bluuebunny/crossref_metadata_2025_split huggingface dataset:
A fusion of machine learning and cryptography for fast data encryption through the encoding of high and moderate plaintext information blocks
Authors: Shafique Arslan , Mehmood Abid , Alawida Moatsum , Elhadef Mourad , Rehman Mujeeb Ur 
Published: April 2024

AbstractWithin the domain of image encryption, an intrinsic trade-off emerges between computational complexity and the integrity of data transmission security. Protecting digital images often requires extensive mathematical operations for robust security. However, this computational burden makes real-time applications unfeasible. The proposed research addresses this challenge by leveraging machine learning algorithms to optimize efficiency while maintaining high security. This methodology involves categorizing image pixel blocks into three classes: high-information, moderate-information, and low-information blocks using a support vector machine (SVM). Encryption is selectively applied to high and moderate information blocks, leaving low-information blocks untouched, significantly reducing computational time. To evaluate the proposed methodology, parameters like precision, recall, and F1-score are used for the machine learning component, and security is assessed using metrics like correlation, peak signal-to-noise ratio, mean square error, entropy, energy, and contrast. The results are exceptional, with accuracy, entropy, correlation, and energy values all at 97.4%, 7.9991, 0.0001, and 0.0153, respectively. Furthermore, this encryption scheme is highly efficient, completed in less than one second, as validated by a MATLAB tool. These findings emphasize the potential for efficient and secure image encryption, crucial for secure data transmission in rea-time applications.
Proximal intentions intentionalism
Authors: Tamburini Victor 
Published: April 2024

AbstractAccording to a family of metasemantics for demonstratives called intentionalism, the intentions of speakers determine the reference of demonstratives. And according to a sub-family I call proximal intentions (PI) intentionalism, the intention that determines reference is one that occupies a certain place—the proximal one—in a structure of intentions. PI intentionalism is thought to make correct predictions about reference where less sophisticated forms of intentionalism make the wrong predictions. In this article I argue that this is an illusion: PI intentionalism also suffers from predictive inadequacy. In Sect. 1, I present the problem of predictive inadequacy for intentionalism and an ad hoc response to it. In Sect. 2, I sketch a version of PI intentionalism that aims to provide the most principled response to this problem. In Sect. 3, I explain why PI intentionalism cannot solve the problem after all. In Sect. 4, I indicate where I think metasemanticists should go next.
Membrane-based inverse-transition purification facilitates a rapid isolation of various spider-silk elastin-like polypeptide fusion proteins from extracts of transgenic tobacco
Authors: Gruchow H. M. , Opdensteinen P. , Buyel J. F. 
Published: April 2024

AbstractPlants can produce complex pharmaceutical and technical proteins. Spider silk proteins are one example of the latter and can be used, for example, as compounds for high-performance textiles or wound dressings. If genetically fused to elastin-like polypeptides (ELPs), the silk proteins can be reversibly precipitated from clarified plant extracts at moderate temperatures of ~ 30 °C together with salt concentrations > 1.5 M, which simplifies purification and thus reduces costs. However, the technologies developed around this mechanism rely on a repeated cycling between soluble and aggregated state to remove plant host cell impurities, which increase process time and buffer consumption. Additionally, ELPs are difficult to detect using conventional staining methods, which hinders the analysis of unit operation performance and process development. Here, we have first developed a surface plasmon resonance (SPR) spectroscopy-based assay to quantity ELP fusion proteins. Then we tested different filters to prepare clarified plant extract with > 50% recovery of spider silk ELP fusion proteins. Finally, we established a membrane-based purification method that does not require cycling between soluble and aggregated ELP state but operates similar to an ultrafiltration/diafiltration device. Using a data-driven design of experiments (DoE) approach to characterize the system of reversible ELP precipitation we found that membranes with pore sizes up to 1.2 µm and concentrations of 2–3 M sodium chloride facilitate step a recovery close to 100% and purities of > 90%. The system can thus be useful for the purification of ELP-tagged proteins produced in plants and other hosts.
The SpRY Cas9 variant release the PAM sequence constraint for genome editing in the model plant Physcomitrium patens
Authors: Calbry Julie , Goudounet Guillaume , Charlot Florence , Guyon-Debast Anouchka , Perroud Pierre-François , Nogué Fabien 
Published: April 2024

AbstractGenome editing via CRISPR/Cas has enabled targeted genetic modifications in various species, including plants. The requirement for specific protospacer-adjacent motifs (PAMs) near the target gene, as seen with Cas nucleases like SpCas9, limits its application. PAMless SpCas9 variants, designed with a relaxed PAM requirement, have widened targeting options. However, these so-call PAMless SpCas9 still show variation of editing efficiency depending on the PAM and their efficiency lags behind the native SpCas9. Here we assess the potential of a PAMless SpCas9 variant for genome editing in the model plant Physcomitrium patens. For this purpose, we developed a SpRYCas9i variant, where expression was optimized, and tested its editing efficiency using the APT as a reporter gene. We show that the near PAMless SpRYCas9i effectively recognizes specific PAMs in P. patens that are not or poorly recognized by the native SpCas9. Pattern of mutations found using the SpRYCas9i are similar to the ones found with the SpCas9 and we could not detect off-target activity for the sgRNAs tested in this study. These findings contribute to advancing versatile genome editing techniques in plants.
Consumer responses to human-AI collaboration at organizational frontlines: strategies to escape algorithm aversion in content creation
Authors: Haupt Martin , Freidank Jan , Haas Alexander 
Published: April 2024

Abstract
Although Artificial Intelligence can offer significant business benefits, many consumers have negative perceptions of AI, leading to negative reactions when companies act ethically and disclose its use. Based on the pervasive example of content creation (e.g., via tools like ChatGPT), this research examines the potential for human-AI collaboration to preserve consumers' message credibility judgments and attitudes towards the company. The study compares two distinct forms of human-AI collaboration, namely AI-supported human authorship and human-controlled AI authorship, with traditional human authorship or full automation. Building on the compensatory control theory and the algorithm aversion concept, the study evaluates whether disclosing a high human input share (without explicit control) or human control over AI (with lower human input share) can mitigate negative consumer reactions. Moreover, this paper investigates the moderating role of consumers’ perceived morality of companies’ AI use. Results from two experiments in different contexts reveal that human-AI collaboration can alleviate negative consumer responses, but only when the collaboration indicates human control over AI. Furthermore, the effects of content authorship depend on consumers' moral acceptance of a company's AI use. AI authorship forms without human control lead to more negative consumer responses in case of low perceived morality (and no effects in case of high morality), whereas messages from AI with human control were not perceived differently to human authorship, irrespective of the morality level. These findings provide guidance for managers on how to effectively integrate human-AI collaboration into consumer-facing applications and advises to take consumers' ethical concerns into account.
Citalopram, an antipsychotic agent, induces G1/G0 phase cell cycle arrest and promotes apoptosis in human laryngeal carcinoma HEP-2 cells
Authors: Salama Mohammed , Ali Abeer , Ibrahim Fawziya A. R. , Elabd Seham 
Published: April 2024

AbstractHuman laryngeal squamous carcinoma (LSCC) is a common malignant tumor in the head and neck. Despite the recently developed therapies for the treatment of LSCC, patients’ overall survival rate still did not enhance remarkably; this highlights the need to formulate alternative strategies to develop novel treatments. The antitumor effects of antidepressant drugs such as citalopram have been reported on several cancer cells; however, they have yet to be investigated against LSCC. The current study was directed to explore the possible antitumor effects of citalopram on human laryngeal carcinoma cell lines (HEP-2). HEP-2 cells were cultured and treated with different doses of citalopram (50–400 µM) for 24, 48, and 72 h. The effects of citalopram on the viability of cancer cells were determined by the MTT assay. In addition, apoptosis and cell cycle analysis were performed by flow cytometry. Moreover, evaluation of the expression of proapoptotic and apoptotic proteins, such as cytochrome c, cleaved caspases 3 and 9, Bcl-2, and BAX, was performed by western blotting analysis. Our results revealed that citalopram significantly suppressed the proliferation of HEP-2 cells through the upregulation of p21 expression, resulting in the subsequent arrest of the cell cycle at the G0/G1 phase. Furthermore, citalopram treatment-induced HEP-2 cell apoptosis; this was indicated by the significant increase of cytochrome c, cleaved caspases 3 and 9, and BAX protein expression. On the contrary, Bcl-2 protein expression was significantly downregulated following treatment with citalopram. The ultrastructure studies were in accordance with the protein expression findings and showed clear signs of apoptosis with ring chromatin condensation upon treatment with citalopram. These findings suggest that citalopram’s anti-tumor activities on HEP-2 cells entailed stimulation of the intrinsic apoptotic pathway, which was mediated via Bcl-2 suppression.
Sleep Behaviors and the Shape of Subcortical Brain Structures in Children with Overweight/Obesity: A Cross-Sectional Study
Authors: Cadenas-Sanchez Cristina , Migueles Jairo H. , Torres-Lopez Lucia V. , Verdejo-Román Juan , Jiménez-Pavón David , Hillman Charles H. , Catena Andrés , Ortega Francisco B. 
Published: April 2024

Abstract
Objectives
To examine the relationship between sleep and subcortical brain structures using a shape analysis approach.

Methods
A total of 98 children with overweight/obesity (10.0 ± 1.1 y, 59 boys) were included in the cross-sectional analyses. Sleep behaviors (i.e., wake time, sleep onset time, total time in bed, total sleep time, sleep efficiency, and wakening after sleep onset) were estimated with wrist-worn accelerometers. The shape of the subcortical brain structures was acquired by magnetic resonance imaging. A partial correlation permutation approach was used to examine the relationship between sleep behaviors and brain shapes.

Results
Among all the sleep variables studied, only total time in bed was significantly related to pallidum and putamen structure, such that those children who spent more time in bed had greater expansions in the right and left pallidum (211–751 voxels, all p’s <0.04) and right putamen (1783 voxels, p = 0.03).

Conclusions
These findings suggest that more time in bed was related to expansions on two subcortical brain regions in children with overweight/obesity.
Introduction of the South American slipper limpet Crepipatella dilatata in Europe: Secondary spread in the Northeast Atlantic and first records for the Mediterranean Sea
Authors: Salvi Daniele , Smriglio Carlo , Garzia Matteo , Andreuccci Sarah , Mariottini Paolo 
Published: April 2024

AbstractThe slipper limpet Crepipatella dilatata, native to Chile and Argentina, was introduced in north-western Spain in 2005 and since then has spread to the Galician and Cantabrian coasts. In this work, we provide the first molecularly validated record of an established population of C. dilatata in central Portugal (Aveiro), and of reproductive individuals (i.e. brooding females) of C. dilatata in the Mediterranean Sea, from three Italian mussel farms (in eastern Sardinia and northern Adriatic). DNA barcoding and phylogenetic analyses based on mitochondrial markers indicate that limpets from Italian farms belong to the C. dilatata ‘clade1’, whereas limpets collected in Aveiro cluster within the C. dilatata ‘clade2’. All these limpets share the same COI haplotypes with introduced populations from Galicia. The arrival of C. dilatata to Europe is undoubtedly due to transoceanic live mussel trade from southern Chile to Galicia. Mussel trade and farming are also the most likely drivers for the post-border dispersal of C. dilatata from Spain to Portugal and to Italy. Several countries have a potential role as a hub for the primary and secondary dispersal of slipper limpets towards and within Europe. This calls the attention for future research focused on assessing the current occurrence and ecological impact of established populations of slipper limpets within and nearby mussel farms along the eastern Atlantic and Mediterranean coasts.
Comparative assessment of hydrochemical characterization and groundwater quality for irrigation in an autochthonous karst aquifer with the support of GIS: case study of Altinova, Turkey
Authors: Wani Alex Modi Lomoro , Abunada Ziyad , Yenilmez Firdes , Muhammetoglu Ayse , Muhammetoglu Habib 
Published: April 2024

AbstractThis study aims to present a comparative assessment of hydrochemical characterization and groundwater quality in karst aquifers with the support of GIS which is essential to correlate the source of water with climate and geology, and to evaluate suitability of water for various uses. The study area is the Altinova region in Turkey where intensive agricultural activities prevail and travertine covers 85% of the study area. A total of 25 groundwater wells were monitored by seasonal field measurements and extensive water quality analyses for a period of one year to establish correlation between groundwater quality, its source, regional climate, and geology. A comprehensive analysis was conducted to assess the groundwater's suitability for irrigation based on electrical conductivity, sodium adsorption ratio, sodium percentage, magnesium hazard, permeability index, residual sodium bicarbonate, Kelly’s ratio, and an irrigation water quality (IWQ) index. This multi-parameter evaluation was further integrated with geospatial analysis using ArcGIS, providing a detailed spatial understanding of hydrochemical variations across the area. Major cations and anions dominance were identified as Ca2+ > Na+ > Mg2+ > K+ and HCO3− > Cl− > SO42−, respectively. Spatial mapping identified high concentrations of Ca2+, TDS, TH, and SO42− in non-karstic areas, occasionally exceeding WHO guidelines. Nitrate concentrations displayed varied spatial distribution. The SAR values generally matched C2-S1 and C3-S1 classes, suggesting medium to high salinity risks and low sodium presence. Based on the IWQ index and observed correlations with total dissolved solids, the groundwater in Altinova’s karstic aquifer is considered suitable for irrigation, with salinization largely due to ionic interactions and geology. The presented comparative assessment provides a holistic approach for understanding hydrochemical characteristics of karst aquifers, and analyzing the impacts of natural factors and anthropogenic pollution sources on groundwater quality.
The Effect of Mindfulness-Based Stress Reduction Program on Stress and Quality of Life in Family Caregivers of Patients with Cancer: Randomized Controlled Trial
Authors: Türkoğlu Nihan , Kavuran Esin 
Published: April 2024

Abstract
Objectives
The study aimed to examine the effects of an online Mindfulness-Based Stress Reduction program on stress and quality of life levels of family caregivers of cancer patients.

Method
The study used a randomized controlled trial design with a pre-test (T1), follow-up (T2) and post-test (T3) which was conducted with 104 family caregivers of cancer patients. Data collection was conducted using the Caregiver and Patient Descriptive Information Form, Caregiver’s Stress Scale and The Caregiver Quality of Life Index Cancer Scale. T1 measurements were conducted for experimental (n = 50) and control groups (n = 54). After the 8-week online Mindfulness-Based Stress Reduction program of the experimental group, T2 measurements were taken for both groups. Four weeks later, the T3 measurement was collected for both experimental and control groups.

Results
A statistically significant difference over time was detected between the mean Caregiver’s Stress Scale scores of the experimental group in the T1, T2, and T3. There was no significant difference in the control group over time. A statistically significant difference was detected in the mean Caregiver Quality of Life Index Cancer Scale total score of the experimental group across T1, T2, and T3. When the scale pre-test mean scores were compared between the groups, no significant differences were detected for T1, but a statistically significant difference was found between the T2 and T3 scores.

Conclusion
In the study, it was determined that the online Mindfulness-Based Stress Reduction program had an effect on reducing stress and improving the quality of life.

Preregistration
The research was registered on http://clinicaltrials.gov (ID:NCT05831293).
Online Mindfulness-Based Intervention Program Improves Mental Health, Well-Being, and Productivity
Authors: Ogino Junya , Maruyama Takashi , Umene-Nakano Wakako , Maeno Takashi 
Published: April 2024

Abstract
Objectives
This study aimed to evaluate the effectiveness of the Intervention program of Mindfulness and Compassion against COVID-19 (IMACOCO), an online mindfulness-based intervention (MBI), in enhancing mindfulness, mental health, well-being, and productivity among working individuals during the COVID-19 pandemic. Additionally, the study examined the program’s efficacy in individuals directly impacted by the pandemic through a randomized controlled trial and pre-post program comparisons.

Method
Three hundred working adults, including office workers, educators, and medical welfare workers, were randomly allocated to the intervention or waiting control group. An 8-week online MBI program, with pre-, interim (4 weeks), and post-program (8 weeks) evaluations, was conducted via the Internet; standardized questionnaires were used to assess mindfulness, psychological distress, life satisfaction, and productivity. After the initial 8-week program, the waiting control group participated in the same program and evaluation surveys for pre-post comparisons.

Results
There were 99 participants in the intervention group and 111 in the control group. Significant increases in mindfulness (FFMQ) and life satisfaction (SWLS) as well as decrease in psychological distress (GHQ-12) were observed primarily in the intervention group (Cohen’s d = 0.18–0.52). Furthermore, the pre-post comparisons with 168 participants demonstrated significant improvements in productivity (Cohen’s d = 0.26), and stratified analysis revealed that participants affected by COVID-19 showed more pronounced benefits in mindfulness and life satisfaction than those who were unaffected.

Conclusions
Implementing an online MBI program (IMACOCO) can be a potent strategy to reduce mental stress and enhance overall well-being and resilience, in a disaster-prone world.

Preregistration
This study is not preregistered.
Fibrin glue mediated direct delivery of radiation sensitizers results in enhanced efficacy of radiation treatment
Authors: Nguyen Jane , Chandekar Akhil , Laurel Sophia , Dosanjh Jazleen , Gupta Keya , Le Justin , Hirschberg Henry 
Published: April 2024

Abstract
Purpose
Radiation therapy (RT) plays an important role in the treatment of glioblastoma multiforme (GBM). However, inherent intrinsic resistance of tumors to radiation, coupled with the need to consider the tolerance of normal tissues and the potential effects on neurocognitive function, impose constraints on the amount of RT that can be safely delivered. A strategy for augmenting the effectiveness of RT involves the utilization of radiation sensitizers (RS). Directly implanting RS-loaded fibrin glue (FG) into the tumor resection cavity would by-pass the blood brain barrier, potentially enhancing the impact of RT on tumor recurrence. This study investigated the ability of FG to incorporate and release, in non-degraded form, the radiation sensitizers 5-Fluorouracil (5FU) and Motexafin gadolinium (MGd).

Methods
FG layers were created in a 24-well plate by combining thrombin, fibrinogen, and 5FU or MGd. Supernatants from these layers were collected at various intervals and added to F98 glioma spheroid cultures in 96-well plates. Radiation was applied either before or after RS application as single or fractionated dosages. Spheroid growth was monitored for 14 days.

Results
Combined treatment of FG-released 5FU and RT significantly inhibited spheroid growth compared to RS or RT as a single treatment. As a free drug, MGd demonstrated its efficacy in reducing spheroid volume, but had diminished potency as a released RS. Fractionated radiation was more effective than single dose radiation.

Conclusion
Non-degraded RS was released from the FG for up to 72 h. FG-released 5FU greatly increased the efficacy of radiation therapy.
Are deep learning classification results obtained on CT scans fair and interpretable?
Authors: Ashames Mohamad M. A. , Demir Ahmet , Gerek Omer N. , Fidan Mehmet , Gulmezoglu M. Bilginer , Ergin Semih , Edizkan Rifat , Koc Mehmet , Barkana Atalay , Calisir Cuneyt 
Published: April 2024

AbstractFollowing the great success of various deep learning methods in image and object classification, the biomedical image processing society is also overwhelmed with their applications to various automatic diagnosis cases. Unfortunately, most of the deep learning-based classification attempts in the literature solely focus on the aim of extreme accuracy scores, without considering interpretability, or patient-wise separation of training and test data. For example, most lung nodule classification papers using deep learning randomly shuffle data and split it into training, validation, and test sets, causing certain images from the Computed Tomography (CT) scan of a person to be in the training set, while other images of the same person to be in the validation or testing image sets. This can result in reporting misleading accuracy rates and the learning of irrelevant features, ultimately reducing the real-life usability of these models. When the deep neural networks trained on the traditional, unfair data shuffling method are challenged with new patient images, it is observed that the trained models perform poorly. In contrast, deep neural networks trained with strict patient-level separation maintain their accuracy rates even when new patient images are tested. Heat map visualizations of the activations of the deep neural networks trained with strict patient-level separation indicate a higher degree of focus on the relevant nodules. We argue that the research question posed in the title has a positive answer only if the deep neural networks are trained with images of patients that are strictly isolated from the validation and testing patient sets.