bluuebunny/crossref_metadata_2025 huggingface dataset:
Modeling Sorption of Water and Vanadium Cations by Ion-Exchange Membranes
Authors: Darling Robert M. , Saraidaridis James D. , Shovlin Christopher , Fortin Michael
Published: May 2024

We develop a macroscopic model for sorption of ions and solvent by ion-exchange membranes and use it to investigate how different membranes behave when exposed to electrolytes for vanadium flow batteries. The model combines a classical expression for the Gibbs free energy of a moderately concentrated electrolyte containing several ions with a term that describes elastic swelling of a polymer membrane. Parameters describing pairwise interactions between mobile ions and fixed membrane ions were fit to published experimental data and discussed in the context of the competition for sites in ion-exchange membranes. The model provides insights into why sorption of vanadium cations by Nafion is lower than predicted by Donnan theory and why switching to an anion-exchange membrane does not dramatically reduce vanadium sorption.
FIGURE 7 from Humanized Patient-derived Xenograft Models of Disseminated Ovarian Cancer Recapitulate Key Aspects of the Tumor Immune Environment within the Peritoneal Cavity
Authors: Steinkamp Mara P. , Lagutina Irina , Brayer Kathryn J. , Schultz Fred , Burke Danielle , Pankratz Vernon S. , Adams Sarah F. , Hudson Laurie G. , Ness Scott A. , Wandinger-Ness Angela
Published: May 2024

Survival time is reduced in huNBSGW PDX models. A, huNBSGW PDX3, 9, and 18 were engrafted with the same pooled donor CD34+ cells. Survival time was PDX dependent with PDX3 and 9 having a shorter survival time compared with PDX18. Survival curves are significantly different between huPDX and non-huPDX for all three PDX models (P < 0.025, log-rank test). For all PDX models, n = 3 mice/group for huPDX and non-huPDX. B, Solid tumor mass (in grams) of huPDX and non-huPDX at necropsy. Bars are the average tumor burden, error bars are SEM. Measures for individual mice are shown as black dots (n = 2–3 per group). C, Ascites fluid volume at necropsy. The ascites fluid volume trended higher in non-huPDX for PDX3 and PDX9, but was only significantly different for PDX9. Statistical analysis for B and C used unpaired t tests to compare huPDX versus non-huPDX values for each PDX line.
FIGURE 1 from Humanized Patient-derived Xenograft Models of Disseminated Ovarian Cancer Recapitulate Key Aspects of the Tumor Immune Environment within the Peritoneal Cavity
Authors: Steinkamp Mara P. , Lagutina Irina , Brayer Kathryn J. , Schultz Fred , Burke Danielle , Pankratz Vernon S. , Adams Sarah F. , Hudson Laurie G. , Ness Scott A. , Wandinger-Ness Angela
Published: May 2024

Analysis of RNA-seq data comparing ovarian cancer patient samples to non-huPDX samples highlights the importance of immune cells in the patient samples. A, Of the differentially expressed genes that show significantly lower expression in non-huPDX samples (orange) compared with primary ovarian cancer ascites cells and primary ovarian cancer tumor samples, 43% are immune-related genes (highlighted in purple). A list of the differentially expressed genes (left) can also be found in Supplementary Table S3. B and C, GSEA comparing primary ascites (n = 8) and primary tumors (n = 14) shows enrichment in genes associated with IFNγ stimulation in primary ascites. D–G, Deconvolution analysis of the ovarian cancer RNA-seq dataset using Carcinoma Ecotyper to estimate the abundance of monocytes/macrophages (D), CD4+ T cells (E), CD8+ T cells (F), and cancer epithelial cells (G). Deconvolution can detect the absence of immune cells in the PDX samples. Note that certain predicted states (S) may not be specific to immune cells since they are abundant in the immunocompromised non-huPDX samples (e.g., monocyte/macrophage states S07–S09 and CD4+ T-cell states S03, S05, and S06). G, The relative abundance of epithelial states is also altered in the non-huPDX with a significant reduction in states S02–S04 based on an unpaired t test (P < 0.0001, P < 0.009, P < 0.005, respectively).
Supplementary Figure S2 from LP-184, a Novel Acylfulvene Molecule, Exhibits Anticancer Activity against Diverse Solid Tumors with Homologous Recombination Deficiency
Authors: Kulkarni Aditya , Zhou Jianli , Biyani Neha , Kathad Umesh , Banerjee Partha P. , Srivastava Shiv , Prucsi Zsombor , Solarczyk Kamil , Bhatia Kishor , Ewesuedo Reginald B. , Sharma Panna
Published: May 2024

Figure S2 shows viability of parental or ATM depleted PC3M cells in response to LP-184 or Olaparib
Supplementary Figure S1 from LP-184, a Novel Acylfulvene Molecule, Exhibits Anticancer Activity against Diverse Solid Tumors with Homologous Recombination Deficiency
Authors: Kulkarni Aditya , Zhou Jianli , Biyani Neha , Kathad Umesh , Banerjee Partha P. , Srivastava Shiv , Prucsi Zsombor , Solarczyk Kamil , Bhatia Kishor , Ewesuedo Reginald B. , Sharma Panna
Published: May 2024

Figure S1 shows levels of DNA strand breaks in colon cancer cells over 24 hours
Design of an enhanced dual-band microstrip patch antenna with defected ground structures for WLAN and WiMax
Authors: El Issawi Mohamed Lemine , Onyango Konditi Dominic Bernard , Usman Aliyu Danjuma
Published: May 2024

This research presents an innovative dual-band microstrip patch antenna design enhanced with defected ground structures (DGS) and barium strontium titanate (BST) thin film, tailored for wireless local area network (WLAN) and WiMax applications. The first design phase involved the development of an microstrip patch antenna (MPA) using an flame retardant (FR4) substrate with a permittivity (εr1) of 4.3 and a thickness of 1.524 mm, enhanced with DGS. This configuration achieved a single-band resonance at 4.1 GHz, with a bandwidth of 0.82 GHz and a return loss (S11) of -32 dB. The second phase involved the integration of a BST thin film, with a high permittivity(εr2) of 250 and a thickoness of 0.1 mm, into the DGS-enhanced microstrip patch antenna (MPA). This mdification led to a transformation in the antenna's performance, enabling dual-band operation at resonance frequencies of 2.8 GHz and 5.8 GHz. Further, there was a corresponding substantial increase in bandwidth to 1.34 GHz and 1.25 GHz, respectively, an improvement in S11 values to -16.3 dB and -21.4 dB. Moreover, and antenna’s size of 14×10×1.524 mm3 . The study underscores the critical role of innovative material use and design optimization in advancing antenna technology, offering significant enhancements in bandwidth, and miniaturization, for wireless communication systems.
Comparing Leach protocol and its descendants on transferring scalar data
Authors: Bennani Mohamed Taj , Zbakh Abdelali , El Far Mohamed , Lamrini Mohamed , El Hichami Outman , El Fahssi Khalid , Satori Hassan
Published: May 2024

In the last years, The CMOS was developed and miniaturized rapidly, which, made sensors very fast, small and accurate. Hence, the creation of wireless sensor network (WSN) which are a network of nodes that exchange the data between them until it reaches the sink (base station). It is responsible for treating the data and transfer them to other servers linked to the internet for further treatment or storage. Therefore, everything related to WSN is a big topic of research for scientific community, especially transferring scalar data. In fact, many factors enter into account when it comes to send data like a radio, range of transmission, energy consumption and routing protocol. Routing protocols are very important in transferring data. They also have a big impact on energy consumption by nodes. Many categories of routing protocols exist: planning and level routing. Each type has its strength and weakness points. So, using a routing protocol in high-density environments is very challenging in energy consumption and data delivery. In addition, since level routing protocols like Leach are known for their energy efficiency. We choose three level routing protocol (Leach, MLD-Leach and MRE-Leach) to put them in a harsh environment to test their energy consumption and data transferring. We found that MLD-Leach has better energy consumption and data delivery.
Feature fusion-based video summarization using SegNetSN
Authors: Girase Sheetal Pravin , Bedekar Mangesh
Published: May 2024

This paper addresses the video summarization problem. For the given video goal is to find the subset of frames that capture the important events of the input video and produce a small concise summary. We formulate video summarization as a sequence labeling problem, where for a given input video a subset of frames are selected as a summary video. Based on the principle of semantic segmentation, here each pixel within a frame is assigned to one of the labels, where each frame is assigned a binary label indicating whether it will be included in the summary video or not. We propose a SegNet sequence network (SegNetSN) for video summarization and further extend the work by applying various feature fusion techniques to enhance the input. We performed experiments on the benchmark dataset TVSum.
A data-driven analysis to determine the optimal number of topics 'K' for latent Dirichlet allocation model
Authors: Goyal Astha , Kashyap Indu
Published: May 2024

Topic modeling is an unsupervised machine learning technique successfully used to classify and retrieve textual data. However, the performance of topic models is sensitive to selecting optimal hyperparameters, the number of topics 'K' and Dirichlet priors 'α' and 'β.' This data-driven analysis aims to determine the optimum number of topics, 'K,' within the latent Dirichlet allocation (LDA) model. This work utilizes three datasets, namely 20-Newsgroups news articles, Wikipedia articles, and Web of Science containing science articles, to assess and compare various 'K' values through the grid search approach. The grid search approach finds the best combination of hyperparameter values by trying all possible combinations to see which performs best. This research seeks to identify the 'K' that optimizes topic relevance, coherence, and model performance by leveraging statistical metrics, such as coherence scores, perplexity, and topic distribution quality. Through empirical analysis and rigorous evaluation, this work provides valuable insights for determining the ideal 'K' for LDA models.
An efficient controller-based architecture for AES algorithm using FPGA
Authors: Nadaf Reshma , Bhairannawar Satish S.
Published: May 2024

The importance of crucial current technical advancements, particularly those centered on the cryptography process such as Cryptographic advanced encryption standard (AES) hardware architectures are gaining momentum with respect to improving the speed and area optimizations. In this paper, we have proposed a novel architecture to implement AES on a reconfigurable hardware i.e., field programmable gate arrays (FPGA). The controller in AES algorithm is responsible to generate the signals to perform operations to generate the 128 bits ciphertext. The proposed controller uses multiplexer and synchronous register-based approach to obtain area and speed efficient on the FPGA hardware. The entire architecture of AES with proposed controller is implemented on Virtex 5, Virtex 6, and Virtex 7series using XilinxISE 14.7 and tested for critical path delay, frequency, slices, efficiency and throughput. It is observed that all the parameters are improved compared to existing architectures achieving the throughput of 32.29, 40.01, and 43.01 Gbps respectively. The key benefit of this approach is the high level of parallelism it displays in a quick and efficient manner.
Study of BaTiO3-doped Bi2O3/ZnO varistor microstructure and its electrical characteristics
Authors: Kharchouche Faiçal , Malaoui Yousra , Bouketir Omrane
Published: May 2024

This study presents the characterization and optimization of BaTiO3-doped ZnO-based varistors for electrical and electronic applications. The varistors were prepared using a conventional ceramic procedure and were sintered at a temperature of 1,000 °C with different concentrations of BaTiO3 (0 and 3 mol%) added to the Bi2O3/ZnO-based varistor composition (99.5 mol% ZnO and 0.5 mol% Bi2O3). The results showed that the addition of BaTiO3 led to the formation of various oxides and solid solutions, such as Bi12TiO20, BaTiO3, and (Bi2O3)0.80 (BaO)0.20. The dielectric constant and grain size decreased with increasing BaTiO3 content, while the non-linearity coefficient, electric fields (Eb) increased, and dielectric loss (Tanδ) decreased. The optimized varistor contains 2 mol% BaTiO3 and an electric field of 148.08 V/mm, which are superior to those of the BaTiO3/Bi2O3/ZnO-based varistor. During this study, we were able to observe that a slight addition of BaTiO3 will increase the breakdown voltage and the coefficient of nonlinearity and this will allow us to develop low-dimensional varistors and install them in the high-voltage domain.
A review of intrusion detection system and security threat in internet of things enabled environment
Authors: Nisha Nisha , Gill Nasib Singh , Gulia Preeti
Published: May 2024

Thousands of devices communicate globally to share data and information without any human intervention. A network of physical objects with numerous sensors and other network hardware to exchange data with servers and additional devices that are linked is referred to as the "internet of things (IoT)”. The actions hurting the communication system are known as intrusions. Security features such as (integrity, and confidentiality) within IoT networks are compromised when any kind of intrusion occurs. To identify multiple infiltration types in an environment where IoT is enabled, an intrusion detection system (IDS) is required. In environments where IoT is enabled, security vulnerabilities are now more prevalent than ever. In this study, the IoT architecture is reviewed, and potential security risks at each tier are investigated. It is also hoped that this research will stimulate thought about the expanding risks posed by unprotected IoT devices. The paper also intends to provide an in-depth analysis of intrusion detection systems for identifying and classifying security threats in an IoT-enabled environment. Furthermore, this study investigates a variety of efficient machine learning-based methods for detecting cyberattacks on IoT devices.
Use of explainable AI to interpret the results of NLP models for sentimental analysis
Authors: Bidve Vijaykumar , Shafi Pathan Mohd , Sarasu Pakiriswamy , Pavate Aruna , Shaikh Ashfaq , Borde Santosh , Pratap Singh Veer Bhadra , Raut Rahul
Published: May 2024

The use of artificial intelligence (AI) systems is significantly increased in the past few years. AI system is expected to provide accurate predictions and it is also crucial that the decisions made by the AI systems are humanly interpretable i.e. anyone must be able to understand and comprehend the results produced by the AI system. AI systems are being implemented even for simple decision support and are easily accessible to the common man on the tip of their fingers. The increase in usage of AI has come with its own limitation, i.e. its interpretability. This work contributes towards the use of explainability methods such as local interpretable model-agnostic explanations (LIME) to interpret the results of various black box models. The conclusion is that, the bidirectional long short-term memory (LSTM) model is superior for sentiment analysis. The operations of a random forest classifier, a black box model, using explainable artificial intelligence (XAI) techniques like LIME is used in this work. The features used by the random forest model for classification are not entirely correct. The use of LIME made this possible. The proposed model can be used to enhance performance, which raises the trustworthiness and legitimacy of AI systems.
Review on integration of ontology and deep learning in cultural heritage image retrieval
Authors: Budiman Fikri , Sugiarto Edi , Hendriyanto Novi
Published: May 2024

Image retrieval methods are currently developing towards big data processing. The literature review is focused on image big data extraction with cultural heritage domain as training and testing datasets. The development of image retrieval process starts from content-based using machine algorithms, deep learning to ontology-based. Image recognition research with cultural heritage domain is conducted because of the importance of preserving and appreciating cultural heritage, in this case, cultural heritage images such as Indonesian Batik are discussed. Batik motif images are Indonesian cultural heritage that has thousands of motifs that are grouped into many classes with a non-linear hyperplane. The problem is focused on processing big data that has many classes. Currently research is evolving into knowledge-based image retrieval using ontologies due to semantic gap constraints. The results of this literature study can be the basis for developing research on the application of appropriate deep learning algorithms so as to utilize the hierarchy of classes and subclasses of image ontologies with cultural heritage domains.
Development of a payload for monitoring biological samples in microgravity and hypergravity conditions
Authors: Canto-Vivanco Elber E. , Ramos-Cosi Sebastian , Romero-Alva Victor N. , Vargas-Cuentas Natalia I. , Roman-Gonzalez Avid
Published: May 2024

This research aims to address the need for monitoring the behavior of organic and inorganic materials in hypergravity conditions. To fulfill this objective, a container with specific features was designed. The container has a box with a lid, measuring 10×10×10 cm, conforming to the 1U volume of the CubeSat standard. It includes four cylindrical spaces to accommodate the sample wells. The container was 3D printed using polylactic acid (PLA) wire. For the electronic components, four ESP32-CAM modules were utilized, with two programmed to capture and upload photos to the cloud, and the other two programmed to capture and store photos on a micro SD memory card. Additionally, four light emitting diodes (LEDs) were incorporated to illuminate the well spaces. The total weight of the container is 450 grams, and it has a maximum wireless upload distance of 10 meters to the cloud. The storage capacity of the SD memory card determines the number of images that can be saved.
ADKNN fostered BIST with Namib Beetle optimization algorithm espoused BISR for SoC-based devices
Authors: Alnatheer Suleman , Ahmed Mohammed Altaf
Published: May 2024

Redundancy analysis is a widely used method in fault-tolerant memory systems, and it is essential for large-size memories. In current security operations centers (SoCs), memory occupies most of the chip space. To correct these memories using a conventional external equipment test approach is more difficult. To overcome this issue, memory creators utilize redundancy mechanism for substituting the columns and rows along with a spare one to increase output of the memories. In this study, a built-in-self-test (BIST) to test memories and built-in-self-repair (BISR) mechanism to repair the faulty cells for any recent SoC devices is proposed. The BIST, based on adaptive activation functions with a deep Kronecker neural network (ADKNN), not only detects the defect but also determines the kind of defect. The BISR block uses the Namib Beetle optimization algorithm (NBOA) to fix the mistakes in the memory under test (MUT). The study attempts to determine how the characteristics of SoC-based devices change in the real world and then contributes to the suggested controller blocks. Performance metrics such as slice register, region, delay, maximum operating frequency, power consumption, minimum clock period, and access time evaluate performance. Comparing the proposed ADKNN-NBOA-BIST-BISR scheme to existing BIST, BISR, and BISD-based methods reveals its significant performance.
Universalismo renovado, ciudadanía social y políticas públicas
Authors: Duque Daza Javier
Published: May 2024

Este artículo analiza tres enfoques sobre las relaciones Estado, sociedad y políticas públicas. El objetivo central es analizar las tres formas de asumir la provisión de bienes y servicios por parte del Estado y la respectiva concepción de la ciudadanía social: la selectividad, el universalismo y el universalismo renovado o de nuevo tipo. La metodología utilizada se basó en la revisión sistemática de autores centrales que han trabajado este tema desde las políticas públicas. Se hizo la revisión, se contrastaron y se determinó la forma de proponer una alternativa a los modelos clásicos. Se describen sus principales características, sus limitaciones, las críticas y las tendencias actuales de reivindicación del papel del Estado en el desarrollo social y humano y el desarrollo de la ciudadanía social. El resultado es una reflexión conceptual y teórica sobre uno de los problemas básicos de la discusión actual sobre estado y ciudadanía sin reiterar y avanzando sobre una tercera alternativa: el universalismo renovado.
Proceso de inclusión educativa: de narrativas de déficit a narrativas de las potencias sobre niños y niñas en condición de discapacidad en la primera infancia
Authors: Ávila Babativa Maria Andrea , Martínez Murcia Ana Carolina , Ospina Alvarado María Camila
Published: May 2024

El artículo presenta los resultados de la investigación desarrollada con seis docentes del Jardín Colinas de la localidad Rafael Uribe Uribe y seis docentes del Instituto de Integración Cultural de la localidad de Puente Aranda. El objetivo de la investigación fue comprender las narrativas de los docentes frente a las categorías de inclusión educativa y discapacidad en la primera infancia, mediante la identificación de relatos, así como de los factores culturales, afectivos, sociales y educativos que inciden en la constitución de los mismos. Se utilizó metodología cualitativa, realizando análisis categorial de narrativas. Como conclusión, se plantea que las narrativas de los docentes, construidas de manera relacional, se enfocan principalmente en descripciones deficitarias acerca de los niños, siendo posible identificar algunos relatos alternativos que enfatizan en las potencias.
Cross-Seal IDE Trial: Prospective, Multicenter, Single-Arm Study of the Cross-Seal Suture-Mediated Vascular Closure Device System
Authors: Krishnan Prakash , Farhan Serdar , Zidar Frank , Krajcer Zvonimir , Metzger Christopher , Kapadia Samir , Moore Erin , Nazif Tamim , Garland Ty , Zhang Ming , Khera Sahil , Sharafuddin Mel , Patel Virendra I. , Bacharach John Michael , Coady Paul , Schermerhorn Marc L. , Shames Murray L. , Rahimi Saum , Panneton Jean M. , Elkins Craig , Foteh Mazin
Published: May 2024

BACKGROUND:

An increasing number of interventional procedures require large-sheath technology (>12F) with a favorable outcome with endovascular rather than open surgical access. However, vascular complications are a limitation for the management of these patients. This trial aimed to determine the effectiveness and safety of the Cross-Seal suture-mediated vascular closure device in obtaining hemostasis at the target limb access site following interventional procedures using 8F to 18F procedural sheaths.

METHODS:

The Cross-Seal IDE trial (Investigational Device Exemption) was a prospective, single-arm, multicenter study in subjects undergoing percutaneous endovascular procedures utilizing 8F to 18F ID procedural sheaths. The primary efficacy end point was time to hemostasis at the target limb access site. The primary safety end point was freedom from major complications of the target limb access site within 30 days post procedure.

RESULTS:

A total of 147 subjects were enrolled between August 9, 2019, and March 12, 2020. Transcatheter aortic valve replacement was performed in 53.7% (79/147) and percutaneous endovascular abdominal/thoracic aortic aneurysm repair in 46.3% (68/147) of subjects. The mean sheath ID was 15.5±1.8 mm. The primary effectiveness end point of time to hemostasis was 0.4±1.4 minutes. An adjunctive intervention was required in 9.2% (13/142) of subjects, of which 2.1% (3/142) were surgical and 5.6% (8/142) endovascular. Technical success was achieved in 92.3% (131/142) of subjects. Freedom from major complications of the target limb access site was 94.3% (83/88).

CONCLUSIONS:

In selected patients undergoing percutaneous endovascular procedures utilizing 8F to 18F ID procedural sheath, Cross-Seal suture-mediated vascular closure device achieved favorable effectiveness and safety in the closure of the large-bore arteriotomy.

REGISTRATION:

URL:
https://www.clinicaltrials.gov
; Unique identifier: NCT03756558.
VINNA for neonates: Orientation independence through latent
augmentations
Authors: Henschel Leonie , Kügler David , Zöllei Lilla , Reuter Martin
Published: May 2024

A robust, fast, and accurate segmentation of neonatal brain images is highly desired to better understand and detect changes during development and disease, specifically considering the rise in imaging studies for this cohort. Yet, the limited availability of ground truth datasets, lack of standardized acquisition protocols, and wide variations of head positioning in the scanner pose challenges for method development. A few automated image analysis pipelines exist for newborn brain Magnetic Resonance Image (MRI) segmentation, but they often rely on time-consuming non-linear spatial registration procedures and require resampling to a common resolution, subject to loss of information due to interpolation and down-sampling. Without registration and image resampling, variations with respect to head positions and voxel resolutions have to be addressed differently. In deep learning, external augmentations such as rotation, translation, and scaling are traditionally used to artificially expand the representation of spatial variability, which subsequently increases both the training dataset size and robustness. However, these transformations in the image space still require resampling, reducing accuracy specifically in the context of label interpolation. We recently introduced the concept of resolution-independence with the Voxel-size Independent Neural Network framework, VINN. Here, we extend this concept by additionally shifting all rigid-transforms into the network architecture with a four degree of freedom (4-DOF) transform module, enabling resolution-aware internal augmentations (VINNA) for deep learning. In this work, we show that VINNA (i) significantly outperforms state-of-the-art external augmentation approaches, (ii) effectively addresses the head variations present specifically in newborn datasets, and (iii) retains high segmentation accuracy across a range of resolutions (0.5–1.0 mm). Furthermore, the 4-DOF transform module together with internal augmentations is a powerful, general approach to implement spatial augmentation without requiring image or label interpolation. The specific network application to newborns will be made publicly available as VINNA4neonates.
Idiosyncratic patterns of interhemispheric connectivity in the face and scene networks of the human brain
Authors: Quinn Bartholomew P.A. , Watson David M. , Noad Kira , Andrews Timothy J.
Published: May 2024

Neuroimaging studies have revealed a network of regions in both hemispheres of the human brain that respond selectively to faces. Neural models of face processing have typically focused on functional connectivity between regions in the same hemisphere (intrahemispheric), with a particular bias toward the right hemisphere. Here, we explored the role of interhemispheric connectivity using fMRI. We used three datasets to compare functional connectivity, as shown by correlations between the time-courses of neural activity of face regions during different natural viewing paradigms. We found higher correlations of neural activity between corresponding interhemispheric regions (e.g., rFFA–lFFA) than between intrahemispheric regions (e.g., rFFA–rOFA), indicating a bias towards higher interhemispheric than intrahemispheric connectivity. A similar interhemispheric bias was evident in scene-selective regions. In contrast, we did not find an interhemispheric bias in early visual regions (V1–V3), where intrahemispheric connectivity between corresponding regions was generally higher than interhemispheric connectivity. Next, we asked whether the higher interhemispheric connectivity in the face and scene networks between corresponding regions was consistent across participants. We found that the interhemispheric bias was significantly attenuated when we compared the time-course of response across participants. This shows that interhemispheric bias in connectivity between corresponding regions in the face and scene networks is specific to the individual. These findings raise the possibility that idiosyncratic variation in interhemispheric connectivity may explain individual differences in perception.
Neural Networks as Cognitive Models of the Processing of Syntactic Constraints
Authors: Arehalli Suhas , Linzen Tal
Published: May 2024

Languages are governed by syntactic constraints—structural rules that determine which sentences are grammatical in the language. In English, one such constraint is subject-verb agreement, which dictates that the number of a verb must match the number of its corresponding subject: “the dogs run”, but “the dog runs”. While this constraint appears to be simple, in practice speakers make agreement errors, particularly when a noun phrase near the verb differs in number from the subject (for example, a speaker might produce the ungrammatical sentence “the key to the cabinets are rusty”). This phenomenon, referred to as agreement attraction, is sensitive to a wide range of properties of the sentence; no single existing model is able to generate predictions for the wide variety of materials studied in the human experimental literature. We explore the viability of neural network language models—broad-coverage systems trained to predict the next word in a corpus—as a framework for addressing this limitation. We analyze the agreement errors made by Long Short-Term Memory (LSTM) networks and compare them to those of humans. The models successfully simulate certain results, such as the so-called number asymmetry and the difference between attraction strength in grammatical and ungrammatical sentences, but failed to simulate others, such as the effect of syntactic distance or notional (conceptual) number. We further evaluate networks trained with explicit syntactic supervision, and find that this form of supervision does not always lead to more human-like syntactic behavior. Finally, we show that the corpus used to train a network significantly affects the pattern of agreement errors produced by the network, and discuss the strengths and limitations of neural networks as a tool for understanding human syntactic processing.
Twenty years of the Open Access movement: A retrospective study on the relationship between publishing strategies and scientific capital of Brazilian researchers in biological science
Authors: Sarzi Deise Schröder , Leta Jacqueline
Published: May 2024

In this study, we aim to investigate the publishing strategies adopted by the Brazilian scientific community and how they are related to the researchers’ scientific capital. The “research productivity” grant (PQ grant) is taken as an indicator of scientific capital: The greater the PQ grant a researcher receives, the greater is their scientific capital. Personal data from 6,993 researchers linked to at least one Brazilian graduate program in biological sciences were obtained through the Sucupira Platform, data on articles published from 2000 to 2019 were retrieved from the Lattes Platform, and the Directory of Open Access Journals was consulted to classify articles as Open Access (OA). Our main findings indicate that subscription-based journals are the most prevalent publishing strategy, but the proportion of OA publications is increasing over time, mainly with article processing charges (APC). We also observed that the lower the level of PQ grant, the higher the share of articles in OA journals. Finally, we observed a growing trend in the percentage of researchers with high and mid-high adherence to OA from all levels of PQ grant, but mainly with APC. Mapping the dynamics of publishing strategies can play an important step towards driving policies oriented to the promotion of OA.
Latent variable modeling of scientific impact: Estimation of the Q model parameters with structural equation models
Authors: Forthmann Boris , Nestler Steffen
Published: May 2024

Statistical modeling of scientific productivity and impact provides insights into bibliometric measures used also to quantify differences between individual scholars. The Q model decomposes the log-transformed impact of a published paper into a researcher capacity parameter and a random luck parameter. These two parameters are then modeled together with the log-transformed number of published papers (i.e., an indicator of productivity) by means of a trivariate normal distribution. In this work we propose a formulation of the Q model that can be estimated as a structural equation model. The Q model as a structural equation model allows us to quantify the reliability of researchers’ Q parameter estimates. It can be extended to incorporate person covariates and multivariate extensions of the Q model could also be estimated. We empirically illustrate our approach to estimate the Q model and also provide openly available code for R and Mplus.
Attrition and the Gender Patenting Gap
Authors: Aneja Abhay , Reshef Oren , Subramani Gauri
Published: May 2024

Women are underrepresented in patenting. In this study, we consider differential responsiveness to rejection as a contributor to the gender gap in invention. Leveraging the prosecution histories of almost one million U.S. patent applications and the quasi-random assignment of applications to examiners, we show that women are 3.6-6.9 percentage points less likely to continue in the application process following an early-stage rejection. Conditional on applying for a patent, male-female disparities in the propensity to abandon applications account for more than half of the overall gender gap in issued patents. We provide suggestive evidence that institutional support can help reduce the attrition gap.
Permanent and Transitory Responses to Capital Gains Taxes: Evidence from a Lifetime Exemption in Canada
Authors: Lavecchia Adam M. , Tazhitdinova Alisa
Published: May 2024

Using panel data on a 20% random sample of Canadian taxpayers, we study behavioral responses to the cancellation of a lifetime capital gains exemption that resulted in increased capital gains taxation for some individuals. We show that the exemption did not change the number of taxpayers reporting positive capital gains, and thus unlikely resulted in increased participation in capital markets. Furthermore, our results suggest that the cancellation increased the long-run capital gains realizations of tax filers with more unused exemption room but had a small, statistically insignificant impact on the capital gains realizations of those with little unused exemption room.
Destruction, Policy, and the Evolving Consequences of Washington, DC's 1968 Civil Disturbance
Authors: Brooks Leah , Rose Jonathan , Veuger Stan
Published: May 2024

We study the aftermath of the 1968 Washington, DC civil disturbance to illuminate the mechanisms that drive urban redevelopment in the presence of low demand and racial tension. Using a within-block identification strategy, we show that destruction caused lots to remain vacant for the next thirty years and only recently converge in terms of structure value. The city acted to preclude for-profit land owners from leaving land vacant until demand conditions improved by purchasing nearly half of all properties in damaged neighborhoods. Despite this and other steps, the city had limited success in speeding up redevelopment.
Critical Values Robust to P-hacking
Authors: McCloskey Adam , Michaillat Pascal
Published: May 2024

P-hacking is prevalent in reality but absent from classical hypothesis-testing theory. We therefore build a model of hypothesis testing that accounts for p-hacking. From the model, we derive critical values such that, if they are used to determine significance, and if p-hacking adjusts to the new significance standards, spurious significant results do not occur more often than intended. Because of p-hacking, such robust critical values are larger than classical critical values. In the model calibrated to medical science, the robust critical value is the classical critical value for the same test statistic but with one fifth of the significance level.
Aid Fragmentation and Corruption
Authors: Child Travers B. , Wright Austin L. , Xiao Yun
Published: May 2024

Aid fragmentation—the simultaneous operation of multiple development agencies in one setting—has long raised concerns about coordination challenges and opportunities for corruption. Leveraging unique data on project delivery in Afghanistan, we present the first microlevel empirical analysis of aid fragmentation. We find that aid delivered by a single donor can significantly reduce corruption. Projects delivered under conditions of aid fragmentation, by contrast, can facilitate corruption. We find evidence for a theoretical mechanism linking infrastructure and physical goods with waste and leakage. Our results clarify the policy losses tied to fragmentation, yielding insights for combating misappropriation of aid.
Simultaneous Selection and Adaptation of Source Data via Four-Level Optimization
Authors: Xie Pengtao , Zhao Xingchen , He Xuehai
Published: May 2024

In many NLP applications, to mitigate data deficiency in a target task, source data is collected to help with target model training. Existing transfer learning methods either select a subset of source examples that are close to the target domain or try to adapt all source examples into the target domain, then use selected or adapted source examples to train the target model. These methods either incur significant information loss or bear the risk that after adaptation, source examples which are originally already in the target domain may be outside the target domain. To address the limitations of these methods, we propose a four-level optimization based framework which simultaneously selects and adapts source data. Our method can automatically identify in-domain and out-of-domain source examples and apply example-specific processing methods: selection for in-domain examples and adaptation for out-of-domain examples. Experiments on various datasets demonstrate the effectiveness of our proposed method.
Automatically Correcting Large Language Models: Surveying the Landscape of Diverse Automated Correction Strategies
Authors: Pan Liangming , Saxon Michael , Xu Wenda , Nathani Deepak , Wang Xinyi , Wang William Yang
Published: May 2024

While large language models (LLMs) have shown remarkable effectiveness in various NLP tasks, they are still prone to issues such as hallucination, unfaithful reasoning, and toxicity. A promising approach to rectify these flaws is correcting LLMs with feedback, where the LLM itself is prompted or guided with feedback to fix problems in its own output. Techniques leveraging automated feedback—either produced by the LLM itself (self-correction) or some external system—are of particular interest as they make LLM-based solutions more practical and deployable with minimal human intervention. This paper provides an exhaustive review of the recent advances in correcting LLMs with automated feedback, categorizing them into training-time, generation-time, and post-hoc approaches. We also identify potential challenges and future directions in this emerging field.
CloudRoots-Amazon22: Integrating Clouds with Photosynthesis by Crossing Scales
Authors: Vilà-Guerau de Arellano J. , Hartogensis O. K. , de Boer H. , Moonen R. , González-Armas R. , Janssens M. , Adnew G. A. , Bonell-Fontás D. J. , Botía S. , Jones S. P. , van Asperen H. , Komiya S. , de Feiter V. S. , Rikkers D. , de Haas S. , Machado L. A. T. , Dias-Junior C. Q. , Giovanelli-Haytzmann G. , Valenti W. I. D. , Figueiredo R. C. , Farias C. S. , Hall D. H. , Mendonça A. C. S. , da Silva F. A. G. , Marton da Silva J. L. , Souza R. , Martins G. , Miller J. N. , Mol W. B. , Heusinkveld B. , van Heerwaarden C. C. , D’Oliveira F. A. F. , Rodrigues Ferreira R. , Gotuzzo R. Acosta , Pugliese G. , Williams J. , Ringsdorf A. , Edtbauer A. , Quesada C. A. , Takeshi Tanaka Portela B. , Gomes Alves E. , Pöhlker C. , Trumbore S. , Lelieveld J. , Röckmann T.
Published: May 2024

How are rain forest photosynthesis and turbulent fluxes influenced by clouds? To what extent are clouds affected by local processes driven by rain forest energy, water, and carbon fluxes? These interrelated questions were the main drivers of the intensive field experiment CloudRoots-Amazon22 which took place at the Amazon Tall Tower Observatory (ATTO)/Campina supersites in the Amazon rain forest during the dry season, in August 2022. CloudRoots-Amazon22 collected observational data to derive cause–effect relationships between processes occurring at the leaf level up to canopy scales in relation to the diurnal evolution of the clear-to-cloudy transition. First, we studied the impact of cloud and canopy radiation perturbations on the subdiurnal variability of stomatal conductance. Stoma opening is larger in the morning, modulated by the cloud optical thickness. Second, we combined 1-Hz frequency measurements of the stable isotopologues of carbon dioxide and water vapor with measurements of turbulence to determine carbon dioxide and water vapor sources and sinks within the canopy. Using scintillometer observations, we inferred 1-min sensible heat flux that responded within minutes to the cloud passages. Third, collocated profiles of state variables and greenhouse gases enabled us to determine the role of clouds in vertical transport. We then inferred, using canopy and upper-atmospheric observations and a parameterization, the cloud cover and cloud mass flux to establish causality between canopy and cloud processes. This shows the need for a comprehensive observational set to improve weather and climate model representations. Our findings contribute to advance our knowledge of the coupling between cloudy boundary layers and primary carbon productivity of the Amazon rain forest.
Identification of Chronic Pancreatitis Associated microRNAs and Genes for the Diagnosis of Pancreatic Cancer
Authors: Gong Jing , Zhang Qinghua , Peng Qimin , Shi Dongling
Published: May 2024

Objective

The timely identification of both malignant and nonmalignant pancreatic lesions has the potential to significantly enhance prognosis and implement risk management strategies across various levels. microRNAs (miRs) and their corresponding targets play a crucial role in the development of pancreatic lesions and can serve as valuable diagnostic and therapeutic targets. The objective of our study was to investigate potential diagnostic markers that can effectively differentiate between malignant and nonmalignant pancreatic lesions.

Methods

Gene Expression Omnibus (GEO) database with GSE24279 dataset was utilized to screen differentially expressed miRNAs (DEMs). We utilized the TargetScanHuman database to predict the target genes associated with hsa-miR-150-3p, hsa-miR-150-5p, and hsa-miR-214-3p. Furthermore, a cohort comprising healthy individuals (n = 52), chronic pancreatitis (CP; n = 34), and pancreatic adenocarcinoma (PAAD; n = 53) patients was recruited to ascertain the levels of plasma markers.

Results

We identified 3 miRNAs (hsa-miR-150-3p, hsa-miR-150-5p, and hsa-miR-214-3p) and 2 proteins (PCDH1 and AMN) as potential diagnostic markers for distinguishing between CP and PAAD. The area under the curve (AUC) values for all markers exceeded .800. Notably, a combination of plasma PCDH1 and AMN demonstrated excellent diagnostic performance (AUC = .921; 95% CI: .866-.977; sensitivity = .792; specificity = .941) in discriminating between CP and PAAD. In addition, the model of hsa-miR-150-3p, hsa-miR-150-5p, and hsa-miR-214-3p yielded an AUC of .928, sensitivity of .830, and specificity of .912, respectively.

Conclusion

Plasma levels of miRNAs (hsa-miR-150-3p, hsa-miR-150-5p, and hsa-miR-214-3p) and their corresponding targets (PCDH1 and AMN) hold promise as potential biomarkers for predicting PAAD in patients with CP.
A retrospective review and reflection on the alignment of SIMULATION with the evolving professional realm of Modeling and Simulation
Authors: Yilmaz Levent
Published: May 2024

This paper highlights the renewal and restructuring period for SIMULATION: Transactions of the Society for Modeling and Simulation (SCS) between 2008 and 2016. Following a retrospective review of the author’s formative years, evolving research interests, and continuing academic journey, the rationale for reorganizing the journal is examined in the context of the evolving professional realm of Modeling and Simulation (M&S). The alignment of the profession, developments in the broader M&S domain, and related SCS initiatives are discussed. The simulation discipline is viewed as a dynamic adaptive innovation ecosystem that brings the principles of the science of complexity to bear on the challenges to its resilience and vitality. The innovation dynamics and complexity perspectives imply future aspirations for the M&S discipline based on recent technological advancements, emerging trends in the scientific culture, and evolving societal demands.
Parents’ Industrial Sectors and Fields of Study: Five Decades of Evidence from an Elite Regional University in China
Authors: Zang Emma , Yang Yining Milly , Lee James Z
Published: May 2024

How family background affects students’ fields of study across different historical periods in China is not well studied. Post 1949, China explicitly prioritized specific industrial sectors when allocating resources, creating an especially strong reason to expect that the industrial sector in which a parent was employed might strongly influence a child’s educational outcomes and career aspirations. Using data from the school registration records of 51,801 students who entered an elite regional university from 1952 through 2002, this study is the first to examine the role of parents’ industrial sectors in predicting children’s fields of study and the temporal patterns of this association. Applying multinomial logistic regression and the log-multiplicative layer effect model, we found that parents’ industrial sectors predicted children’s fields of study independent of parents’ broad categories of occupation. The strength of the association was particularly strong during the Cultural Revolution and post-market transition periods.