bluuebunny/crossref_metadata_2025 huggingface dataset:
Abstract SY37-03: Leveraging the complexities of tumor associated macrophages for effective anti-cancer therapy
Authors: Guerriero Jennifer L.
Published: April 2024

Macrophages are innate immune cells that play a critical role in host defense and maintaining tissue homeostasis, however their infiltration into tumors is associated with disease progression and resistance to therapy. Tumor associated macrophages (TAMs) represent a significant proportion of solid tumors, including breast cancer. TAMs play a major role in tumorigenesis as they can enhance tumor cell growth, angiogenesis and metastasis. In addition, TAMs can inhibit anti-tumor responses of T cells. Our recent work has shown that removal or conversion of TAMs to an anti-tumor phenotype enhances chemo- and immuno-therapy establishing TAMs as targets for anti-cancer therapy. Using high-dimensional single-cell and multi-omics profiling of murine and human breast tumors we reveal multiple subsets of TAMs with distinct transcriptional and activity profiles that correlate with progression of disease and response to therapy. This work has revealed the complexity of TAMs and major gaps in our knowledge of the functional and phenotypic characterization of TAM subsets associated with cancer, before and after treatment. Here we will discuss the complexity of TAMs in solid tumors including characterizing TAM subsets, location, and crosstalk with neighboring cells, as well as novel TAM-modulating strategies and combinations that are likely to enhance current therapies and overcome chemo- and immuno-therapy resistance. Our findings support the idea that targeting TAMs offers great potential to enhance both chemo- and immuno-therapy.

Citation Format: Jennifer L. Guerriero. Leveraging the complexities of tumor associated macrophages for effective anti-cancer therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr SY37-03.
Distinct Distribution of HBB Variants in Two Cohorts of Beta Thalassemia Patients, and a Novel Variant from Turkey
Authors: Kocak Eker Hatice , Balasar Ozgur
Published: April 2024

Introduction: Beta thalassemia is a serious disease for which mutation-based diagnostic and screening tests are readily available. These tests are based on specific variant profile in the regions of the testing centers. De novo mutations and migration change the distribution of these variants. We aim to update the variant spectrum in the HBB gene in our region. In addition, we present a variant, which not been detected before in Turkey, and also a changed classification of another variant. Methods: This study includes 142 patients (46 of Turkish, 96 of Syrian) who were investigated for defects in their β-globin gene with Sanger sequencing. Clinically, 52 of these patients had thalassemia major, and 90 had thalassemia minor. Results: Twenty three types of pathogenic variants were identified causing beta thalassemia and abnormal hemoglobins. Variant distribution has differed considerably between Turkish and Syrian patients. While the IVSI-110G>A was the most prevalent variant (41.1%) in Turkish patients, the IVSII-1G>A and Codon 39 (C>T) variants were found in 22% and 21.3%, respectively, in Syrian patients. We detected the novel c.31_32insT variant in 3 Syrian patients. Conclusion: The detection of updated regional HBB variant spectrum will contribute to future prenatal and/or postnatal molecular diagnostic tests. Also, our study presents a novel variant that was not previously reported.
Akne vulgaris: Post-hoc-Analyse zeigt anhaltende Verbesserung durch Clascoteron-Creme
Authors: Makrantonaki Evgenia
Published: April 2024

Background: Clascoterone cream 1% is approved for the treatment of acne vulgaris in patients aged 12 years or older based on results from two identical pivotal Phase 3 trials. Integrated efficacy of clascoterone in patients aged 12 years or older with acne vulgaris from the pivotal trials (NCT02608450 and NCT02608476) and long-term extension (LTE) study (NCT02682264) is reported. Methods: In the pivotal trials, patients with moderate-to-severe acne vulgaris were randomized 1:1 to twice-daily application of clascoterone cream 1% or vehicle for 12 weeks; they could then enter the LTE study, where all patients applied clascoterone to the face and, if desired, trunk for up to 9 additional months. Efficacy was assessed from treatment success based on Investigator's Global Assessment scores (IGA 0/1) in patients aged 12 years or older in the intention-to-treat population; lesion counts were assessed through week 12. Missing data were handled using multiple imputation in the pivotal studies and were not imputed in the LTE study. Results: Of 1421 patients enrolled, 1143 (clascoterone, 576; vehicle, 567) completed week 12; 600 entered and 343 completed the LTE study. The treatment success rate and most lesion count reductions following clascoterone vs placebo treatment reached statistical significance at week 12; the overall treatment success rate increased to 30.2% for facial acne after 12 months and 31.7% for truncal acne after 9 months of treatment.
A lightweight YOLOv5 for real-time dangerous weapons detection
Authors: Khalfaoui Aicha , Badri Abdelmajid , El Mourabit Ilham
Published: April 2024

Deep neural networks are currently employed to detect weapons, and although these techniques provide a high level of accuracy, it still suffers from large weight parameters and a slow inference speed. When it comes to real-world applications, such as weapon detection, these methods are often not suitable for deployment on embedded devices. Because of the huge number of parameters and poor efficiency. The most recent object detection technique, which belongs to the YOLOv5 class, is commonly used for detecting weapons. However, it faces some difficulties such as high computational parameters and an unfavorable detection rate. to solve these shortcomings. an enhanced lightweight Yolov5s approach is suggested. Which consists of a combination of YOLOv5 and GhostNet modules. To evaluate the efficacy of the suggested technique, a set of experiments was performed on the Sohas weapon dataset., which is commonly used as a reference dataset in the field. Compared to the original YOLOv5, the results indicate a slight increase in the proposed model's mean Average Precision (mAP). Furthermore, there has been a reduction of 2.7 in GFLOPs and weights, and the number of model parameters has decreased by 1.42.
EASESUM: an online abstractive and extractive text summarizer using deep learning technique
Authors: Adeniyi Jide Kehinde , Ajagbe Sunday Adeola , Adeniyi Abidemi Emmanuel , Aworinde Halleluyah Oluwatobi , Falola Peace Busola , Adigun Matthew Olusegun
Published: April 2024

Large volumes of information are generated daily, making it challenging to manage such information. This is due to redundancy and the type of data available, most of which needs to be more structured and increases the amount of search time. Text summarization systems are considered a real solution to this vast amount of data because they are used for document compression and reduction. Text summarization keeps the relevant information and eliminates the text's non-relevant parts. This study uses two types of summarizers: Extractive Text summarizers and Abstractive text summarizers. The Text Rank Algorithm was used to implement the Extractive summarizer, while Bi-directional Recurrent Neural Network (RNN) was used to implement the Abstractive text summarizer. To improve the quality of summaries produced, word embedding was also used. For the evaluation of the summarizers, the ROUGE evaluation system was used. ROUGE contrasts summaries created by hand versus those created automatically. ROUGE examination of the produced summary revealed the superiority of human-produced summaries over those generated automatically. For this paper, a summarizer was implemented as a Web Application. The average ROUGE recall score ranging from 30.00 to 60.00 for abstractive summarizer and 0.75 to 0.82 for extractive text showed an encouraging result.
Comparative analysis of explainable AI models for predicting lung cancer using diverse datasets
Authors: Makubhai Shahin , R Pathak Ganesh , R Chandre Pankaj
Published: April 2024

Lung cancer prediction is crucial for early detec-tion and treatment, and explainable AI models have gained attention for their interpretability. This study aims to compare various explainable AI models using diverse datasets for lung cancer prediction. Clinical, genomic, and imaging data from multiple sources were collected, prepro-cessed, and used to train models such as Logistic Regression, SVC-Linear, SVC-rbf, Decision Tree, Random Forest, AdaBoost Classifier, and XGBoost Classifier. Preliminary results indicate that Random Forest achieved the highest accuracy of 98.9% across multiple datasets. Evaluation metrics such as accuracy, precision, recall, and F1 score were utilized, along with interpretability techniques like feature importance rankings and rule extraction methods. The study's findings will aid in identifying effective and interpretable AI models, facilitating early detection and treatment decisions for lung cancer.
Enhancing ANPR accuracy for staff car verification using convolutional neural networks and RegEX correction
Authors: AWOSEYI Ayomikun Abayomi , TIMOTHY Timileyin Favour , ONUIRI Ernest E. , ABDULAHI Qudus Opeyemi , Ajagbe Sunday Adeola , Adigun Matthew
Published: April 2024

This research paper presents the development and evaluation of an Automatic Number Plate Recognition (ANPR) system using Convolutional Neural Networks (CNN) with Regex correction. The aim is to enhance the accuracy and effectiveness of car verification and security processes at First Technical University, Ibadan. The ANPR system was implemented both without Regex correction and with Regex correction. The evaluation results demonstrate significant improvements in the system's performance when CNN with Regex correction is employed. The CNN-based ANPR system achieves a precision of 1.00, recall of 0.90, and F1-score of 0.95 in accurately identifying number plates. These scores indicate increased accuracy and reduce false positives compared to the system without Regex correction. The integration of CNN and Regex correction effectively handles variations and errors in the number plate data, leading to a reliable and efficient car verification process. Future work can focus on further refining the CNN model and optimizing the Regex correction algorithms to enhance the system's accuracy and robustness. The developed ANPR system, utilizing CNN with Regex correction, shows great potential for enhancing car verification and security in various domains, including law enforcement, parking management, and traffic monitoring
Multi-granularity tooth analysis via YOLO-based object detection models for effective tooth detection and classification
Authors: AbuSalim Samah , Zakaria Nordin , Maqsood Aarish , Saboor Abdul , Kwang Hooi Yew , Mokhtar Norehan , Jadid Abdulkadir Said
Published: April 2024

Accurate detection and classification of teeth is the first step in dental disease diagnosis. However, the same class of tooth exhibits significant variations in surface appearance. Moreover, the complex geometrical structure poses challenges in learning discriminative features among the different tooth classes. Due to these complex features, tooth classification is one of the challenging research domains in deep learning. To address the aforementioned issues, the presented study proposes discriminative local feature extraction at different granular levels using YOLO models. However, this necessitates a granular intra-oral image dataset. To facilitate this requirement, a dataset at three granular levels (two, four, and seven teeth classes) is developed. YOLOv5, YOLOv6, and YOLOv7 models were trained using 2,790 images. The results indicate superior performance of YOLOv6 for two-class classification problems. The model generated a mean average precision (mAP) value of 94%. However, as the granularity level is increased, the performance of YOLO models decreases. For, four and seven-class classification problems, the highest mAP value of 87% and 79% was achieved by YOLOv5 respectively. The results indicate that different levels of granularity play an important role in tooth detection and classification. The YOLO’s performance gradually decreased as the granularity decreased especially at the finest granular level.
Identification and classification of Prakriti of human using facial features
Authors: Suguna Guttor Chickaramanna , S T Veerabhadrappa
Published: April 2024

Changes in the lifestyle of individual, several of disease has emerged due to imbalance of doshas components. Ayurveda practitioners could identify the imbalance of dosha and relate the root cause of imbalance of doshas. Analysis of dosha varies from practitioner to practitioner and it requires well practiced practitioner to identify dosha. To overcome, the darshana method was adopted to automatically identify predominant dosha using facial features such as face, eyes, nose, and mouth and skin color. Computer vision and Image processing techniques were made attempted in Ayurveda domain, for identification of predominate prakriti, age, and gender of the subject. Eye Aspect Ratio (EAR), Nose Aspect Ratio (NAR), Mouth Aspect Ratio (MAR) and skin color was computed based on Euclidean distance to identify on-live predomaint prakriti of an individual. The values of MAR  ≤  0.5,EAR  ≤  0.1,NAR  ≤  0.8 as identified as vata , 0.5  ≥ MAR  ≤  0.6, 0.1  ≥  EAR  ≤  0.2, 0.8 ≥ NAR ≤ 1 as identified as pitta and MAR  ≥  0.6,EAR  ≥ 0.2 and NAR  ≥  1 as identified as kapha dosha. With the features MAR, EAR and NAR classification of predominant prakriti was carried out with an accuracy of 87.5% with support vector classifier.
Knee osteoarthritis automatic detection using U-Net
Authors: Salama Ahmed , Rahouma Kamel , Mansour Fatma Elzahraa
Published: April 2024

Knee osteoarthritis or OA is one of the most common diseases that can affect the elderly and overweight people. OA is occur as the result of wear and tear and progressive loss of articular cartilage. Kellgren-Lawrence system is a common method of classifying the severity of osteoarthritis depends on knee joint width. According to Kellgren-Lawrence, knee osteoarthritis is divided into five classes; one class represents a normal knee and the others represent four levels of knee osteoarthritis. In this work, we aim to automatically detect knee OA according to the Kellgren-Lawrence classification. The proposed system uses the U-Net architecture. The overall system yielded an accuracy of 96.3% during training.
Sensitivity and feature importance of climate factors and evaluation of different machine learning models for predicting fire hotspots in Kalimantan, Indonesia
Authors: Nurdiati Sri , Nugrahani Endar Hasafah , Bukhari Fahren , Najib Mohamad Khoirun , Sebastian Denny Muliawan , Nur Fallahi Putri Afia
Published: April 2024

Hotspots as indicators of forest fires capable of quickly monitoring large areas are often predicted using various machine learning methods. However, there is still little research that analyzes the sensitivity and feature importance of each predictor that forms a machine learning prediction model. This study evaluates and compares several machine learning methods to predict hotspots in Kalimantan. Using the most accurate machine learning model, each climate factor used as a predictor is analyzed for its sensitivity and feature importance. Some of the machine learning methods used include random forest, gradient boosting, Bayesian regression, and artificial neural networks. Meanwhile, several measures of sensitivity and feature importance used are variance-based, density-based, and distribution-based sensitivity indices, as well as permutation and Shapley feature importance. Evaluation of the ML model concluded that the Bayesian linear regression model outperformed other ML models, based on RMSE and explained variance score. Meanwhile, tree-based models, such as random forest and gradient boosting, are indicative of overfit. Based on the results of sensitivity analysis and feature importance, the number of dry days is the most important feature for the Bayesian linear regression model in predicting the number of hotspots in Kalimantan.
The rise of AI: a comprehensive research review
Authors: Rama Padmaja Chinimilli Venkata , Lakshminarayana Sadasivuni
Published: April 2024

Artificial Intelligence (AI) has emerged as a transformative force with far-reaching implications across various domains. This research review provides a comprehensive analysis of the rise of AI, examining its evolution, applications, ethical considerations, and future prospects. The study traces the historical development of AI, highlighting key milestones and technological advancements that have propelled its growth. It explores the wide-ranging applications of AI in sectors such as healthcare, finance, transportation, manufacturing, and entertainment, showcasing its impact on efficiency, decision-making, and user experiences. Ethical considerations surrounding AI, including bias, privacy, and societal implications, are thoroughly discussed. The transformative potential of AI in shaping society is examined, with insights into its effects on employment, education, governance, and societal challenges. Looking ahead, the review identifies emerging technologies and discusses challenges related to data privacy, security, and transparency. The research review concludes by emphasizing the importance of responsible and ethical development of AI, while underscoring the need for continued research and collaboration to fully harness its potential. This comprehensive review serves as a valuable resource for researchers, and practitioners seeking a holistic understanding of the rise of AI and its implications.
A multilingual semantic search chatbot framework
Authors: R Vinay , B U Thejas , Sharma H A Vibhav , G Shobha , Ghuli Poonam
Published: April 2024

Chatbots are conversational agents which interact with users and simulate a human interaction. Companies use chatbots on their customer-facing sites to enhance user experience by answering questions about their products and directing users to relevant pages on the site. Existing Chatbots which are used for this purpose give responses based on pre-defined FAQs only. In this paper, we propose a framework for a chatbot which combines two approaches - retrieval from a knowledge base consisting of question answer pairs, combined with a natural language search mechanism which can scan through the paragraphs of text information. A feedback-based knowledge base update is implemented which provides continuous improvement in user experience. The framework achieves a result of 81.73 percent answer matching on SQuAD 1.1 and 69.21 percent answer matching on SQuAD 2.0. The framework also performs well on languages such as Spanish (67.32 percent answer match), Russian (61.43 percent answer match), Arabic (51.63 percent answer match) etc. by means of zero shot learning.
Congestion and throughput optimization protocol for providing better quality of service and experience
Authors: VijayKumar Sathya , Thyagaraj Shiva Prakash
Published: April 2024

Multimedia traffic in Internet of Things applications is generated for various purposes and encompasses a wide range of multimedia data, including video streams, audio files, images, and sensor data. Network providers employ various strategies to handle multimedia traffic in IoT applications efficiently. But most of these methods have not considered optimizing the RTSP (Real-Time Streaming Protocol), RTP (Real-time Transport Protocol), and RTCP (Real-Time Control Protocol) to improve the throughput and QoS of the IoT applications. Hence, in this Congestion and Throughput Optimization Protocol (CTOP) work, we present a model which optimizes the RTSP, RTP, and RTCP protocol to improve the throughput and QoS. The CTOP model outperforms the Big Packet Protocol model in terms of average throughput, multimedia loss, delay, and energy consumption for both less and high-traffic scenarios. For less-level of traffic and high level of traffic, the CTOP model achieves a better average throughput, and average multimedia delay, reducing the average multimedia loss and average energy consumption in comparison to the existing BBP model. These results highlight the improved performance and efficiency of the CTOP model compared to the BBP model.
La escritura, una experiencia de paz. Transformación de la comprensión de paz a través de la producción escrita en niños de quinto grado
Authors: Carmona Idárraga María Isabel , Hernández Giraldo Luz Amparo
Published: April 2024

Las pruebas Saber se quedan cortas para valorar cómo escriben nuestros niños en Colombia, de allí la preocupación por investigar cómo la escritura transforma las comprensiones de paz de cuatro niños y tres niñas de quinto grado de básica primaria en una institución oficial urbana. Es una investigación de tipo cualitativo, con un diseño metodológico de estudio de caso múltiple. La recolección de la información se hizo a través de dos entrevistas semiestructuradas (una inicial y otra final), la aplicación de seis talleres sobre escritura y paz, instrumentos creados por las investigadoras, y los registros en diarios de campo. El análisis e interpretación de la información se desarrolló en cinco etapas: transcripción de la información, categorización natural y categorización axial, elaboración de redes semánticas, y confirmación de transformaciones. Los resultados demuestran el carácter epistémico y social de la escritura; se considera un hallazgo importante para la investigación el hecho de identificar la escritura como un asunto emotivo que le permite a los sujetos enunciarse y reconocerse a través de ella, y transforma la manera como los niños enfrentan conceptos que les tocan su vida cotidiana.
Subjetividades Políticas de Paz en Jóvenes de Colombia
Authors: Posada Escobar Jorge Jairo , Briceño Alvarado Patricia del Pilar , Corredor Romero Nudyered Consuelo , Munar Moreno Yudi Astrid , Rossi Rincón Jean Paul
Published: April 2024

El propósito general de este artículo apunta a la recopilación, sistematización y el análisis crítico de la producción de conocimiento en torno a la categoría subjetividades políticas de paz en jóvenes de Colombia. Como primera medida, se llevó a cabo una labor heurística en donde se buscaron y compilaron las diversas fuentes de información, obtenidas principalmente a partir del rastreo de escritos, pertenecientes a las dos últimas décadas, que trataran categorías subyacentes a la mencionada, como consecuencia del mínimo tratamiento que ésta ha tenido.
Cuestionamientos a la sociedad moderna y criterios contextuales para una discusión de los principios de la educación actual
Authors: Torres Rojas Emilio
Published: April 2024

El presente artículo describe las bases y cuestionamientos a la sociedad moderna, discutiendo dimensiones clave que estuvieron en la base de su despliegue y crisis. Constructos que parecían tan firmes originalmente, se encuentran hoy en una encrucijada para responder a la emergencia de nuevos procesos tornando cuestionables los logros alcanzados desde el siglo XVIII, marcando de incertidumbre y confusión la acción individual y colectiva. La aceleración del cambio, la complejidad de una sociedad diferenciada global y los cuestionamientos a la razón como fundamento de las estructuras modernas de convivencia, han generado crisis en la mayor parte de las instituciones e incertidumbre en las personas. En ese marco se aprecia desesperanza, pero también oportunidades para la educación que puede formular alternativas de discusión para ampliar las posibilidades transformación humana. Se proponen siete criterios para resituar contextualmente el entorno social de lo educativo y discutir en el nuevo escenario los ideales ilustrados.
Desarrollo humano en las localidades de Bogotá y su relación con las estructuras familiares
Authors: Niño Muñoz Diana Patricia , Díaz López Erika , Ricaurte Parrado Beatriz , Villalobos Arango Elbers
Published: April 2024

La familia es una institución que influye en su entorno mejorando la calidad de vida de sus integrantes y de la sociedad, sin embargo, han surgido diferentes estructuras familiares. El objeto del presente artículo de investigación es esclarecer si la estructura familiar es una condición necesaria para obtener una mayor calidad de vida en las localidades de la ciudad de Bogotá; específicamente entre los años 2011 y 2014. Para ello, se llevó a cabo un análisis comparativo de semejanzas y diferencias propuesto por Ragin (2007), y se realizó un análisis georreferenciado, para identificar posibles patrones. Los resultados evidencian que la evolución de las estructuras familiares no es un factor suficiente para explicar el desarrollo socioeconómico en Bogotá.
Programmable Analogue Drawing Machines, 1952–2023
Authors: Tait Jack
Published: April 2024

The author discusses his work creating programmable, generative analogue drawing machines over six decades in the context of the constructivist tradition and influenced by the Bauhaus German art school and the subsequent art, science, and technology movement. During the first three decades he developed a variety of machines and from 1990 followed a more analytical approach focusing on randomness, chaos, and subjectivity in art. This progressed to the author’s PhD research program wherein he investigated innovative analogue programming systems that employed direct current motors, linkages, and cranks together with programmers, actuating motors for a variety of timed pulses. These enabled variables such as pen-lift and rotation, forward/reverse pen action, light drawing, sine waves, turntable and drum machines, and versions of X:Y plotters.
A new species of Pristerophora Harold, 1869 (Coleoptera: Scarabaeidae: Melolonthinae) from Chile
Authors: E. JOSÉ MONDACA
Published: April 2024

A new species of Macrodactylini (Coleoptera: Scarabaeidae: Melolonthinae), Pristerophora rothmanni new species, is described and illustrated based on male and female specimens collected in southern Chile. Natural history, habitat, and distributional data are given. An identification key for Pristerophora species is included.
Rapidly Developing a Community- and Evidence-Based Heat Action Plan
Authors: Uejio Christopher K. , Gilbert Jane , Ahn Yoonjung , Martella Ludovica , Hu Leiqiu , Marturano Julia
Published: April 2024

Extreme heat contributes to 8000–12 000 excess U.S. deaths per year. Partly due to increasing summer temperatures and a renewed focus on environmental justice, local governments started new initiatives to manage and adapt to extreme heat. For example, Miami-Dade County, Florida, United States, appointed Jane Gilbert as the world’s first Chief Heat Officer. This manuscript summarizes Miami-Dade County’s preliminary efforts to build local evidence, engage the community, and rapidly respond to extreme heat. The manuscript’s goal is to expedite the translation of existing tools into mainstream extreme heat, health, and equity planning. The study generated local evidence to identify the places and periods of time with elevated heat-related illness using a statistical vulnerability and time series analysis, respectively. The places with the highest severe heat-related illness rates had hotter land surface temperatures and/or higher proportions of people who were outdoor workers, Indigenous, living in poverty or mobile homes, and households with children. “Everyday” summer conditions instead of rare heatwaves increase the risk of a heat-related death. The Chief Heat Officer convened workshops that engaged 298 unique community members on six cross-sectoral heat topics. Key recommendations included increasing multisectoral heat monitoring and risk communication, building more affordable housing, preserving and expanding greenspace, and creating heat resilience hubs. The activities culminated in a Heat Action Plan, which was completed in less than two years from the receipt of project funding.
The Eighteenth Constitutional Amendment and the Baloch National Question in Pakistan
Authors: Wani Shakoor Ahmad
Published: April 2024

The passage of the eighteenth amendment bill in 2010 represented a critical milestone in Pakistan’s constitutional history. It sought to better manage the perennial federal-provincial tensions by restructuring the country’s constitutional framework to assuage the grievances of the ethno-regional movements opposed to the centralised state system, especially in Balochistan, where Pakistan’s territorial integrity faces its toughest challenge. Islamabad’s inflexibility in accommodating ethnic dissidence through various institutional measures has exacerbated ethnic tensions and hardened nationalist sentiments. The eighteenth amendment aimed to reverse deformations introduced during dictatorships and promote a more federal polity. More than a decade has passed since the introduction of the bill, yet the question lingers: Did the amendment achieve its intended goal of mitigating the ethnic conflict in Balochistan? This article scrutinises the current situation in Balochistan and offers a critically oriented analysis of the amendment’s impact on the province’s security scenario. It contends that the amendment fell short of its objectives because it remained silent on issues of critical import to the Baloch and failed to address the underlying issues fuelling the conflict.
The COVID-19 Border Closure and Local Economic Development in a South African Border Town
Authors: Masiloane Mary , Marais Lochner
Published: April 2024

Border towns benefit from cross-border movement of goods, services and people. Many suffered setbacks when governments responded to the COVID-19 pandemic by closing borders. We investigated how the lockdown regulations affected the economy of Ladybrand, a small South African town near Lesotho. We found that local planning was not taking advantage of the benefits of a border town economy and was unprepared for border closure. Retail outlets were the hardest hit, followed by the transport, services and health sectors. Dilapidated infrastructure and poor service delivery made it difficult for the town to cope with the effects of the border closure.
Oral–Gut–Estrobolome Axis May Exert a Selective Impact on Oral Cancer
Authors: Tatullo M. , Nor J. , Orrù G. , Piattelli A. , Cascardi E. , Spagnuolo G.
Published: April 2024

A subset of bacterial species that holds genes encoding for β-glucuronidase and β-galactosidase, enzymes involved in the metabolism of conjugated estrogens, is called the “estrobolome.” There is an emerging interest embracing this concept, as it may exert a selective impact on a number of pathologies, including oral cancer. Although the estrobolome bacteria are typically part of the gut microbiota, recent experimental pieces of evidence have suggested a crosstalk among oral and gut microbiota. In fact, several oral bacterial species are well represented also in the gut microbiota, and these microbes can effectively induce the estrobolome activation. The main pathways used for activating the estrobolome are based on the induction of the expression patterns for 2 bacterial enzymes: β-glucuronidase and aromatase, both involved in the increase of estrogen released in the bloodstream and consequently in the salivary compartment. Mechanistically, high estrogen availability in saliva is responsible for an increase in oral cancer risk for different reasons: briefly, 1) estrogens directly exert biological and metabolic effects on oral mucosa cells; 2) they can modulate the pathological profile of some bacteria, somewhere associated with neoplastic processes (i.e., Fusobacterium spp., Parvimonas ssp.); and 3) some oral bacteria are able to convert estrogens into carcinogenic metabolites, such as 4-hydroxyestrone and 16α-hydroxyestrone (16α-OHE), and can also promote local and systemic inflammation. Nowadays, only a small number of scientific studies have taken into consideration the potential correlations among oral dysbiosis, alterations of the gut estrobolome, and some hormone-dependent cancers: this lack of attention on such a promising topic could be a bias affecting the full understanding of the pathogenesis of several estrogen-related oral pathologies. In our article, we have speculated on the activity of an oral–gut–estrobolome axis, capable of synergizing these 2 important microbiotas, shedding light on a pilot hypothesis requiring further research.
Past Imperfect or Present Perfect? How Dynamic Ranks Influence Consumer Perceptions
Authors: Pandey Arpita , Tripathi Sanjeev , Jain Shailendra Pratap
Published: April 2024

While ranked lists are ubiquitous, research on how consumers interpret changes in the rank of an entity is limited. Across seven studies (including a study with web data and a Google AdWords field experiment), this investigation shows that consumers reward a rise in rank and penalize a decline in rank, and that psychological momentum associated with the rank change information underlies these effects. Further, rewarding a rise and penalizing a fall are moderated by consumers’ perception of the reason for the rank change, the nature of the entity, and the nature of the ranked list. The impact of changing rank is attenuated when the rank change is attributed to other entities on the list, when entities are considered nonmalleable, or when the list is updated more frequently. The investigation also identifies a specific case in which consumers do not extrapolate the direction of a change in rank into the future. In addition to contributing to theory, this research provides actionable insights and demonstrates practical ways in which managers can communicate dynamic ranks to enhance the benefit of an improvement in rank or attenuate the penalty from a decline.
Finding the Police Before the Police Find Them? Investigating How and Why Motorists Use Facebook for Knowledge of Roadside Drug Testing Locations
Authors: Mills Laura , Freeman James , Truelove Verity
Published: April 2024

Facebook groups and pages exist that expose the locations of roadside drug testing, potentially undermining police enforcement and enabling punishment avoidance. This study aimed to understand how and why these sites are used, with a focus on Queensland motorists who reported using illicit drugs and/or medical cannabis and used Facebook police location communities. Interviews with 30 participants were conducted. A thematic analysis revealed that participants used police location communities to avoid receiving a charge for driving under the influence of drugs. Upon observation of a relevant roadside drug-testing location on police location communities, participants reported (a) delaying their driving and/or (b) circumventing the operation. Avoidance of roadside drug-testing locations appeared driven by the perception that laws for driving under the influence of drugs were unfair and that a charge for driving under the influence of drugs would negatively impact their life. The findings provide important knowledge regarding police location communities and have implications for how roadside drug testing could be most effectively operated.
People Reject Free Money and Cheap Deals Because They Infer Phantom Costs
Authors: Vonasch Andrew J. , Mofradidoost Reyhane , Gray Kurt
Published: April 2024

If money is good, then shouldn’t more money always be better? Perhaps not. Traditional economic theories suggest that money is an ever-increasing incentivizer. If someone will accept a job for US$20/hr, they should be more likely to accept the same job for US$30/hr and especially for US$250/hr. However, 10 preregistered, high-powered studies ( N = 4,205, in the United States and Iran) reveal how increasing incentives can backfire. Overly generous offers lead people to infer “phantom costs” that make them less likely to accept high job wages, cheap plane fares, and free money. We present a theory for understanding when and why people imagine these hidden drawbacks and show how phantom costs drive judgments, impact behavior, and intersect with individual differences. Phantom costs change how we should think about “economic rationality.” Economic exchanges are not merely about money, but instead are social interactions between people trying to perceive (and deceive) each others’ minds.
Discrimination between benign and malignant gallbladder lesions on enhanced CT imaging using radiomics
Authors: Zhuang Ying-ying , Feng Yun , Kong Dan , Guo Li-li
Published: April 2024

Background

Gallbladder cancer is a rare but aggressive malignancy that is often diagnosed at an advanced stage and is associated with poor outcomes.

Purpose

To develop a radiomics model to discriminate between benign and malignant gallbladder lesions using enhanced computed tomography (CT) imaging.

Material and Methods

All patients had a preoperative contrast-enhanced CT scan, which was independently analyzed by two radiologists. Regions of interest were manually delineated on portal venous phase images, and radiomics features were extracted. Feature selection was performed using mRMR and LASSO methods. The patients were randomly divided into training and test groups at a ratio of 7:3. Clinical and radiomics parameters were identified in the training group, three models were constructed, and the models’ prediction accuracy and ability were evaluated using AUC and calibration curves.

Results

In the training group, the AUCs of the clinical model and radiomics model were 0.914 and 0.968, and that of the nomogram model was 0.980, respectively. There were statistically significant differences in diagnostic accuracy between nomograms and radiomics features ( P <0.05). There was no significant difference in diagnostic accuracy between the nomograms and clinical features ( P >0.05) or between the clinical features and radiomics features ( P >0.05). In the testing group, the AUC of the clinical model and radiomics model were 0.904 and 0.941, and that of the nomogram model was 0.948, respectively. There was no significant difference in diagnostic accuracy between the three groups ( P >0.05).

Conclusion

It was suggested that radiomics analysis using enhanced CT imaging can effectively discriminate between benign and malignant gallbladder lesions.
Influence of Non-Melting Waste Plastics on Volumetric Properties and Performance of Asphalt Mixtures
Authors: Revelli Venkatsushanth , Ali Ayman , Mehta Yusuf , Cox Ben C. , Casillas Sadie
Published: April 2024

The main objective of the study is to evaluate the impact of using polystyrene (PS) and polyethylene terephthalate (PET) plastics as an additive in asphalt mixtures. For this purpose, volumetric modification, moisture susceptibility along with performance variation at high, intermediate, and low temperature conditions were evaluated. Initially plastics were subjected to calorimeter analysis for assessing their melting characterization. Both PS and PET are included as dry mix additives individually at dosage levels of 3%, 6%, and 9% by weight of asphalt binder. Further, the changes in thermal properties of plastics occurring during mixture preparation were correlated to better understand the volumetric modification. PS, owing to its glass transition and partial amorphous nature, exhibited minimum deviation (<1%) from design air voids (4 ± 0.5%). PET was observed to increase the volumes of voids in mineral aggregate (VMA) and air void, owing to its crystalline nature. As regards performance, PS and PET modification enhanced the moisture resistance by 1.05 to 1.11 times the control mixture. The rutting tolerance index ( RTindex) value increased for all plastic modified mixtures from the indirect tensile asphalt rutting test (IDEAL RT) performed at 58°C. However, the intermediate temperature cracking tolerance index ( CTindex) at 19°C conveyed the high embrittled nature from plastic modification making the mixtures more susceptible to cracking. From the Gf versus l75 /m75 interaction diagram, it was conveyed that although addition of plastics improves the fracture toughness of asphalt mixtures, the ductile nature of mixtures is compromised. Also, PS and PET modification could not improve the ability of asphalt mixtures to resist thermal cracking, evaluated at −18°C.
Trolling the Leviathan: How the use of social media by democratic organizations engenders monsters
Authors: Pasquier Vincent , Barros Marcos , Daudigeos Thibault
Published: April 2024

The proliferation of trolls may be one of the main reasons why democratic organizations fail to use social media to renew. The literature predominantly assimilates these trolls to psychologically deviant individuals. This article questions this individual-centric approach by suggesting that trolls may well be socially constructed organizational monsters. To investigate this phenomenon, for 2 years, we studied the interactions on a Facebook group between the leaders and members of a trade union. We identified three bi-directional effects at the heart of what we call the monstrification process: discording, disordering, and disgusting effects. The paper contributes to the troll and organizational monster literature by evidencing the four-stage process through which trolls are organizationally constructed as deviant online participants. Our work also adds to the democratic organization literature by metaphorically underlining actors’ emotional and moral distress caused by the dysfunctional encounter of offline and online democracy.
Trial sequential analysis: A simple guide for judging the conclusiveness of the effect
Authors: Mheissen Samer
Published: April 2024

Meta-analysis is a statistical method used in systematic reviews to provide a quantitative estimate of the effect. However, including very few studies and participants may increase the risk of spurious findings. Trial sequential analysis (TSA) has been introduced to enhance the robustness of meta-analysis. TSA is a cumulative meta-analysis method that weighs type I and II errors while estimating the effect. The application of TSA can lead to a more accurate estimation of the clinical effectiveness of the intervention. The aim of the present paper was to introduce the TSA to orthodontic clinicians and researchers using continuous data from an orthodontic systematic review.
Agency theory and social entrepreneurship: An axe that needs sharpening
Authors: Muldoon Jeffrey , Skorodziyevskiy Vitaliy , Gould Anthony M. , Joullié Jean-Etienne
Published: April 2024

Social entrepreneurship is a recent strategy for addressing public policy concerns that have traditionally been viewed as falling within the State's ambit. This article exposes the inadequacy of agency theory for interpreting how parties coexist within a multi-stakeholder service delivery configuration under the rubric of social entrepreneurship. Using the case of Teach for America, the article explores the criticisms that traditionally trained teachers direct towards the organization's members but does not take a side on whether these criticisms are justified. Rather, it prosecutes the case that, absent a frame of reference (e.g., appropriately adapted agency theory) for exposing the interests of disparate stakeholders to a social entrepreneurship venture, misaligned interests manifest as ill-founded mutual critique, often as argumentum ad hominem denunciations.
The benefit, harm, and complication of humor in social work: A qualitative inquiry
Authors: Ocean Mia , Gordon Donette A
Published: April 2024

The use of humor in social work is an underrecognized and underexplored area of practice despite its potential to heal, harm, and complicate communication. To date, very minimal scholarship has been published on humor in social work. Therefore, this qualitative study sought to examine how social workers use, perceive, and experience humor. Data were gathered from 22 participants who identified as social workers via an online survey. Data also included learning artifacts (e.g., discussion board posts, humor therapy treatment plans) from 19 graduate-level social work students who completed a humor in social work course in the northeast region of the United States. Both datasets were analyzed thematically.

Findings

Participants perceived social workers as using humor in clearly distinct ways, as a tool to promote generative growth, and as a weapon to harm already marginalized populations. In total, participant responses highlight the complexities of humor, including its subjective and dynamic nature, which can lead to multiple and sometimes conflicting experiences.

Applications

The findings suggest that social workers view humor positively, yet they engage in its use without adequate training, strategy, and reflection, sometimes violating professional ethics. Results further indicate that social workers will continue to employ humor in their professional work to the benefit and detriment of those around them. To support reflective and informed practice, additional research is needed on the use and misuse of humor in social work.
Evaluation of the low-velocity impact response of high-performance multi-axial warp-knitted flexible composites
Authors: Li Bing , Zhao Ziyu , Ma Pibo
Published: April 2024

This article aims to investigate the dynamic behavior of high-performance multi-axial warp-knitted flexible composite materials under low-velocity impact tests through experiments and numerical simulations. In this paper, high-performance multi-axial warp-knitted flexible composites were prepared. Three different preparation processes, 175°C-5 min, 185°C-10 min, and 195°C-15 min, were designed for the multi-axial warp-knitted flexible composites. Studied the impact response of different preparation processes, initial impact energy, and punch shapes and diameters on materials. The results showed that the flexible composites prepared by various processes exhibit the same impact response curves in the impact resistance process, while the damage morphology and failure modes of the samples are different. Different initial impact energies caused multiple failure modes in the samples. The material showed penetration damage at high energy impacts and permanent depression damage at low energies. For different punch shapes, the impact resistance of materials to hemispherical punches is better than that of cylindrical punches. Numerical simulations were carried out using the finite element software ABAQUS. The custom material subroutine (VUMAT) based on the Hashin damage criterion model was implemented in the finite element program. The experimental and numerical simulation results agree regarding impact response characteristics. This paper analyzes the composite damage shapes, crack extensions caused by low-velocity impact tests and finite element simulation on multi-axial warp-knitted flexible composites. It provides a valuable reference for failure and structural optimization of multi-axial warp-knitted flexible composites for architectural applications.