bluuebunny/crossref_metadata_2025_split huggingface dataset:
Implementation of a Data-Driven Approach to Internship Recruitment
Authors: Efron Lisa A. , Mackey Eleanor R. 
Published: May 2023

Objective: Recruitment for Psychology Clinical Internship is a complex and labor-intensive process. The objective of this study is to describe a data-driven procedure to maximize objectivity and optimize outcome for internship recruitment. Method: The Psychology Training Committee designed an objective rating system for online applications and interviews, incorporating both objective and subjective data. Perceptions of efficiency and effectiveness with this approach were assessed via a survey distributed to the approximately 50 faculty members who have participated in the internship recruitment process. Intern perceptions following completion of the program were also assessed. Results: This recruitment procedure is highly efficient, as the streamlined process of reviewing applications, developing a list of candidates to interview, and generating final rankings of candidates interviewed occurs quickly, with limited burden to training faculty. The system has demonstrated effectiveness, as there have been no unfilled internship slots and all matched applicants have been within the top half of the rank list generated annually. All interns during this period of time have successfully completed the program, and data suggest that the training interns have received has met (or exceeded) their expectations. Survey data from training faculty echo these findings. Conclusions: This data-driven approach to internship recruitment has been easy to implement. This approach provides a highly effective and flexible system for ranking a diverse and qualified group of applicants and has the potential to be utilized by other training programs within psychology, as well as across a wide range of disciplines within the medical field. Implications for Impact Statement This study describes a data-driven procedure developed to maximize objectivity and optimize outcome for internship recruitment. The approach reviewed has demonstrated efficiency and effectiveness for recruiting a diverse and qualified group of applicants. It has the potential to be utilized by other training programs within psychology and medicine more generally.
Cilia-associated wound repair mediated by IFT88 in retinal pigment epithelium
Authors: Ning Ke , Bhuckory Mohajeet B. , Lo Chien-Hui , Sendayen Brent E. , Kowal Tia J. , Chen Ming , Bansal Ruchi , Chang Kun-Che , Vollrath Douglas , Berbari Nicolas F. , Mahajan Vinit B. , Hu Yang , Sun Yang 
Published: May 2023

AbstractPrimary cilia are conserved organelles that integrate extracellular cues into intracellular signals and are critical for diverse processes, including cellular development and repair responses. Deficits in ciliary function cause multisystemic human diseases known as ciliopathies. In the eye, atrophy of the retinal pigment epithelium (RPE) is a common feature of many ciliopathies. However, the roles of RPE cilia in vivo remain poorly understood. In this study, we first found that mouse RPE cells only transiently form primary cilia. We then examined the RPE in the mouse model of Bardet-Biedl Syndrome 4 (BBS4), a ciliopathy associated with retinal degeneration in humans, and found that ciliation in BBS4 mutant RPE cells is disrupted early during development. Next, using a laser-induced injury model in vivo, we found that primary cilia in RPE reassemble in response to laser injury during RPE wound healing and then rapidly disassemble after the repair is completed. Finally, we demonstrated that RPE-specific depletion of primary cilia in a conditional mouse model of cilia loss promoted wound healing and enhanced cell proliferation. In summary, our data suggest that RPE cilia contribute to both retinal development and repair and provide insights into potential therapeutic targets for more common RPE degenerative diseases.
Residual deformation of coal gangue subgrade filler under multi-vibration cyclic loading
Authors: Tang Xiaoyu , Wan Wen , Zhang Zongtang , Gao Wenhua , Wang Yanhao 
Published: May 2023

AbstractIn this paper, the development law of residual deformation of coal gangue subgrade filler is analyzed through large scale triaxial test, and the residual deformation model of coal gangue mainly sandstone and limestone is established. The purpose is to provide research basis for the applicability of coal gangue as subgrade filler. The results show that the deformation of coal gangue filler increases first and then tends to be constant under cyclic load of multiple vibration times. It is found that the Shenzhujiang residual deformation model cannot accurately predict the deformation law, and the corresponding modification is made to the residual deformation model of coal gangue filling body. Finally, according to the calculation of grey correlation degree, the influence degree of main factors of coal gangue filler on its residual deformation is sorted. Combined with the actual engineering situation represented by these main factors, it can be analyzed that the effect of packing particle density on residual deformation is greater than that of packing particle size composition.
Application of artificial intelligence in green building concept for energy auditing using drone technology under different environmental conditions
Authors: Khan Osama , Parvez Mohd , Alansari Monairah , Farid Mohammad , Devarajan Yuvarajan , Thanappan Subash 
Published: May 2023

AbstractThermal losses through weak building envelope is responsible for global current energy crises. Application of artificial intelligence and drone setups in green buildings can help in providing the sustainable solution the world is striving for years. The contemporary research incorporates a novel concept of measuring the wearing thermal resistances in the building envelope with the aid of a drone system. The above procedure conducts a throughout building analysis by considering three prime environmental parameters such as wind speed (WS), relative humidity (RH) and dry bulb temperature (DBT) with the aid of drone heat mapping procedure. The novelty of the study can be interpreted by the fact that prior researches have never explored the building envelope through a combination of drone and climatic conditions as variables in building areas difficult to access, thereby providing an easier, risk free, cost effective and efficient reading. Validation of the formula is authenticated by employing artificial intelligence-based software’s which are applied for data prediction and optimization. Artificial models are established to validate the variables for each output from the specified number of climatic inputs. The pareto-optimal conditions attained after analysis are 44.90% RH, 12.61 °C DBT and 5.20 km/h WS. The variables and thermal resistance were validated with response surface methodology method, thereby presenting lowest error rate and comprehensive R2 value, which are 0.547 and 0.97, respectively. Henceforth, employing drone-based technology in estimating building envelope discrepancies with the novel formula, yields consistent and effective assessment for development of green building, simultaneously reducing time and cost of the experimentation.
Testing the speed of “spooky action at a distance” in a tabletop experiment
Authors: Santamaria Amato Luigi , Pallotti Deborah Katia , Siciliani de Cumis Mario , Dequal Daniele , Andrisani Andrea , Slussarenko Sergei 
Published: May 2023

AbstractNonlocality, probably the principal friction between Quantum Physics and Relativity, disturbed the physicists even more than realism since it looks to originate superluminal signalling, the Einsteinian “Spooky action at a distance”. From 2000 on, several tests to set lower bounds of the Spooky action at a distance velocity ($$c \beta _{t,max}$$

c

β

t
,
m
a
x

) have been performed. They are usually based on a Bell Test performed in km long and carefully balanced experimental setups to fix a more and more improved bound making some assumptions dictated by the experimental conditions. By exploiting advances in quantum technologies, we performed a Bell’s test with an improved bound in a tabletop experiment of the order of few minutes, thus being able to control parameters otherwise uncontrollable in an extended setup or in long lasting experiments.
Hybrid nanofluid flow within cooling tube of photovoltaic-thermoelectric solar unit
Authors: Khalili Z. , Sheikholeslami M. , Momayez Ladan 
Published: May 2023

AbstractIn this work, the thermoelectric generator (TEG) layer has been combined with conventional layers of photovoltaic-thermal (PVT) modules to use the waste heat and increase the efficiency. To reduce the cell temperature, there exists a cooling duct in the bottom of the PVT-TEG unit. Type of fluid within the duct and structure of duct can change the performance of the system. So, hybrid nanofluid (mixture of Fe3O4 and MWCNT with water) has been replaced instead of pure water and three various configurations of cross section [STR1 (circular), STR2 (rhombus), STR3 (elliptic)] have been implemented. Through the tube incompressible laminar flow of hybrid nanofluid has been solved while in solid layers of panel, pure conduction equation has been simulated involving heat sources resulting from optical analysis. According to simulations, the third structure (elliptic) has the best performance and rise of inlet velocity causes overall performance to enhance about 6.29%. The values of thermal and electrical performances for elliptic design with equal fractions of nanoparticles are 14.56% and 55.42%, respectively. With the best design, electrical efficiency improves about 16.2% in comparison with an uncooled system.
Comparative transcriptome analysis of Veratrum maackii and Veratrum nigrum reveals multiple candidate genes involved in steroidal alkaloid biosynthesis
Authors: Wang Dan , Yu Zhijing , Guan Meng , Cai Qinan , Wei Jia , Ma Pengda , Xue Zheyong , Ma Rui , Oksman-Caldentey Kirsi-Marja , Rischer Heiko 
Published: May 2023

AbstractVeratrum (Melanthiaceae; Liliales) is a genus of perennial herbs known for the production of unique bioactive steroidal alkaloids. However, the biosynthesis of these compounds is incompletely understood because many of the downstream enzymatic steps have yet to be resolved. RNA-Seq is a powerful method that can be used to identify candidate genes involved in metabolic pathways by comparing the transcriptomes of metabolically active tissues to controls lacking the pathway of interest. The root and leaf transcriptomes of wild Veratrum maackii and Veratrum nigrum plants were sequenced and 437,820 clean reads were assembled into 203,912 unigenes, 47.67% of which were annotated. We identified 235 differentially expressed unigenes potentially involved in the synthesis of steroidal alkaloids. Twenty unigenes, including new candidate cytochrome P450 monooxygenases and transcription factors, were selected for validation by quantitative real-time PCR. Most candidate genes were expressed at higher levels in roots than leaves but showed a consistent profile across both species. Among the 20 unigenes putatively involved in the synthesis of steroidal alkaloids, 14 were already known. We identified three new CYP450 candidates (CYP76A2, CYP76B6 and CYP76AH1) and three new transcription factor candidates (ERF1A, bHLH13 and bHLH66). We propose that ERF1A, CYP90G1-1 and CYP76AH1 are specifically involved in the key steps of steroidal alkaloid biosynthesis in V. maackii roots. Our data represent the first cross-species analysis of steroidal alkaloid biosynthesis in the genus Veratrum and indicate that the metabolic properties of V. maackii and V. nigrum are broadly conserved despite their distinct alkaloid profiles.
Application of neural networks and neuro-fuzzy models in construction scheduling
Authors: Obianyo Jude Iloabuchi , Udeala Richard Chinenye , Alaneme George Uwadiegwu 
Published: May 2023

AbstractConstruction scheduling is a complex process that involves a large number of variables, making it difficult to develop accurate and efficient schedules. Traditional scheduling techniques rely on manual analysis and intuition, which are prone to errors and often fail to account for all the variables involved. This results in project delays, cost overruns, and poor project performance. Artificial intelligence models have shown promise in improving construction scheduling accuracy by incorporating historical data, site-specific conditions, and other variables that traditional scheduling methods may not consider. In this research study, application of soft-computing techniques to evaluate construction schedule and control of project activities in order to achieve optimal performance in execution of building projects were carried out. Artificial neural network and neuro-fuzzy models were developed using data extracted from a residential two-storey reinforced concrete framed-structure construction schedule and project execution documents. The evaluation of project performance indicators in earned value analysis from 0 to 100% progress at 5% increment with a total of seventeen tasks were carried out using Microsoft Project software and data obtained from the computation were utilized for model development. Using input–output and curve-fitting (nftool) function in MATLAB, a 6-10-1 two-layer feed-forward network with tansig activation-function (AF) for the hidden neurons and linear AF output neurons was generated with Levenberg–Marquardt (Trainlm) training algorithm. Similarly, with the aid of ANFIS toolbox in MATLAB software, the training, testing and validation of the ANFIS model were carried out using hybrid optimization learning algorithm at 100 epochs and the Gaussian-membership-function (gaussmf). Loss-function parameters namely MAE, RMSE and R-values were taken as the performance evaluation criteria of the developed models. The generated statistical results indicates no significant difference between model-results and experimental values with MAE, RMSE, R2of 1.9815, 2.256 and 99.9% respectively for ANFIS-model and MAE, RMSE, R2of 2.146, 2.4095 and 99.998% respectively for the ANN-model. The model performance indicated that the ANFIS-model outclassed the ANN-model with their results satisfactory to deal with complex relationships between the model variables to produce accurate target response. The findings from this research study will improve the accuracy of construction scheduling, resulting in improved project performance and reduced costs.
Optimization of seismic performance in waste fibre reinforced concrete by TOPSIS method
Authors: Ali Husnain , Jamshaid Hafsa , Mishra Rajesh , Chandan Vijay , Jirku Petr , Kolar Viktor , Muller Miroslav , Nazari Shabnam , Shahzada Khan 
Published: May 2023

AbstractFor a sustainable environment and to tackle the pollution problem, industrial wastes can be used in concrete composite materials. This is especially beneficial in places prone to earth quack and lower temperature. In this study, five different types of waste fibres such as polyester waste, rubber waste, rock wool waste, glass fibre waste and coconut fibre waste were used as an additive in 0.5% 1%, and 1.5% by mass in concrete mix. Seismic performance related properties of the samples were examined through evaluation of compressive strength, flexural strength, impact strength, split tensile strength, and thermal conductivity. Results showed that, impact strength of the concrete significantly improved by the addition of fibre reinforcement in concrete. Split tensile strength and flexural strength were significantly reduced. Thermal conductivity was also influenced by addition of polymeric fibrous waste. Microscopic analysis was performed to examine the fractured surfaces. In order to get the optimum mix ratio, multi response optimization technique was used to determine the desired level of impact strength at an acceptable level of other properties. Rubber waste was found to be the most attractive option followed by coconut fibre waste for the seismic application of concrete. The significance and percentage contribution of each factor was obtained by Analysis of variance ANOVA (α = 0.05) and pie chart which showed that Factor A (waste fibre type) is the main contributor. Confirmatory test was done on optimized waste material and their percentage. The order preference similarity to ideal solution (TOPSIS) technique was used for developed samples to obtain solution (sample) which is closest to ideal as per given weightage and preference for the decision making. The confirmatory test gives satisfactory results with error of 6.68%. Cost of reference sample and waste rubber reinforced concrete sample was estimated, which showed that 8% higher volume was achieved with waste fibre reinforced concrete at approximately same cost as pure concrete. Concrete reinforced with recycled fibre content is potentially beneficial in terms of minimizing resource depletion and waste. The addition of polymeric fibre waste in concrete composite not only improves seismic performance related properties but also reduces the environmental pollution from waste material which has no other end use.
Passenger‐perception dynamic ridesharing service based on parallel technology
Authors: Xue Shouqiang , Song Rui , He Shiwei , Li Guangye , Chi Jushang 
Published: May 2023

AbstractWith the emergence of new information and communication technology, mobile‐based ridesharing services have received more attention and have improved. They offer timely and convenient service and exert an enormous influence on pollution and congestion by allowing passengers to share overlapping routes. However, ridesharing services have also been discussed and called into question by people with respect to their attractiveness, their comfort, and passenger safety. This paper proposes a ridesharing algorithm with a perceived mechanism by introducing multiple dimensions of perceived value to overall assess passengers’ perceptions. The approach involved can continuously track the psychological changes in passengers during travel, capture the dynamic and comprehensive perceptions of passengers, and make real‐time adjustments on this basis. Furthermore, the proposed partition‐based parallel strategy can ensure high‐quality services and further enhance computational efficiency. Finally, numerical experiments are conducted based on the urban transportation network and the actual trip data from Manhattan to evaluate the performance of the proposed algorithm. The results show that it is important to effectively capture the passengers’ perception of ridesharing services and apply them to optimization mechanisms, which will contribute to improving the perception of ride experiences and attracting potential passengers.
Pregnant Patients with a Documented History of Penicillin Allergy and Associated Maternal and Neonatal Outcomes at a Tertiary Care Center
Authors: Azmy Veronica , Lundsberg Lisbet S. , Culhane Jennifer , Kwah Jason , Partridge Caitlin , Son Moeun 
Published: May 2023

Objective Pregnant individuals are likely to need antibiotics during the peripartum period. For pregnant individuals who report a history of penicillin allergy, non-β-lactam antibiotics are often administered. Compared with first-line β-lactam antibiotics, alternative antibiotics can be less effective, more toxic, and more costly. It remains unclear if being labeled with a penicillin allergy is associated with adverse maternal and neonatal outcomes.
Study Design We conducted a retrospective cohort study of all pregnant patients who delivered a viable singleton between 24 and 42 weeks of gestation at a large academic hospital from 2013 to 2021. We compared patients who had a documented penicillin allergy history in their electronic medical record versus those who did not and examined whether there were significant differences in maternal outcomes and neonatal outcomes. Bivariable and multivariable analyses were performed.
Results Of 41,943 eligible deliveries included in the analysis, 4,705 (11.2%) patients had a penicillin allergy history documented in their electronic medical record and 37,238 (88.8%) did not. Even after adjusting for potential confounders, patients with a documented penicillin allergy had a higher risk of postpartum endometritis (adjusted odds ratio [aOR]: 1.46; 95% confidence interval [CI]: 1.01–2.11) and a higher risk of their neonates having a postnatal hospital stay lasting more than 72 hours (aOR: 1.10; 95% CI: 1.02–1.18). There were no significant differences seen in the other maternal and neonatal outcomes in both bivariable and multivariable analyses.
Conclusion Pregnant patients who are labeled as having a penicillin allergy are more likely to have postpartum endometritis, and neonates born to mothers who are labeled as having a penicillin allergy are more likely to have a postnatal hospital stay lasting more than 72 hours. There were no other significant differences seen in pregnant patients and their newborns whether they were labeled as having a penicillin allergy history or not. However, pregnant individuals with a penicillin allergy documented in their medical record were significantly more likely to receive alternative non-β lactam antibiotics, and may have benefitted from having more details of their allergy history available as well as proper allergy verification with testing.
Key Points
Risk Factors for Early- and Late-Onset Superimposed Preeclampsia
Authors: Onishi Kazuma , Seagraves Elizabeth , Baraki Dana , Donaldson Thomas , Barake Carole , Abuhamad Alfred , Huang Jim C. , Kawakita Tetsuya 
Published: May 2023

Objective Risk factors of early- and late-onset preeclampsia among pregnant individuals with chronic hypertension are not well described in the literature. We hypothesized that early- and late-onset superimposed preeclampsia (SIPE) have different risk factors. Therefore, we aimed to examine the risk factors of early- and late-onset SIPE among individuals with chronic hypertension.
Study Design This was a retrospective case-control study of pregnant individuals with chronic hypertension who delivered at 22 weeks' gestation or greater at an academic institution. Early-onset SIPE was defined as SIPE diagnosed before 34 weeks' gestation. To identify risk factors, we compared individuals' characteristics between individuals who developed early- and late-onset SIPE and those who did not. We then compared characteristics between individuals who developed early-onset SIPE and late-onset SIPE. Characteristics with p-values of less than 0.05 by bivariable variables were analyzed by simple and multivariable logistic regression models to calculate crude and adjusted odds ratios (aOR) and 95% confidence intervals (95% CI). Missing values were imputed with multiple imputation.
Results Of 839 individuals, 156 (18.6%) had early-onset, 154 (18.4%) had late-onset SIPE and 529 (63.1%) did not have SIPE. The multivariate logistic regression model showed that serum creatinine ≥ 0.7 mg/dL compared to less than 0.7 mg/dL (aOR: 2.89 [95% CI: 1.63–5.13]), increase of creatinine (1.33 [1.16–1.53]), nulliparity compared to multiparity (1.77 [1.21–2.60]), and pregestational diabetes (1.70 [1.11–2.62]) were risk factors for early-onset SIPE. The multivariate logistic regression model showed that nulliparity compared to multiparity (1.53 [1.05–2.22]) and pregestational diabetes (1.74 [1.14–2.64]) was a risk factor for late-onset SIPE. Serum creatinine ≥ 0.7 mg/dL (2.90 [1.36–6.15]) and increase of creatinine (1.33 [1.10–1.60]) were significantly associated with early-onset SIPE compared to late-onset SIPE.
Conclusion Kidney dysfunction seemed to be associated with the pathophysiology of early-onset SIPE. Nulliparity and pregestational diabetes were common risk factors for both early- and late-onset SIPE.
Key Points