Suitable Matching Research Articles

Window Shopping Humans in the Dating Store: What User Bios Tell Us About Online Dating

This essay explores certain aspects related to the projection and objectification of the self on dating apps. I explain how romance and intimacy have become a part of a wider consumerist logic—governed by ease of access, multiplicity of choice, frivolous interactions and diminished attention span. In an algorithm-induced mechanism, where human options are quick-swiped like commodities, visual displays and textual descriptions invariably play a significant part in determining choice and getting matches on an anonymous platform. I focus more on the careful curation of the self-image through short descriptions called user bios and what these bios represent not just about the user, but also about a range of other aspects that are integral to app-mediated dating. I argue how several users portray themselves as desirable objects waiting to be consumed and see others as commodities on the shopping window. Using several bios, I reveal how self-objectification also takes the route of overt sexualisation of the self or disdain for that amongst other users. I also argue how self-information announces boredom, disenchantment and doubts about the app to find a suitable match. Finally, I explore the non-obligatory casual nature of this sort of human interaction, where users are entitled to ‘ghost’—disappear without an explanation—making human interactions uncertain.

Impact of Charge on Strange Compact Stars in Rastall Theory

Within the framework of Rastall theory, we investigate the impact of charge on the structural development of different types of spherically symmetric anisotropic stars. To do so, we present modified field equations based upon the Finch–Skea metric potentials expressed in terms of three parameters (A,B,C). These constants are determined using suitable matching conditions and observational data for compact objects which include Her X-1, SAX J 1808.4-3658, PSR J038-0842, LMC X-4 and SMC X-1. The equation of state offered by the MIT bag model for quark–gluon plasma is used to investigate the inner structure and other characteristics of these compact objects. For a fixed bag constant, B=60MeV/fm3, and two sets of the Rastall and charge parameters, ζ=0.255,0.259 and Q˜=0.2,0.7, respectively, we analyze the consistency of the matter variables in the model and other physical parameters such as energy conditions, stellar mass, compactness, and surface redshift. In addition, we assess the stability of the constructed model through two different approaches. It is found that the obtained model is physically viable and stable.

Significant Radiation Reduction Using Cloud-Based AI Imaging in Manually Matched Cohort of Complex Aneurysm Repair.

Cloud-based, surgical augmented intelligence (Cydar Medical, Cambridge, UK) can be used for surgical planning and intraoperative imaging guidance during complex endovascular aortic procedures. We aim to evaluate radiation exposure, operative safety metrics, and post-operative renal outcomes following implementation of Cydar imaging guidance using a manually matched cohort of aortic procedures. We retrospectively reviewed our prospectively maintained database of endovascular aortic cases. Patients repaired using Cydar imaging were matched to patients who underwent a similar procedure without using Cydar. Matching was performed manually on a 1:1 basis using anatomy, device configuration, number of branches/fenestrations, and adjunctive procedures including in-situ laser fenestration. Radiation, contrast use, and other operative metrics were compared. Pre- and post-operative maximum creatinine was compared to assess for acute kidney injury (AKI) based on RIFLE Criteria. 100 patients from 2012-2023 were identified: 50 cases (38 FEVAR, 2 TEVAR, 3 octopus-type TAAA repair, 7 EVAR) where Cydar imaging was used, with suitable matches to 50 non-Cydar cases. Baseline characteristics including BMI did not differ significantly between the two groups (27.8 ± 5.6 vs. 26.7 ± 6.1; P=0.31). Radiation dose was significantly lower in the Cydar group (2529 ± 2256 vs 3676 ± 2976 mGy; P<0.03 Figure 1), despite there being no difference in fluoroscopy time (51 ± 29.4 vs 58 ± 37.2 min; P = 0.37). Contrast volume (94 ± 37.4 vs 93 ± 43.9 mL; P = 0.73), estimated blood loss (169 ± 223 vs 193 ± 222 mL; P = 0.97), and procedure time (154 ± 78 vs 165 ± 89.1 min) did not differ significantly. Additionally, Cydar vs non-Cydar patients did not show a significant difference between pre- and post-creatinine changes (0.13 +/- 0.08 vs 0.05 +/- 0.07; P=0.34). Only one patient in the non-Cydar group met RIFLE criteria for AKI post-operatively. The use of cloud-based augmented intelligence imaging was associated with a significant reduction in radiation dose in a cohort of matched aortic procedures but did not appear to affect other parameters or renal function. Even with advanced imaging, surgeons should remain conscientious about radiation safety and administration of nephrotoxic contrast agents.

Identification of a suitable matching procedure in health services research: Insights into a study for stroke patients

Background STROKE OWL is a quasi-experimental study using claims data from statutory health insurances in Germany to calculate the effect of case managers for stroke. Since there is no recruited control group, a suitable procedure needed to be identified to make the intervention effect measurable. Hence, the objective of this paper is to present an approach for comparing matching procedures before final data analyses take place. Methods We followed a four-step approach to identify an appropriate procedure on a partial dataset. First, we conducted a systematic review for identifying potential confounders of the study’s outcome. Afterwards we checked whether a matching procedure was able to balance the dataset with respect to the outcome, under the assumption that all relevant covariates including the intervention variable were balanced. Within the two last steps we checked covariate balances and remaining group sizes. Three matching procedures – coarsened exact matching, optimal full matching and propensity score matching – were tested. Results The coarsened exact matching was able to balance variables perfectly but on average lost &gt;50% of the observations. Although optimal full and propensity score matching revealed some weaknesses concerning the variable balance, considerably more observations remained in the dataset. Based on the described approach and the external framework conditions of STROKE OWL the optimal full matching was chosen as matching procedure most suitable. Conclusion In summary, it was challenging to identify a suitable matching procedure for this study, since the detailed results of the different balance and group size checks varied.

Local Charge Regulation in Selenides via High‐Entropy Engineering to Boost Electromagnetic Wave Absorption

AbstractLocal charge modulation is an effective method to improve the polarization loss and electromagnetic (EM) absorption characteristics. However, the use of conventional means (doping, defects, heterojunction surfaces) remains singular and limited in achieving local charge modulation. Surprisingly, lattice distortions induced by high‐entropy engineering can intrinsically regulate local charge states and improve EM wave absorption performances. Herein, a series of selenides with enhanced configuration entropy are designed and prepared to improve polarization loss capacity. Due to the different radii of the mixed ions and the Jahn‐Teller distortion effect, the local charge of the selenides is effectively modulated by the presence of defects and strong lattice distortions inside the lattice. Uneven distribution of charge at defects and formation of boundaries promotes defect‐induced polarization and interface polarization, respectively. Compared to single NiSe2, high‐entropy (NiFeCuCoMn)Se2 with an entropy value of 1.53R has more severe lattice defects and suitable impedance matching properties, exhibiting good EM absorption properties both in the absorption intensity and respond frequency. Tailoring the local charge density via an entropy strategy paves a new way for the high‐performance EM absorption materials.

A capacitive tactile force sensor with mutual fringe effect and parallel plate design for robot assisted surgery

This paper presents a unique design of a single-axis tactile force sensor by a mutual parallel plate and fringing effect of an electric field that is generated between stationary patterned electrodes in the sensor. The proposed sensor can measure the normal and shear forces with high sensitivity and linear response. The capacitive tactile sensor is fabricated by low-cost rapid prototyping techniques using conductive ink for electrode printing that is printed on a polyethylene terephthalate sheet by an inkjet printer. Ecoflex 00-30 and silicone rubber RTV-528 are used as the dielectric medium and dome for force application. A finite element method analysis is performed for deciding the dimensions of the sensor's stationary electrodes. The force measurement ranges of the sensor for the normal and shear axis are 4 N and 2 N, respectively. The proposed tactile sensor shows a highly linear response, which makes it a suitable match for force feedback in robotic surgery.

Feasibility of the CO2-ESGR technique for providing carbon-negative shale gas: A life cycle assessment

To verify the possibility of producing negative-carbon shale gas by CO2-ESGR technology, a systematic approach based on life cycle assessment (LCA) method was developed to evaluate the net CO2 emission of CO2-ESGR covering its entire processes including CO2 capture, transportation, utilization and the consumption of the produced shale gas. As a case study, the CO2-ESGR in the Fuling shale reservoir was investigated using two CO2 injection methods, including huff & puff and continuous injection. Then, the net CO2 emission were analyzed using a Monte Carlo simulation with 10,000 randomly generated cases under two CO2 injection modes and four CO2 sources. The results indicated that both modes have the potential to produce negative carbon shale gas. However, for a system with the input of 1 ton CO2, the optimal net CO2 emission reduction for huff & puff CO2 injection mode is 0.21 tons, which is lower than the continuous mode with the net CO2 emission reduction of 0.70 tons under the same condition. Finally, the shale gas reservoirs of Chongqing in the case study shows great potential for the application of CO2-ESGR technique. The results verify that CO2-ESGR has significant potential for producing negative-carbon shale gas with the suitable source-sink matching.

Hierarchically porous N-doped dual-carbon coupled Co5.47N composite with tunable electromagnetic shielding and absorption properties

Electromagnetic interference (EMI) and pollution issues are becoming increasingly prominent. It is of great scientific significance and practical value to develop lightweight, efficient and tunable electromagnetic wave (EMW) attenuating materials. Herein, a three-dimensional (3D) hierarchical porous N-doped dual-carbon (glucose-derived carbon and reduced graphene oxide (rGO)) coupled Co5.47N (Co5.47N@HNCF) composite was reasonably designed and prepared via simple and low-cost methods, which exhibited excellent electromagnetic attenuation properties. By appropriately adjusting the filling amount of Co5.47N@HNCF, tunable EMI shielding and EMW absorption properties could be achieved. At high filling amount (40 wt%), the highly conductive Co5.47N@HNCF composite had excellent EMI shielding effectiveness (EMI SE) in X-band (8.2–12.4 GHz), with a maximum total electromagnetic shielding effectiveness (SET) of 81.6 dB (average EMI SE of 76.8 dB) and a thickness of 2 mm. Particularly, when the thickness is only 0.8 mm, the SET could reach 32 dB. While at low filling amount (15 wt%), Co5.47N@HNCF composite with suitable impedance matching showed remarkable EMW absorption performance, exhibiting high values of reflection loss (RL) of −45.86 dB in 2–18 GHz. The high-performance EMW attenuation in Co5.47N@HNCF could be ascribed to the construction of stable 3D conductive dual-carbon frameworks and Co5.47N nanoparticles with abundant N vacancies. The dielectric and magnetic components of the system acted synergistically, possessing abundant heterogeneous interfaces and defects, which could induce various loss modes such as multiple reflections/scattering, conductive loss, magnetic loss and polarization loss to synergistically dissipate EMW. Therefore, this study endeavors to give an effective strategy for the preparation of low-cost, lightweight, and highly efficient tunable EMW attenuation materials.

Deep Learning-Based Freight Recommendation System for Freight Brokerage Platform

Platform-based businesses in the logistics market are evolving under the influence of digital transformation. Transforming the freight market into an environment where various types of freight can be traded across multiple markets and locations. Freight brokerage platforms have revolutionized the trading relationship between freight owners and vehicle owners. However, this type of system has also introduced inefficiencies, such as unestablished contracts, leading to unnecessary costs and delays. To address this issue, a freight recommendation system can assist users in finding what they are looking for while aiming to reduce failed contracts. With current advances in deep learning, complex patterns based on users’ past behaviors and preferences can be learned, enabling more accurate and personalized recommendations. This study proposes a deep learning-based freight recommendation system to provide personalized services and reduce failed contracts on freight brokerage platforms. The system is built by creating a freight transaction dataset, classifying freight categories through natural language processing and text mining techniques, and incorporating externally derived data on transportation distances. The deep learning model is trained using Autoencoder, Word2Vec, and Graph Neural Networks (GNN), with recommendation logic implemented to suggest suitable freight matches for vehicle owners. This system is expected to increase the market efficiency of the freight logistics industry and is a key step toward improving the long-term profit structure.

The Characterization of Aquifer Parameters in Using Skimming Tubewells Through the Pumping Test Method: A Case Study of Tando Allahyar

Sindh is in the lower reaches of the Indus River; it is most vulnerable to a variety of upstream water development challenges. The aim of this research was to determine aquifer characteristics in the command area of Tando Allahyar-II distributary within the culmination of underground water potential. The hydraulic properties of the aquifer as well as the susceptibility of the formation to tedious extraction and saltwater upcoming were recognized. Three pumping tests were performed at head, middle, and tail reaches along the selected distributary. The drawdowns were measured at head reach (5.1667 h), at middle reach (6.0 h), and at tail reach (19.667 h) of the selected distributary by performing the pumping tests. Groundwater levels were lower at the tail reach compared to those at the head and middle reaches, likely due to a higher concentration of tubewells in the lower reach. The head and middle reaches showed higher groundwater levels, possibly due to constant head conditions promoting infiltration and recharge. The pumping test versus drawdown analysis revealed that the tubewells should be run with 7-h (on) and 4-h (off) operation. Further, the tubewells at all reaches (head, middle, and tail) should be closed for a minimum of 4 h between operations. This strategy would allow safe groundwater extraction, maintain water quality, and prevent water table depletion in the study area. The hydrodynamic and hydro-salinity behaviors were scrutinized in PWMIN 5.3 (version) by means of the MODFLOW mode. The results were estimated to compare the calibration and validation simulation outcomes using measured data. The model was successfully calibrated, and the root mean square (RMS) value of the head tubewell varied between 0.024 and 0.108, whereas it speckled between 0.0166 and 0.0349 for the middle tubewell and between 0.0659 and 0.0069 for the tail tubewell. The RMS values for hydrodynamic behavior for the head, middle, and tail reaches were less than 10%. These values represent a suitable match between the observed and simulated heads when a water table depletion of 1 to 2 m was observed due to extreme pumping. However, the average relative error values, for all validated procedures, were less than 10%.

Genomic characterization of clinically significant blood group variants in Aboriginal Australians.

Hematological disorders are often treated with blood transfusions. Many blood group antigens and variants are population-specific, and for patients with rare blood types, extensive donor screening is required to find suitable matches for transfusion. There is a scarcity of knowledge regarding blood group variants in Aboriginal Australian populations, despite a higher need for transfusion due to the higher prevalence of renal diseases and anemia. In this study, we applied next-generation sequencing and analysis to 245 samples obtained from Aboriginal Australians from South-East Queensland, to predict antigen phenotypes for 36 blood group systems. We report potential weak antigens in blood group systems RH, FY and JR that have potential clinical implications in transfusion and pregnancy settings. These include partial DIII type 4, weak D type 33, and Del RHD (IVS2-2delA). The rare Rh phenotypes D+ C+ E+ c- e+ and D+ C+ E+ c+ e- were also detected. The comprehensive analyses of blood group genetic variant profiles identified in this study will provide insight and an opportunity to improve Aboriginal health by aiding in the identification of appropriate blood products for population-specific transfusion needs.

Is informedness the key? An empirical analysis of VET dropouts in Germany

In 2022, one in four vocational education and training (VET) contracts resulted in premature termination—a potential sign of inefficiency in the training of urgently needed skilled professionals. This study focuses on the level of perceived informedness of trainees and its potential influence on dropout. This includes trainees’ perceived level of information about the characteristics and requirements of an occupation, which may result from various sources of information in the form of social contacts. We draw on theories from the field of career choice and job search to argue that a better level of informedness can reduce uncertainty and enable individuals to make better-informed decisions about their careers. With better informedness, there is a higher probability of finding a suitable match between a trainee and their chosen occupation, ultimately increasing their likelihood of job persistence. This should also lead to a lower probability of dropout among VETs. Using data from the National Educational Panel Study, starting cohort 4, we employed event history analysis. We show that good perceived informedness on the requirements of one’s vocational training and the perception of good school-based vocational preparation reduce the probability of dropping out. In contrast, good informedness about alternative training programs increases dropout risk. We also see that the distinction between closer or more distant groups of people from the social network (strong or weak ties) who provide information about training is not decisive.

Multi-line laser 3D reconstruction method based on spatial quadric surface and geometric estimation

The traditional multi-line laser 3D reconstruction is based on binocular epipolar constraints and the equation of the laser optical plane. Firstly, matching points are identified based on the epipolar constraints. Then, the correct matching points are selected based on the optical plane equation of the multi-line laser. Finally, 3D reconstruction is performed using the selected matching points. In actual production processes involving multi-line lasers, noticeable distortion occurs due to the projection of Diffractive Optical Elements (DOE) at a large angle. This results in curved laser light planes and curved reflections on the measured objects. Under such circumstances, efficiently screening matching points using the traditional method based on the laser plane equation becomes challenging. Additionally, inherent noise in multi-line laser systems introduces errors in extracted laser center coordinates, making it impossible to directly obtain high-precision 3D data. To address these issues, this paper proposes a method that utilizes spatial quadric surfaces and geometric estimation for completing multi-line laser 3D reconstructions. By analyzing the distortion principle of DOE and the positional relationship after optical diffraction, the multi-line laser manifests as a quadric surface on the optical output plane. Consequently, by calibrating the equations of the quadric surface and applying binocular polar constraints, suitable matching points for the multi-line laser can be chosen. Once an accurate matching point is identified, a minimum geometric distance estimation can be established based on the distance constraint between the point and its corresponding epipolar line. This distance represents the separation between the left and right camera’s laser center points and their respective epipolar lines. Utilizing this estimate of the minimum geometric distance, a refined calculation can be performed to better satisfy epipolar constraints and obtain new matching points. Ultimately, utilizing these new matching points enables the completion of 3D reconstruction for multi-line lasers. In comparison with methods relying on spatial plane and epipolar constraints, our algorithm exhibits a superior degree of matchability and accuracy.According to multiple groups of test data, the average error before optimization is 0.3126 mm, and can be increased to 0.0336 mm after optimization.

Exploring Trade-Offs for Online Mental Health Matching: Agent-Based Modeling Study.

Online mental health communities (OMHCs) are an effective and accessible channel to give and receive social support for individuals with mental and emotional issues. However, a key challenge on these platforms is finding suitable partners to interact with given that mechanisms to match users are currently underdeveloped or highly naive. In this study, we collaborated with one of the world's largest OMHCs; our contribution is to show the application of agent-based modeling for the design of online community matching algorithms. We developed an agent-based simulation framework and showcased how it can uncover trade-offs in different matching algorithms between people seeking support and volunteer counselors. We used a comprehensive data set spanning January 2020 to April 2022 to create a simulation framework based on agent-based modeling that replicates the current matching mechanisms of our research site. After validating the accuracy of this simulated replication, we used this simulation framework as a "sandbox" to test different matching algorithms based on the deferred acceptance algorithm. We compared trade-offs among these different matching algorithms based on various metrics of interest, such as chat ratings and matching success rates. Our study suggests that various tensions emerge through different algorithmic choices for these communities. For example, our simulation uncovered that increased waiting time for support seekers was an inherent consequence on these sites when intelligent matching was used to find more suitable matches. Our simulation also verified some intuitive effects, such as that the greatest number of support seeker-counselor matches occurred using a "first come, first served" protocol, whereas relatively fewer matches occurred using a "last come, first served" protocol. We also discuss practical findings regarding matching for vulnerable versus overall populations. Results by demographic group revealed disparities-underaged and gender minority groups had lower average chat ratings and higher blocking rates on the site when compared to their majority counterparts, indicating the potential benefits of algorithmically matching them. We found that some protocols, such as a "filter"-based approach that matched vulnerable support seekers only with a counselor of their same demographic, led to improvements for these groups but resulted in lower satisfaction (-12%) among the overall population. However, this trade-off between minority and majority groups was not observed when using "topic" as a matching criterion. Topic-based matching actually outperformed the filter-based protocol among underaged people and led to significant improvements over the status quo among all minority and majority groups-specifically, a 6% average chat rating improvement and a decrease in blocking incidents from 5.86% to 4.26%. Agent-based modeling can reveal significant design considerations in the OMHC context, including trade-offs in various outcome metrics and the potential benefits of algorithmic matching for marginalized communities.

Design and investigation of electrostatic doped heterostructure vertical Si(1-x)Gex/Si nanotube TFET

Researchers are inclining toward heterostructures suitable lattice matching, in Tunnel FETs to eliminate the difficulties of decreased On-Current, subthreshold swings, and ambipolar behavior. Nowadays, Electrostatic doping (ED) is a scrutinized substitute device for creating areas with a high electron or hole density to the conventional doped devices. This manuscript proposes an Electrostatic Doped Heterostructure Vertical Si(1-x)Gex/Si Nanotube Tunnel Field Effect with performance scanned by analyzing the different device parameters, considering the energy band diagram, concentrations of electrons, holes, potential, and electric field. In comparison to the Nanowire TFETs, the area, and rate of tunneling of the proposed device stand superior with a better ION/IOFF ratio of 1.56∗1013 and a lower OFF-current of about ∼10−18A/μm. The device exhibits a Drain current (IDS) of 2.39∗105A/μm. The architecture of the suggested device possessing Si(1-x)Gex/Si structure exhibits enhanced characteristics like improved steepness of the sub-threshold slope, ION/IOFF ratio, drain current, and lowered OFF-current.

Subjective and objective assessment of color match of universal tinted sunscreens in Fitzpatrick skin phototypes I-VI.

Tinted sunscreens not only shield against UV rays but also provide protection against visible light, as opposed to traditional sunscreens. Universal tinted sunscreens are marketed to complement all skin tones. To assess color match and subject satisfaction for 7 universal tinted sunscreens across various price ranges in all Fitzpatrick skin phototypes (SPT). Products A-G were applied at concentrations of 1 and 2 mg/cm2 on the dorsal arms of 30 subjects spanning SPT I-VI. Photography, colorimetry, and subject and investigator surveys were utilized to determine color match. Using colorimetry analysis at the recommended 2 mg/cm2 concentration, two of seven products were identified as suitable matches for SPT I-II, while six out of seven were determined to be a good match for SPT III-IV. However, only one product was found to be a good match for SPT V-VI at the recommended concentration according to colorimetry results. Universal tinted sunscreens do not provide an adequate color match for all skin phototypes, especially for individuals with very fair or very dark skin tones.

In-situ chemically synthesized Fe3O4/K-geopolymer composite with microwave absorbency for additive manufacturing

In this work, we utilized an in-situ chemical synthesis method to fabricate a Fe3O4/K-geopolymer (KGP) composite to be applied in a microwave absorbent field. This material, as a type of ceramic precursor, is highly expected to be a 3D printing material to prepare microwave absorbing components with complex shapes. The investigation results demonstrate that the material possesses a large effective microwave absorbing bandwidth of 3.7 GHz with the minimum reflection loss reducing to −12.2 dB when the generated Fe3O4 percent reaches 12 wt% in the KGP composite. This microwave absorbent performance can be attributed to a synergistic effect between the eddy current loss caused by the improved electrical conductivity of magnetic nanoparticles and the interfacial polarization effect from the geopolymer matrix and magnetic medium interface. Also, we used direct ink writing technology to print two-dimensional components with desirable patterns. Thickness-dependent wave absorption evaluation results confirmed a maximum reflection loss of −25.9 dB at 15.2 Hz was obtained from the printed sample containing 9.0 wt% Fe3O4 for a layer thickness of 10 mm, indicating that wave consumption effectiveness was determined by porous microstructures, magnetic loss of Fe3O4 nanoparticles as well as suitable impedance matching. The preparation method and synthesized material pave the way for integrated manufacturing of 3D printing components with microwave absorbing performance.

Reversible Electrochemical Swelling of Straight Carbon Nanotube Yarns for High-Performance Linear Actuation.

Coiled artificial muscle yarns outperform their straight counterparts in contractile strokes. However, challenges persist in the fabrication complexity and the susceptibility of the coiled yarns to becoming stuck by surrounding objects during contraction and recovery. Additionally, torsional stability remains a concern. In this study, it is reported that straight carbon nanotube (CNT) yarns when driven by a low-voltage electrochemical approach, can achieve a contractile stroke that surpasses even NiTi shape memory alloy fibers. The key lies in the suitable match between a yarn consisting of randomly aligned CNTs and the reversible and substantial electrochemical swelling induced by solvated ions. Wrinkled structures are formed on the surface of the CNT yarn to adapt to the swelling process. This not only assures torsional stability but also enhances the surface area for improved electrode-electrolyte interaction during electrochemical actuation. Remarkably, the CNT artificial muscle yarn generates a contractile stroke of 8.8% and an isometric stress of 7.5 MPa under 2.5 V actuation voltages, demonstrating its potential for applications requiring low energy consumption while maintaining high operational efficiency. This study highlights the crucial impact of CNT orientation on the effectiveness of electrochemically-driven artificial muscles, signaling new possibilities in smart material and biomechanical system development.

Mate Choice Plurality, Choice Overload, and Singlehood: Are More Options Always Better?

A lack of options can make it challenging for individuals to find a desirable intimate partner. Conversely, an abundance of choices might lead to mate choice overload, making it difficult to determine the most suitable match. Additionally, having numerous alternatives after entering a relationship could undermine its stability by decreasing satisfaction with the current partner. The present research aimed to examine the effects of mate choice plurality on singlehood status and the willingness to stay in a relationship within the Greek cultural context. Specifically, we employed closed-ended questionnaires, which included instruments developed using AI, with a sample of 804 Greek-speaking participants. We found that participants who perceived they had a wider range of potential romantic partners reported a lower likelihood of being single. Furthermore, more perceived mate choices were associated with fewer years spent as single. However, mate choice plurality was also linked to higher choice overload, which, in turn, increased the likelihood of being single rather than in an intimate relationship. Moreover, more perceived mate choices were associated with more regrets about being in the current relationship. These regrets were linked to lower relationship satisfaction and ultimately contributed to a decreased willingness to stay in the relationship. Notably, this indirect effect was significant only for male participants.

Mapping vaccine names in clinical trials to vaccine ontology using cascaded fine-tuned domain-specific language models

BackgroundVaccines have revolutionized public health by providing protection against infectious diseases. They stimulate the immune system and generate memory cells to defend against targeted diseases. Clinical trials evaluate vaccine performance, including dosage, administration routes, and potential side effects. ClinicalTrials.gov is a valuable repository of clinical trial information, but the vaccine data in them lacks standardization, leading to challenges in automatic concept mapping, vaccine-related knowledge development, evidence-based decision-making, and vaccine surveillance.ResultsIn this study, we developed a cascaded framework that capitalized on multiple domain knowledge sources, including clinical trials, the Unified Medical Language System (UMLS), and the Vaccine Ontology (VO), to enhance the performance of domain-specific language models for automated mapping of VO from clinical trials. The Vaccine Ontology (VO) is a community-based ontology that was developed to promote vaccine data standardization, integration, and computer-assisted reasoning. Our methodology involved extracting and annotating data from various sources. We then performed pre-training on the PubMedBERT model, leading to the development of CTPubMedBERT. Subsequently, we enhanced CTPubMedBERT by incorporating SAPBERT, which was pretrained using the UMLS, resulting in CTPubMedBERT + SAPBERT. Further refinement was accomplished through fine-tuning using the Vaccine Ontology corpus and vaccine data from clinical trials, yielding the CTPubMedBERT + SAPBERT + VO model. Finally, we utilized a collection of pre-trained models, along with the weighted rule-based ensemble approach, to normalize the vaccine corpus and improve the accuracy of the process. The ranking process in concept normalization involves prioritizing and ordering potential concepts to identify the most suitable match for a given context. We conducted a ranking of the Top 10 concepts, and our experimental results demonstrate that our proposed cascaded framework consistently outperformed existing effective baselines on vaccine mapping, achieving 71.8% on top 1 candidate’s accuracy and 90.0% on top 10 candidate’s accuracy.ConclusionThis study provides a detailed insight into a cascaded framework of fine-tuned domain-specific language models improving mapping of VO from clinical trials. By effectively leveraging domain-specific information and applying weighted rule-based ensembles of different pre-trained BERT models, our framework can significantly enhance the mapping of VO from clinical trials.