthesis of the products was confirmed by XRD, TGA, EDS, FT-IR, FE-SEM, TEM, and Zeta potential analyses. The heavy metals zinc and cadmium were removed using these nanomaterials as an inorganic/organic hybrid adsorbent in the following, and various ab-sorption properties were examined in these nanoabsorbents.

Conclusion:
The removal of heavy metals from these hybrid nanoabsorbents is particularly effective.
Validation, Reliability, and Clinical Significance of the Arabic Version of Bristol Rheumatoid Arthritis Fatigue Multi-Dimensional Questionnaire
Authors: Aglan Loay , Kamal Mohammed , Mokhtar Mona , Abdelrahman Eman Kamel , Gaafar Sherine M. 
Published: July 2024

Background:
Clinically relevant fatigue in rheumatoid arthritis (RA) patients significantly
affects their quality of life. Almost all studies have assessed fatigue in this population using
non-specific scales. The present multi-centric study aimed to assess the validity, reliability, and
clinical significance of the Arabic version of the Bristol Rheumatoid Arthritis Fatigue Multi-Dimensional
Questionnaire (BRAF-MDQ).

Methods:
The present cross-sectional multicentric study was conducted at Aswan, Mansoura, Port
Said, and Al-Azhar University Hospitals over a 6-month duration. The study included 311 patients
with RA diagnosed according to the 2010 criteria of the American College of Rheumatology. The
Arabic version of BRAF-MDQ was developed to assess fatigue in these patients. All patients were
subjected to careful history taking, thorough clinical assessment, and standard laboratory work-up.
The obtained Arabic BRAF-MDQ was tested for construct validity, internal consistency, testretest
reproducibility, and criterion validity. Construct validity was evaluated using factor analysis
with the Kaiser Meyer Olkin tool of sampling adequacy and Bartlett's sphericity test. Internal consistency
of subscales was assessed using Cronbach’s alpha. Test-retest reproducibility was assessed
after a 1-week interval using the intraclass correlation coefficient. Pearson’s correlation coefficient
was used to correlate numerical variables. Predictors of fatigue were identified using binary
logistic regression analysis.

Results:
The present study included 311 RA patients. Construct validity assessment showed a
high loading of questionnaire items within the proposed construct subscales with a KMO measure
of sphericity of 0.927 and Bartlett's test of sphericity p-value < 0.001. Internal consistency assessment
showed adequate Cronbach’s alpha of Arabic BRAF-MDQ subscales. Total Arabic BRAFMDQ
had excellent criterion validity, as indicated by the high correlations with MAFS (r=0.95, p
< 0.001) and SF-36 vitality subscale (r=-0.91, p < 0.001). Clinically significant fatigue was identified
in 214 patients (68.8%). Multivariate logistic regression analysis revealed age (OR (95% CI):
1.07 (1.02-1.12), p < 0.001), disease duration (OR (95% CI): 1.82 (1.43-2.33), p < 0.001),
DAS28CRP (OR (95% CI): 8.62 (4.63-16.02), p < 0.001), and mHAQ (OR (95% CI): 3.85
(1.07-13.9), p = 0 .039) as significant predictors of fatigue development in the studied patients.

Conclusion:
The Arabic version of the Bristol Rheumatoid Arthritis Fatigue Multi-Dimensional
Questionnaire is a valid, consistent, and reliable tool for the assessment of fatigue in Egyptian
rheumatoid arthritis patients. Clinically significant fatigue was identified in 214 patients (68.8%).
Further, risk factors for fatigue included older age, longer disease duration, and higher disease activity.