bluuebunny/crossref_metadata_2025 huggingface dataset:
Customer Loyalty in Industry 4.0: Perspectives from the Hospitality Supply Chain
Authors: Anderson Matthew
Published: January 2025

This study explores the intricate relationship between Industry 4.0 technologies and customer loyalty in the hospitality sector. As digital transformation continues to shape consumer behavior, understanding how these advancements impact customer loyalty has become increasingly critical for businesses aiming to thrive in a competitive landscape. Through qualitative research involving 32 participants from various segments of the hospitality supply chain, this study identifies key themes that influence customer loyalty, including personalization, technological efficiency, human-centric approaches, trust, transparency, and digital engagement. The findings reveal that personalization is essential in creating tailored experiences that foster emotional connections between customers and brands. Additionally, while technology significantly enhances operational efficiency and streamlines customer interactions, maintaining a human touch is crucial for genuine customer engagement. Trust and transparency emerged as foundational elements, with customers prioritizing data security and ethical practices in their relationships with brands. Moreover, the role of digital channels in fostering customer engagement and community was highlighted, emphasizing the need for businesses to adapt to the digital landscape. The study concludes that a balanced approach, integrating technological advancements with personalized service and ethical considerations, is vital for cultivating customer loyalty in the hospitality industry. This research contributes to the existing literature by providing insights into the evolving dynamics of customer loyalty in an increasingly digital world and offers practical implications for hospitality businesses seeking to enhance customer retention.
Racial Discrimination as a Traumatic Bedrock of Healthcare Avoidance: A Pathway Through Healthcare Institutional Betrayal and Mistrust
Authors: Rastegar Pedram , Cai L , Langhinrichsen-Rohling Jennifer
Published: January 2025

Objectives: Experiences of racial discrimination within the healthcare system are potentially traumatic events (PTEs) that have been associated with lowered perceived trust in healthcare providers (Hall et al., 2021), ongoing symptoms of PTSD and depression (Tamaian et al., 2024), and anticipated healthcare avoidance (Holder-Dixon et al., 2022). Based on the BITTEN trauma impact model, we test a pathway such that greater past healthcare discrimination would be associated with anticipated future healthcare avoidance among BIPOC college students. We posit that this direct relationship will be sequentially mediated by healthcare institutional betrayal (HIB) during one’s worst healthcare event and subsequent reduced trust in healthcare.
Methods: Our model was tested in a subsample of undergraduate students, all of whom self-identified with at least one minoritized racial or ethnic identity (n = 472). Participants reported on their past experiences with racial discrimination in healthcare. Each then chose and described their worst and/or most traumatic previous healthcare experience. Subsequently, they indicated if this experience included acts of HIB and/or led to healthcare mistrust. Finally, they reported on the degree to which they anticipated engaging in future healthcare avoidance.
Results: Our model explained 31% of the variance in anticipated healthcare avoidance. As hypothesized via BITTEN, greater HIB during one’s worst or most traumatic healthcare experience and resulting mistrust in healthcare sequentially mediated the relationship between past experiences of healthcare racial discrimination and anticipated future healthcare avoidance. However, a direct relationship between racial discrimination in healthcare and anticipated healthcare avoidance was retained.
Conclusion: Racial discrimination is a potentially traumatic experience associated with deleterious health outcomes. Current results suggest that healthcare discrimination may drive BIPOC college students’ future healthcare avoidance both directly and through experiencing increased healthcare institutional betrayal during one’s worst healthcare experiences and resultant mistrust in healthcare. Due to the crucial role both discrimination and HIB experiences may play in healthcare outcomes, greater organizational adoption of anti-racist trauma-informed healthcare and the enacting of deliberate system-level repair strategies, post discrimination and/or HIB is critical. Understanding the interplay of racial discrimination, HIB, and healthcare mistrust is also likely to help us address and repair system-level factors leading to anticipated healthcare avoidance behavior among BIPOC emerging adults.
Development of the Crossmatch Test in Kidney Transplantation up to the Virtual Level
Authors: Katalinić Nataša , Crnic Marcetic Tajana , Trobonjača Zlatko , Barin-Turica Franco , Balen Sanja
Published: January 2025

The Human Leukocyte Antigens (HLA) system forms the central part of the immune system and is crucial in the recognition and elimination of „non-self“ antigens. While this role of the HLA system is essential in the effective defense of the organism against pathogens, it is undesirable in organ and tissue transplantation because it enables the recognition of mismatched HLA molecules of the donor as foreign and stimulates the graft rejection reaction. Organ transplantation involves the introduction of antigens that are more or less mismatched to the recipient, so in order to achieve the best possible match in the HLA system between the recipient and the donor, a whole series of immunogenetic tests is performed, including cross-matching (XM). If performed before kidney transplantation, it represent the final in vitro test to rule out the presence of donor-specific antibodies, which may cause graft rejection, and which may not have been detected by earlier serum screening. The beginning of XM was marked by the complement-dependent cytotoxicity (CDC) method developed by Terasaki and colleagues in 1964. Later, as a result of advances in technology and the need for methods that overcome the limitations of CDC, flow cytometry and Luminex XM assays were developed. The introduction of solid-phase technology in the early 2000s brought a new dimension to the detection of low-level HLA antibodies and the determination of their specificities, which enabled the development and implementation of the virtual XM test (vXM). It is an in silico test that assesses the immunological match between the recipient and the organ donor based on the analysis of the specificity of the antibodies present in the recipient's serum and the HLA typing of the organ donor. Each method has its own advantages and limitations which are described and which need to be taken into account considering their significant impact on clinical application in kidney transplantation.
Natural Products with Therapeutic Action in Diabetes: A Coadjuvant Alternative Against COVID-19?
Authors: Fregoso-Aguilar Tomas Alejandro , Morales-González Angél , Madrigal-Santillán Eduardo O. , Melo Luis F. Garcia , Morales-González José A.
Published: January 2025

From the time that, in March, 2020, the World Health Organization (WHO) declared the acute respiratory syndrome caused by Coronavirus-2 (SARS-CoV-2), better known as COVID-19, a pandemic, an effective treatment has been sought, without achieving this at 100%. SARS-CoV-2 mainly affects the respiratory airways, but it is also known to damage various organs and systems, giving rise to a slight symptomatology up to, even, death in some cases. Unfortunately, high comorbility has also been found, which is associated with chronic-degenerative diseases that raises the risk of mortality in patients. In this review, a description is made of some common factors in patients affected by COVID-19 with a diagnosis of prior diabetes. In this regard, the therapeutic effects are described of some plant species and their secondary metabolites that, in some previous studies, have demonstrated, to exert certain effects in patients diagnosed with diabetes, emphasizing that, while different vaccines are now available to meet the challenge of the pandemic, the information collected in this work could be useful in the search for alternative clinical therapies based on Traditional Medicine and on the chemistry of some plant-derived secondary metabolites in patients affected by COVID-19 and diabetes.
Deciphering the Role of Phytohormones Regulated by the Scion in the Adventitious Root Development of Grafted Watermelon Seedlings
Authors: Song Ce , Huang Yi , Wu Chenchen , Tian Baoming , Shi Xuanjie , Mi Guoquan , Jing Yancai , Tang Yanling , Wang Zuojing , Niu Lili , Wang Tengqi , Shi Gongyao , Ma Kai
Published: January 2025

Adventitious roots (ARs) are crucial for grafted seedlings, playing vital roles in nutrient absorption, stress resistance, and grafting efficacy. However, how scions regulate endogenous hormones to influence AR formation remains poorly understood. In this study, we constructed watermelon seedlings (WP) using “HXX” as the scion and “Tie Zhen No. 3” as the rootstock. Removing scion cotyledons (WP-1) significantly promoted AR development, while removing true leaves (WP-2) had minimal effect. Simultaneous removal of both (WP-3) increased endogenous levels of IAA (Indole-3-Acetic Acid), abscisic acid (ABA), and jasmonic acid (JA). Transcriptome sequencing revealed that differentially expressed genes (DEGs) are enriched in various hormone signaling pathways. On the fourth day, when the number of differential genes was the highest, the DEGs significantly expressed in all three treatment groups were enriched in the activation signaling pathways and responses of JA, auxin, ethylene, and cytokinins. Transcription factors such as bHLH, ERF, MYB, and NAC were significantly expressed during the development of ARs, playing a key regulatory role. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis identified 82 DEGs across five hormone signal transduction pathways. Weighted gene co-expression network analysis (WGCNA) identified modules positively correlated with AR hormones, highlighting hub genes such as ethylene transcription factors (CRF4, ABR1, ERF054, ERF098), auxin response factors (SAUR21, SAUR32), and other regulators (CSA, HSP, bHLH93, ZAT5, ZAT13, NAC, MYB, C3H). These findings provide molecular insights into how scions regulate AR development through hormones, offering a foundation for improving watermelon grafting practices.
Integrated Network Pharmacology and Metabolomics to Reveal the Mechanisms of the Combined Intervention of Ligustrazine and Sinomenine in CCI-Induced Neuropathic Pain Rats
Authors: Li Tao , Wang Zhiguo , Yuan Zhaoyue , Zhao Xiaoliang , Zhang Yan , Jiao Yue , Liu Yang , Gao Chang , Zhang Jidan , Ma Yanyan
Published: January 2025

Neuropathic pain (NP) is a chronic pain resulting from injury or dysfunction of the nerves or spinal cord. Previous studies have shown that the combination of ligustrazine (LGZ) and sinomenine (SIN) exerts a synergistic antinociceptive effect in peripheral and central NP models. This study aims to evaluate the pharmacodynamic characteristics of LGZ and SIN in a chronic constriction injury (CCI)-induced NP models in rats, and to analyze its molecular regulatory mechanisms from the perspectives of network pharmacology and metabolomics. Firstly, a comprehensive analgesic evaluation including the mechanical withdrawal threshold test, cold allodynia test, and the incapacitance test was performed after 1, 2 and 3 days of intervention. The sciatic nerve histopathological changes were observed, and inflammatory factor analysis were conducted. Secondly, the pain-related targets of LGZ and SIN were systematically analyzed based on network pharmacology. The differential metabolites in the plasma and cerebrospinal fluid (CSF) were screened, and their content were quantified using LC-MS metabolomics technology. Finally, the key metabolic pathways with crucial role of LGZ and SIN in treating NP was identified from a joint analysis of the potential targets and the differential metabolites. The combination of LGZ and SIN significantly alleviated pain-like behaviors of CCI rats time- and dose-dependently, and the therapeutic effect was notably superior to that of LGZ or SIN alone. The combination of LGZ and SIN could improve pathological damage to the sciatic nerve and regulate the levels of inflammatory cytokine. Network pharmacology analysis revealed that LGZ and SIN have 6 shared pain-related targets, while LGZ have 16 distinct pain-related targets and SIN have 52 distinct pain-related targets. The metabolomics analyses revealed that 54 differential metabolites in plasma and 17 differential metabolites in CSF were associated with the combined intervention of LGZ and SIN. Finally, through integrated analysis of the core targets and differential metabolites, tyrosine metabolism, phenylalanine metabolism, and arginine and proline metabolism were identified as potential key metabolic pathways underlying the therapeutic effects of LGZ and SIN in CCI treatment. This study provides an integrated approach to elucidate the molecular mechanisms underlying the combined use of LGZ and SIN in the treatment of NP. Furthermore, the findings offer new experimental evidence to support the clinical application of LGZ and SIN in the treatment of NP.
HCC and Immunotherapy: The Potential Predictive Role of Gut Microbiota and Future Therapeutic Strategies
Authors: Laface Carmelo , Lauricella Eleonora , Ranieri Girolamo , Ambrogio Francesca , Maselli Felicia Maria , Parlagreco Elena , Bernardi Giulia , Fea Elena , Numico Gianmauro
Published: January 2025

During the last decade, a new therapeutic revolution has involved the management of hepatocellular carcinoma (HCC). This is made possible thanks to the documented efficacy of immunotherapy for this disease. In addition, new evidence demonstrated the role of the gut-liver axis and gut microbiota in host homeostasis, tumor development, and response to therapies. In particular, intestinal dysbiosis can alter the tumor microenvironment leading to the activation of intracellular signalling pathways that promote carcinogenesis. The composition of gut microbiota proved to influence the immune checkpoint inhibitors (ICIs) efficacy and drug toxicities. Therefore, this review aims to deepen knowledge about the immunomodulatory role of gut microbiota and its possible employment as diagnostic and predictive biomarkers in diagnosis and response to immunotherapy of HCC, respectively.
“SIPRODIV”: SISTEM PRODUKSI HORTIKULTURA BERBASIS DRIP FERTIGASI GRAVITASI KELOMPOK WANITA TANI (KWT) KERABAT DI KELURAHAN TAMALANREA INDAH
Authors: Astrada Muhammad Fachri Rama Dwi , Irsan Muhammad , Adam Ahmad Fatih , Nurannisa Sitti , Meyrliani Meyrliani , Bintoyan Winda , Feriawan Andi , Pata’dungan Lianan , Shadiq Syarifah Askina , Winanda Erdy , Nanda Rezki Ayu , Sampepadang Novianti , Ihsan Muhammad Takbiratul , Aswin Rifdah Nafilah , Rifai Ahmad , Dermawan Rahmansyah
Published: January 2025

SIPRODIV memanfaatkan ketinggian sumber air sebagai sumber tenaga (energi) irigasi dan pemupukan yang efisien. Pengabdian ini menggunakan metode pendekatan Asset-Based Community Development (ABCD) dan untuk evaluasi keberhasilan program menggunakan Participatory Action Research (PAR). Kegiatan pemberdayaan dilakukan melalui sosialisasi, pelatihan, dan pendampingan intensif. Kegiatan pengabdian masyarakat ini bertujuan untuk meningkatkan kemampuan dan kemandirian Kelompok Wanita Tani (KWT) Kerabat di kebun sayuran melalui penerapan teknologi pertanian modern berbasis drip fertigasi gravitasi. Hasil pelaksanaan program menunjukkan peningkatan pemahaman dan keterampilan anggota KWT dalam instalasi dan pengoperasian sistem drip fertigasi gravitasi, budidaya hortikultura, serta pengolahan pascapanen dan pemasaran produk. Terbetuknya sebelas bedengan sayuran yang berisi tanaman hortikultura seperti cabai, terong, pakcoy, bayam, dan kangkung. Anggota KWT mampu menjadi paham budidaya hottikultura dan mampu memahami system tentang SIPRODIV. Evaluasi menunjukkan adanya peningkatan pemahaman sebesar 50,03% terkait sistem ini.
ABSTRACT
SIPRODIV utilizes the height of water sources as a source of efficient irrigation and fertilization energy. This community service uses the Participatory Action Research (PAR) method and the Asset-Based Community Development (ABCD) approach. Empowerment activities are carried out through socialization, training, and intensive mentoring. This study aims to improve the ability and independence of the Kerabat Women Farmers Group (KWT) in vegetable gardens by applying modern agricultural technology based on gravity drip fertigation. The results of the program implementation showed an increase in the understanding and skills of KWT members in the installation and operation of the gravity drip fertigation system, horticulture cultivation, post-harvest processing, and product marketing. The formation of eleven vegetable beds containing horticultural plants such as chili, eggplant, pak choy, spinach, and water spinach. KWT members were able to understand horticulture cultivation and were able to understand the SIPRODIV system. The evaluation showed an increase in understanding of 50.03% regarding this system.
Keywords: Gravity drip fertigation, Women Farmers Group (KWT), Community empowerment.
PENINGKATAN PENGETAHUAN MASYARAKAT MELALUI DISEMINASI HASIL PENELITIAN TANAMAN AREN DI KABUPATEN MAROS
Authors: Sukri Hadija , Nur Imran Andi , Nirawati Nirawati , Laban Sartika , Lahasima Edwin Nussy
Published: January 2025

Salah satu strategi peningkatan pengetahuan petani adalah melalui diseminasi hasil  penelitian. Melalui diseminasi, semua hasil penelitian dapat sampai kepada masyarakat luas dan para petani secara khususnya petani aren sehingga memberikan wawasan yang mendalam kepada petani untuk dapat mengoptimalkan penggunaan sumber daya alam, peningkatan hasil panen, dan mengurangi resiko kerusakan lingkungan. Tujuan kegiatan pengabdian pada masyarakat ini adalah menyebarluaskan hasil penelitian yang berhubungan dengan tenaman aren untuk peningkatan pengetahuan dan keterampilan petani aren di Desa Bonto Manurung Kabupaten Maros. Metode yang digunakan dalam program pemberdayaan wilayah di Desa Bonto Manurung, Kabupaten Maros ini adalah metode partisipatif yang akan bertujuan secara inklusif melibatkan semua pihak mitra pemerintah dan mitra sasaran. Diseminasi hasil penelitian melalui kuliah umum dan seminar memberikan akses kepada petani aren terhadap pengetahuan yang lebih dalam tentang budidaya aren. Diseminasi harus diikuti dengan pelatihan berkelanjutan agar dapat meningkatkan keterampilan petani, berdampak positif pada ekonomi lokal, dan mendukung konservasi lingkungan.
ABSTRACT
One of the strategies to increase farmers' knowledge is through the dissemination of research results. Through dissemination, all research results can reach the wider community and farmers in particular palm farmers to provide deep insight to farmers to be able to optimize the use of natural resources, increase yields, and reduce the risk of environmental damage. The purpose of this community service activity is to disseminate the research results related to palm trees to increase the knowledge and skills of palm farmers in Bonto Manurung Village, Maros Regency. The method used in this regional empowerment program in Bonto Manurung Village, Maros Regency, is a participatory method that will aim to involve all government partners and target partners inclusively. Dissemination of research results through public lectures and seminars gives access to palm farmers to deeper knowledge of palm cultivation. Dissemination should be followed by continuous training to improve farmers' skills, positively impact the local economy, and support environmental conservation.
Keywords: Dissemination, research, aren, superior crops, aren cultivation.
PRODUK SURABI IKAN: INOVASI JAJANAN SEHAT DENGAN NILAI GIZI TINGGI UNTUK ANAK-ANAK DI PULAU SAMATELLU LOMPO, PANGKAJENE KEPULAUAN
Authors: Tawali Abu Bakar , Mahendradatta Meta , Karim Muhammad Yusri , Muhpidah Muhpidah , Angriani Lisa , Nabilah Azzahra , Sulkifli Ela , Nadhifa Dwi Ghina
Published: January 2025

Stunting merupakan masalah kesehatan di Kabupaten Pangkajene dan Kepulauan (Pangkep), Sulawesi Selatan, dengan angka prevalensi mencapai 30%. Salah satu upaya untuk mengurangi angka stunting di daerah ini adalah melalui inovasi pangan berbasis sumber daya lokal, khususnya ikan. Artikel ini membahas program pengolahan ikan menjadi surabi, jajanan tradisional yang diperkaya dengan nutrisi, untuk meningkatkan asupan gizi anak-anak di Pulau Samatellu Lompo. Program ini mencakup survei potensi bahan baku, persiapan teknologi pengolahan, pelatihan pembuatan surabi ikan, serta pendampingan dalam proses komersialisasi produk. Hasil dari program ini menunjukkan adanya peningkatan pengetahuan peserta tentang pentingnya konsumsi ikan dan keterampilan dalam pengolahan surabi. Evaluasi pre-test dan post-test menunjukkan peningkatan yang signifikan dalam pemahaman peserta terkait pengolahan pangan bergizi. Melalui kegiatan ini, diharapkan produk surabi ikan dapat membantu meningkatkan asupan gizi anak-anak, sekaligus membuka peluang ekonomi bagi masyarakat setempat. Surabi ikan diposisikan sebagai solusi inovatif untuk mengatasi masalah stunting di daerah kepulauan ini, dengan potensi komersialisasi yang besar.
ABSTRACT
Stunting is a health issue in Pangkajene and Kepulauan (Pangkep) Regency, South Sulawesi, with a prevalence rate reaching 30%. One of the efforts to reduce the stunting rate in this area is through food innovation based on local resources, particularly fish. This article discusses a program that processes fish into surabi, a traditional snack enriched with nutrition, to improve children's nutritional intake on Samatellu Lompo Island. The program involves a survey of raw material potential, preparation of processing technology, training on surabi fish production, and assistance in the commercialization process. The results of this program show an increase in participants' knowledge about the importance of fish consumption and skills in making surabi. Evaluations from pre-test and post-test show a significant improvement in participants' understanding of nutritious food processing. Through this activity, it is expected that surabi fish products can help improve children's nutritional intake while also providing economic opportunities for the local community. Fish surabi is positioned as an innovative solution to tackle the stunting problem in this island area, with great commercialization potential.
Keywords: Fish, Pangkep, stunting, surabi.
Photon shielding competence of concrete doped CuO for gamma shielding applications
Authors: Hudu Salisu , Mustapha Idris M. , Bello Sulayman M. , Halimatu Abdullahi S. , James Iwa S. , Aisha Mohammed A. , Ubaidullah Ahmad
Published: January 2025

In this study, photon attenuation parameters of concrete doped CuO, were determined and their application as shielding material were discussed. The WinXCOM software was used to determine the mass attenuation coefficient (MAC) of the concrete doped CuO samples (0, 20, 40 60 and 100 wt% CuO content) for the energy range (0.015-15MeV). The linear attenuation coefficient, half value layer (HVL), mean free path (MFP), and effective atomic number (Zeff) were calculated from the MAC values. The MAC values of the samples decreases rapidly up to 0.12 MeV, and beyond 0.12 MeV, Compton scattering becomes effective at intermediate energies. The LAC value vary with energy in similar way as MAC. The calculated HVL and MFP were observe to  decline  as  the  CuO doping  of  the  glasses  increased  which  accounts  for  the  three  photon interaction mechanisms effectiveness in the variation of HVL and MFP values with energy. The Zeff shows minimal variation as the energy increases in all the concrete doped CuO samples. It can be concluded that doping CuO with concrete can greatly enhance the gamma shielding ability of the sample.
Bound state solution of schrodinger equation with modified Hylleraas plus inversely quadratic potential using parametric Nikiforov-Uvarov method
Authors: Mohammed Imrana Habibat , Yabagi Jibrin Alhaji , Akusu Patrick Ovie , Ubaidullah Ahmad , Ladan Muhammad Bello , Babakacha Ndanusa
Published: January 2025

In this work, an approximate bound state solution to Schrodinger equation with modified Hylleraas plus inversely quadratic potential was obtained using the parametric form of the Nikiforov-Uvarov method. Applying the elegant approximation to deal with the centrifugal term for arbitrary orbital angular quantum number, the energy spectrum and the corresponding wave function was obtained.
The motion of spinor in the vicinity of spherical star and the magnetic field of non-homogeneous spherical bodies
Authors: Minister Samson Adigizi , Chifu Ebenezer Ndikilar
Published: January 2025

In this article, we developed the spinors connections from Schwarzschild metric and make use of the spinor connections in geodesics in order to obtain the equation of spinor in the vicinity of spherical star. The gravitational scalar potential for non-homogeneous spherical body was use to developed the magnetic field of different regions of some non-homogenous spherical bodies.
Impacts of State COVID-19 Vaccine Mandates for Health Care Workers on Health Sector Employment in the United States
Authors: Wang Yin , Callison Kevin , Hernandez Julie H. , Stoecker Charles
Published: January 2025

Objectives. To assess the impact of state COVID-19 vaccine mandates for health care workers (HCWs) on health sector employment in the United States.

Methods. Using monthly state-level employment data from the Quarterly Census of Employment and Wages between January and October 2021, we employed a partially pooled synthetic control method that accounted for staggered mandate adoption and heterogeneous treatment effects. We conducted analyses separately for the 4 health care subsectors—ambulatory health care services, hospitals, nursing and residential care, and social assistance—with an additional analysis of 2 industry groups—skilled nursing care and community care for the elderly—under the nursing and residential care subsector. We further explored possible heterogeneous impacts according to the test-out option availability.

Results. Mandate impact estimates were statistically indistinguishable from zero. Results further ruled out a mandate-associated decrease in employment larger than 2.1% of premandate employment levels for the 6 health care domains examined and for states with no test-out option.

Conclusions. State COVID-19 vaccine mandates for HCWs were not found to be associated with significant adverse impacts on health sector employment even in states without a testing alternative to vaccination. The findings support vaccine mandates as a viable preventive measure without material disruption to the health care workforce, including in times of public health emergencies. ( Am J Public Health. 2025;115(3):344–348. https://doi.org/10.2105/AJPH.2024.307906 )
Crystallized and fluid cognitive abilities have different genetic associations with neuropsychiatric disorders
Authors: Londono-Correa Diego , Fuente Javier de la , Davies Gail , Cox Simon , Deary Ian , Harden K , Tucker-Drob Elliot
Published: January 2025

Cognitive function is associated with risk for multiple neuropsychiatric disorders. Previous research on the genetic relations between cognition and psychopathology has largely treated cognitive function as unitary, in part due to a lack of well-powered genome-wide association studies (GWAS) on specific domains, particularly crystallized knowledge (Gc). Important domains within the hierarchy of cognitive function, especially Gc, have been underexplored regarding their associations with psychiatric disorders. Here, we parse the genetics of cognitive test performance into components representing reaction time, fluid reasoning, and crystallized knowledge. This multivariate approach that allows us to report results from a GWAS meta-analysis of crystallized knowledge (N ~ 438,000). We then test how multiple neuropsychiatric disorders with established links to cognitive function (Schizophrenia, Bipolar Disorder, Autism Spectrum Disorder, Attention Deficit Hyperactivity Disorder, and Alzheimer’s Disease) are genetically related to these three cognitive domains, and to a noncognitive factor associated with educational attainment (NonCog). We document specific and heterogenous patterns of genetic associations between each neuropsychiatric disorder and the different domains of cognitive function and the noncognitive factor. Previous reports of genetic sharing between neuropsychiatric disorders and GWAS of aggregate cognitive function or educational attainment have failed identify these substantial differences in which cognitive functions drive these relations for which disorders.
Random Saturation Mutagenesis to Generate Highly Diverse Libraries for Directed Evolution
Authors: Weitz David , Zhang Xinge , Chen Anqi , Chen Liyin , Thakur Rohan , Ellis Perry , Xiao Yi , Milčić Miloš , Milcic Karla
Published: January 2025

Directed evolution improves the function of enzymes by diversifying the wild-type to generate variants and searching for the desired functions. When prior knowledge about the wild-type is limited, random mutagenesis is employed to introduce mutations at arbitrary positions. However, conventional methods exhibit significant bias in the distribution of amino acid substitutions, resulting in inaccessible chemical properties, limiting the chemical diversity, and hindering discovery of substantially improved variants. To overcome such limitations, we develop Random Saturation Mutagenesis (RSM) that uniformly introduces all amino acid substitutions across the gene at controlled rates by using overlapping site-mutagenesis oligo pools. Sequencing results illustrate the high quality and diversity of RSM libraries as compared to conventional libraries. We demonstrate the utility of RSM by improving thermotolerance of LipaseA. With only one round of mutagenesis, we identify two variants with over 40°C improvement in thermotolerance, demonstrating the potential of RSM to transform and accelerate directed evolution.
SciToolAgent: A Knowledge Graph-Driven Scientific Agent for Multi-Tool Integration
Authors: Chen Huajun , Ding Keyan , Yu Jing , Huang Junjie , Yang Yuchen , Zhang Qiang
Published: January 2025

Scientific research increasingly relies on specialized computational tools, yet effectively utilizing these tools demands substantial domain expertise. While Large Language Models (LLMs) show promise in tool automation, they struggle to seamlessly integrate and orchestrate multiple tools for complex scientific workflows. Here, we present SciToolAgent, an LLM-powered agent that automates hundreds of scientific tools across biology, chemistry, and materials science. At its core, SciToolAgent leverages a scientific tool knowledge graph that enables intelligent tool selection and execution through graph-based retrieval-augmented generation. The agent also incorporates a comprehensive safety-checking module to ensure responsible and ethical tool usage. Extensive evaluations on a curated benchmark demonstrate that SciToolAgent significantly outperforms existing approaches. Case studies in protein engineering, chemical reactivity prediction, chemical synthesis, and metal-organic framework screening further demonstrate SciToolAgent's capability to automate complex scientific workflows, making advanced research tools accessible to both experts and non-experts.
Tropical deforestation causes considerable heat-related mortality
Authors: Reddington Carly , Smith Callum , Butt Edward , Baker Jessica , Oliveira Beatriz , Yamba Edmund , Spracklen Dominick
Published: January 2025

Tropical deforestation causes local climate warming and is a potential risk to human health. Previous studies have shown tropical deforestation increases heat stress and reduces safe outdoor working hours, but the impact of deforestation on heat-related mortality has not been quantified. Here we make the first pan-tropical assessment of the human mortality resulting from the local climate warming caused by tropical deforestation. Analysis of satellite data shows tropical deforestation during 2001 to 2020 exposed 345 million people to local climate warming with population-weighted daytime land surface warming of 0.27°C. We estimate this warming results in 28,000 additional deaths per year. Heat-related mortality rates were greatest in Southeast Asia with 9 deaths for every 100,000 people living in deforested areas, followed by Tropical Africa (5 deaths per 100,000 people) and Tropical Central and South America (3 deaths per 100,000 people). In regions that experienced forest loss, the local climate warming from deforestation is responsible for over one third of total climate related mortality highlighting the human health risk of local warming due to tropical deforestation.
Barriers in the control of Schistosomiasis with Mass distribution of Praziquantel in Bauchi State, Nigeria - A Phenomenological study
Authors: Charles Adeyemo Sunday , Oluwafemi Are-Daniel Obehi , Yetunde Adeleke Folasade , Maleka Abdulwaris Salisu , Joseph Akintade Odunlami , Raphael Ajayi Ayodele , Muhammad Abdulsalam Hussaini , Rabiu Nafi'u , Yunusa Usman
Published: January 2025

Schistosomiasis is a major public health problem in sub-Saharan Africa and major public health concern. There has been reportage of over 700 million of population at risk arising from an estimated affected population of at least 230 million worldwide. Estimates indicate that approximately 29 million individuals in Nigeria are infected with S. haematobium, while an alarming 101.3 million people are considered at risk. Despite the World Health Organization's recommendations for the widespread distribution of Praziquantel and the efforts of the Bauchi government to ensure access to clean water and health education in accordance with these guidelines, the prevalence of the issue continues to be alarmingly high. This study aims to explore the factors contributing to the failure of widespread distribution of Praziquantel to reduce the prevalence of schistosomiasis in Bauchi State, with a specific focus on the Dass local government area. The research is conducted in the Dass Local Government Area (LGA) of Bauchi State, Nigeria, which is positioned in the north-eastern region of the country. In-depth interviews were carried out with 20 stakeholders at the local government level. Coding was done using qualitative analysis software, ATLAS TI software for the data management and analysis data were coded into themes based on the research objectives. The inadequate involvement of government and NGOs and Community-related factors including fear of side effects and stigmatization where among factors highlighted as major barriers. This research underscores the various obstacles to successful schistosomiasis management in Dass Local Government via mass drug administration (MDA). Tackling issues associated with drug availability, the well-being of healthcare personnel, community education, and logistical challenges necessitates a collaborative effort among multiple stakeholders.
Predicting High Confidence ctDNA Somatic Variants with Ensemble Machine Learning Models
Authors: Maruzani Rugare , Fowler Anna , Brierley Liam , Jorgensen Andrea
Published: January 2025

Circulating tumour DNA (ctDNA) is a minimally invasive cancer biomarker that can be used to inform treatment of cancer patients. The utility of ctDNA as a cancer biomarker depends on the ability to accurately detect somatic variants associated with cancer. Accurate somatic variant detection in circulating cell free DNA (cfDNA) NGS data requires filtering strategies to remove germline variants, and NGS artifacts. Rule-based variant filtering methods either remove a substantial number of true positive ctDNA variants along with false variant calls or retain an implausibly large number of total variants. Machine Learning (ML) enables identification of complex patterns which may improve ability to distinguish between real somatic ctDNA variants and false positive calls. We built two Random Forest (RF) models for predicting high confidence somatic ctDNA variants in low and high depth cfDNA NGS data. Low depth models were fitted and evaluated on whole exome sequencing (WES) cfDNA data at depths of approximately 10X while the high depth data was sequenced at approximately 500X. Both models utilise a set of 15 features from variants detected by bcftools, FreeBayes, LoFreq and Mutect2. High confidence ground truth sets were obtained from matched tissue biopsy samples. We benchmarked our models against rule-based filtering with a set of hard, medium, and soft thresholds. Precision-recall curves showed the high depth model outperformed rule-based filtering at all thresholds in validation data (PR-AUC 0.71). Partial dependence plots showed membership in the COSMIC database, absence from the dbSNP common variants database, and increasing read depth increased mean probability of high confidence somatic variant prediction in both models. Our results demonstrate the utility of supervised ML models for filtering variants in cfDNA data.
A Low-Cost and Scalable Landslide Monitoring and Early Warning System for Mountainous Regions Using Deep Learning-based Computer Vision
Authors: Chen Jie , Song Longfei , Pu Yuanyuan , Apel Derek
Published: January 2025

Landslides pose severe risks to lives, property, and infrastructure, particularly in mountainous regions where monitoring is hindered by harsh environmental conditions and complex terrains. This study proposes a scalable, low-cost landslide monitoring and early warning system that integrates deep learning and computer vision technologies. Using a single optical camera, time-lapse images of slopes were captured and processed through advanced alignment, masking, and histogram equalization to maintain accuracy under adverse conditions. The system combines static monitoring via image differencing with dynamic monitoring using a RAFT-based optical flow model to detect surface deformations and real-time displacements. Field tests conducted on Washington Makahdiot Cliff demonstrated the system’s capability to identify landslide risks across three deformation phases. Static analysis detected significant grayscale changes (> 100) linked to actual slope deformations, while dynamic monitoring achieved a displacement detection accuracy of 94.6% for movements up to 25 cm. A novel early warning algorithm, based on thresholds for abnormal pixel changes, successfully classified risk levels, with landslide risk coefficients exceeding 0.4 during landslide events and remaining below 0.1 otherwise. The system proved resilient to environmental challenges, such as fog and strong winds, and demonstrated a positive correlation between landslide risk coefficients and rainfall, underscoring the importance of integrating real-time environmental data. This method provides an effective, robust, and cost-efficient solution for landslide monitoring and mitigation in complex terrains.
UNICORN: Towards Universal Cellular Expression Prediction with an Explainable Multi-Task Learning Framework
Authors: Zhao Hongyu , Liu Tianyu , Huang Tinglin , Lin Yingxin , Ying Rex
Published: January 2025

Sequence-to-function analysis is a challenging task in human genetics, especially in predicting cell-type-specific multi-omic phenotypes from biological sequences such as individualized gene expression. Here, we present UNICORN, a new method with improved prediction performances than the existing methods. UNICORN takes the embeddings from biological sequences as well as external knowledge from pre-trained foundation models as inputs and optimizes the predictor with carefully-designed loss functions. We demonstrate that UNICORN outperforms the existing methods in both gene expression prediction and multi-omic phenotype prediction at the cellular level and the cell-type level, and it can also generate uncertainty scores of the predictions. Moreover, UNICORN is able to link personalized gene expression profiles with corresponding genome information. Finally, we show that UNICORN is capable of characterizing complex biological systems for different disease states or perturbations. Overall, embeddings from foundation models can facilitate the understanding of the role of biological sequences in the prediction task, and incorporating multi-omic information can enhance prediction performances.
Experimental and numerical study on tribological behavior and machinability in titanium indirect cryogenic machining with minimum quantity lubrication
Authors: Kim Doyoung , Ha Ju-Hyung , Ha Min Gi , Kim Dongmin
Published: January 2025

Cryogenic machining involves spraying cryogenic coolants to reduce the cutting tool temperature. In this study, cryogenic machining was applied to a titanium alloy with minimum quantity lubrication (MQL), and the tribological and machining performance were evaluated. As side-down milling was performed, the effects of cryogenic cooling and MQL were experimentally and numerically investigated with long machining distances (40, 000 mm), and the cutting force, tool wear, and tool temperature were analyzed. Compared to the wet condition, under the cryoMQL condition, which represents the simultaneous application of cryogenic cooling and MQL, the cutting force and flank wear length decreased by up to 17.7% and 46.4%, respectively. The cryogenically cooled and lubricated cutting tool enhanced the tribological performance, slowing tool wear. The reduced surface friction of the tool and tool wear decreased the frictional force and changed the trend of the cutting force according to the machining distance. The cryoMQL milling was simulated using DEFORM software. In the numerical study, a decrease in the tool temperature, which affects the reduction in cutting force and tool wear, was observed under cryoMQL conditions. The maximum tool temperature was reduced by 46.5% compared with that under wet conditions.
Assuring Correctness, Testing, and Verification of Communicating Stream X-Machine (CSXM)-Based Compiler by Integrating Machine Learning Models
Authors: SANUSI BASHIR A. , OGUNSHILE EMMANUEL K. , AYDIN MEHMET
Published: January 2025

Traditional compilers face challenges in detecting and correcting complex errors due to their reliance on static rule-based methods. This research introduces an innovative hybrid approach that integrates Machine Learning (ML) models with a Communicating Stream X-Machine (CSXM)-based compiler to improve error detection and possible suggestion. The CSXM formal method is combined with advanced ML techniques, including Random Forest (RF), Convolutional Neural Network (CNN), and an optimized CNN-LSTM model, leveraging temporal dependencies for improved performance. The ML-enhanced compiler was trained and evaluated on the DeepFix and Generated datasets using metrics such as accuracy, precision, recall, and F1-score. Experimental results demonstrate that the CNN-LSTM outperformed RF and CNN across both datasets, achieving an accuracy of 89.72% on DeepFix and 90.00% on the Generated dataset, with minimal performance variance. This research demonstrates the potential of AI-driven compilers, providing a foundation for future exploration of intelligent, adaptive, and efficient compilation processes, and setting a benchmark for hybrid approaches in software engineering.
Kidney pathological findings of MYH9-related disease: a cross-sectional nationwide survey in Japan
Authors: Nakatani Ryo , Miura Kenichiro , Shirai Yoko , Ohtsuka Yasufumi , Ohwada Yoko , Konomoto Takao , Morohashi Tamaki , Tsugawa Koji , Taneda Sekiko , Honda Kazuho , Kunishima Shinji , Ishikura Kenji , Hattori Motoshi
Published: January 2025

Background
MYH9-related disease (MYH9-RD) is characterized by macrothrombocytopenia, hearing loss, and progressive kidney dysfunction. However, kidney biopsy is seldom performed because of low platelet counts. Although a review based on case reports described pathological findings of MYH9-RD included focal segmental glomerulosclerosis (FSGS) and glomerular basement membrane (GBM) abnormalities similar to those in Alport syndrome, no comprehensive studies of MYH9-RD have been performed.
Methods
We conducted a nationwide survey of MYH9-RD patients and collected kidney pathological samples, and immunofluorescence and electron microscopy images. All pathological samples were examined by multiple pediatric nephrologists and pathologists.
Results
Nine kidney biopsy samples from eight patients were included. Mesangial matrix expansion was observed in all nine samples (100%), and two samples (22%) had FSGS. Segmental foot process effacement was observed in all nine samples (100%), accompanied by irregularly aggregated podocyte dense material in seven samples (78%). Immunofluorescence analysis revealed three samples (33%) had immunoglobulin and/or complement deposition. Electron dense deposits (EDD) in the mesangium and GBM were observed in five samples (56%), including three samples with positive immunofluorescence. Electron microscopy also demonstrated endothelial cell swelling in seven samples (78%) and GBM abnormalities in five samples (55%), including thinning, thickening and splitting of the lamina densa.
Conclusions
Mesangial matrix expansion and segmental foot process effacement were commonly observed in MYH9-RD patients. In addition, various pathological findings including immunoglobulin and complement deposition with EDD and GBM abnormalities were also observed. These results may have important implications for the disease mechanism and treatment of MYH9-RD.
Fusion-Based Hybrid Model for SMS Spam Detection Integrating Local, Sequential, and Contextual Features
Authors: Al-Kaabi Hussein , Al-Ibraheemi Fuqdan , Jasim Ali Kadhim , AL-Rekabi Mohammed , parchami jaber
Published: January 2025

In the era of pervasive digital communication, SMS spam poses significant threats, including financial fraud and phishing attacks, necessitating robust detection mechanisms. This paper introduces a novel hybrid model for SMS spam detection, leveraging advanced deep-learning techniques to capture diverse textual features comprehensively. The model integrates Convolutional Neural Networks (CNN) for local feature extraction, Bidirectional Long Short-Term Memory (Bi-LSTM) networks for sequential dependencies, and Bidirectional Encoder Representations from Transformers (BERT) for contextual embeddings. A parallel architecture combines these components to achieve a holistic representation of SMS content. Fused feature vectors undergo attention-based selection to enhance computational efficiency while preserving critical information. Evaluated on the UCI SMS Spam Collection dataset using a 10-fold cross-validation strategy, the proposed model achieves a remarkable accuracy of 99.68%, outperforming state-of-the-art techniques. This work addresses the limitations of traditional and hybrid methods, offering a highly reliable and adaptable solution to the evolving challenges of SMS spam detection. Future directions include real-time adaptability, multimodal integration, and resource-efficient deployment.