bluuebunny/crossref_metadata_2025 huggingface dataset:
Clinical Presentation of Frontal Sinus Squamous Cell Carcinoma in the Dog and Response to Treatment With Radiation Therapy in Eight Dogs
Authors: Loddo Pietro , Schiavo Luca , Dobson Jane , Marcinowska Ola
Published: January 2025

Primary frontal sinus squamous cell carcinoma (PFSSCC) represents a rare disease in dogs, and there is a general paucity of information in the current veterinary literature regarding its presentation and response to radiation therapy.

The objective of this retrospective observational study was to describe a series of dogs diagnosed with PFSSCC and report their response to radiation therapy.

Medical records of dogs with a diagnosis of PFSSCC were reviewed. Data collected included signalment, presenting complaint, clinicopathologic and diagnostic imaging findings, treatment, therapeutic response, and date of death or last follow‐up.

Eight cases of PFSSCC in dogs were treated with radiation therapy at the authors' institution. Three of these dogs were treated with coarse‐fractionated radiation therapy. One dog was euthanized due to an unrelated cause 36 months after completing the radiation therapy. The second and third dogs survived 18 and 3 months, respectively, from the end of treatment to death due to PFSCC. Five further dogs were treated with a more fractionated protocol (Monday–Wednesday–Friday schedule). The median survival time for all patients was 7.5 months (range 2–36 months).

Despite the small number of cases and variation in the radiation protocols used, the treatment outcomes in these eight dogs suggest that radiation therapy is potentially a viable treatment option for dogs with PFSSCC and that coarse fractionation might be an appropriate approach if more finely fractionated protocols are not possible.
New records of flowering plants for the flora of Laos (1)
Authors: WON Hyosig , KIM Joo Hwan , JANG Junhyung , SAYSAVANH Veosavanh
Published: January 2025

We are reporting 12 flowering plant species new for the flora of Laos, found during a botanical survey of Lao PDR in 2022–2023. These are Strobilanthes barbigera (Acanthaceae), Ceropegia tenuicaulis (Apocynaceae), Trichosanthes pilosa (Cucurbitaceae), Gaultheria discolor (Ericaceae), Ornithoboea puglisiae (Gesneriaceae), Beilschmiedia percoriacea (Lauraceae), Aspidopterys glabriuscula (Malpighiaceae), Cenocentrum tonkinense (Malvaceae), Peperomia tetraphylla (Piperaceae), Polygala karensium (Polygalaceae), Koenigia mollis (Polygonaceae), and Argostemma cordatum (Rubiaceae). In addition, new vouchers for three flowering plants species of Laos, Baeckea frutescens (Myrtaceae), Fagopyrum cymosum (Polygonaceae), and Sagittaria guayanensis (Potamogetonaceae), along with two alien species new to the flora of Laos, Ruellia simplex (Acanthaceae) and Polygala paniculata (Polygalaceae), are reported.
A checklist of Euphorbiaceae in Bhutan with a new record of the genus Sumbaviopsis
Authors: TSHERING Tsethup , WANGDI Karma , TENZIN Ugyen , WANGCHUK Rinchen , SHERUB Sherub , WANGCHUK Jigme
Published: January 2025

The Euphorbiaceae, known for their significant diversity, are particularly abundant in tropical regions and have undergone several taxonomic reclassifications. Bhutan’s lowland tropical forests remain the least explored in this family, creating a gap in the floral database. The genus Sumbaviopsis J. J. Sm., unrecorded in Bhutan, was encountered during a field visit. We report Sumbaviopsis albicans (Blume) J. J. Sm. as a new species record for Bhutan. Following recent taxonomic revisions and current newfound species, Bhutan now lists 41 species and 17 genera within Euphorbiaceae. This newly found species contributes to the country’s floristic database, enhancing the understanding of the biodiversity of the country.
Complete chloroplast genome of Eleutherococcus divaricatus var. chiisanensis (Araliaceae), an endemic Korean species
Authors: PARK Beom Kyun , LEE Se Ryeong , KIM Young-Soo , KANG Eun Su , SON Dong Chan
Published: January 2025

Eleutherococcus Maxim. belongs to the family Araliaceae, with approximately 40 species distributed in Eastern Asia and the Himalayan regions. Among these, Eleutherococcus divaricatus var. chiisanensis is distributed only in the central Korean Peninsula. The complete chloroplast (cp) genome sequence of Eleutherococcus divaricatus var. chiisanensis (Araliaceae) was determined to be 156,765 bp in length, consisting of large (86,592 bp) and small (18,239 bp) single-copy regions and a pair of identical inverted repeats (25,967 bp). The overall GC content of the chloroplast genome was 37.9%, and in the large singlecopy sequence, the small single-copy sequence, and each of inverted repeat sequences, the contents were 36.2%, 32%, and 43%, respectively. The genome consists of 132 genes, made up of 87 protein-coding genes, 37 tRNA genes, and eight rRNA genes. A cp genome phylogenetic analysis of the 12 taxa inferred from the cp genome revealed a close relationship between Eleutherococcus sessiliflorus and E. divaricatus var. chiisanensis<. The complete cp genome sequence of E. divaricatus var. chiisanensis provides important information for future phylogenetic and evolutionary studies of the genus Eleutherococcus.
Effect of text message reminders to improve paediatric immunisation rates: a randomised controlled quality improvement project
Authors: Rosen Kyra , Krelle Holly , King William C , Klapheke Nathan , Pina Paulo , Anderman Judd , Chung Alicia , Mendoza Felicia , Bagheri Ashley , Stadelman Jay , Tsuruo Sarah , Horwitz Leora Idit
Published: January 2025

Previous studies have demonstrated that text message reminders can improve pediatric vaccination rates, including low income & diverse settings such as those served by federally qualified health centers. In this study, we aimed to improve compliance with routine childhood immunizations via a text message intervention in a network of urban, federally qualified health centers at a large academic medical center. We targeted parents or guardians of children aged 0-2 years who were overdue or due within 14 days for at least one routine childhood immunization without a scheduled appointment. In Round 1, two versions of a text were compared to a control (no text). In subsequent Rounds, a new text was compared to a control (no text). In each round the content, wording, and frequency of texts changed. Subjects were randomized to receive a text (treatment group(s)) or to not receive a text (control group) in each round between 2020 and 2022. The primary outcome was whether overdue vaccines had been given by 12 week follow up. The secondary outcome was appointment scheduling within the 72 hours after text messages were sent. In Round 1 (n=1203) no significant differences were found between groups in overdue vaccine administration per group or per patient at follow up, or in appointment scheduling. In Round 2 (n=251) there was no significant difference in vaccine administration per group or per patient. However, significantly more patients in the intervention group scheduled an appointment (9.1% vs. 1.7%, p=0.01). In Round 3 (n=1034), vaccine administration was significantly higher in the intervention group compared to the control overall (7.0% vs. 5.5%, 0.016) and per subject (p=0.02). Significantly more patients in the intervention group scheduled an appointment compared to the control (3.3% vs. 1.2%, p=0.02). We found that text messaging can be an effective intervention to promote health service utilization such as pediatric vaccination rates, which although improved in this study, remain low.
Association between US city firearms dealers and firearm suicide rates, 2015–2021
Authors: OToole Megan J , Szkola Jay , Burd-Sharps Sarah , Kim Byoungjun , Spoer Benjamin R , Fingar Kathryn R
Published: January 2025

Background

Firearm suicides are more prevalent in cities than many recognise. Extant research—though conducted at different geographic levels or on different types of firearm deaths—suggests that firearms dealers may play a role in city firearm suicides. This study examines the relationship between rates of city firearms dealers and firearm suicides.

Methods

Data from the Center for Disease Control’s National Vital Statistical System and the Bureau of Alcohol, Tobacco, Firearms and Explosives’ Federal Firearms Listing included 284 cities in 2015–2021. Types, locations and rates of firearms dealers as well as firearm suicide rates were examined. Poisson regression models tested associations between city firearms dealer and firearm suicide rates, controlling for city characteristics. Models were stratified by city size and poverty level, and results were examined for firearms dealers overall and by type.

Results

Firearms dealer rates were highest in cities in the Midwest, South and West; with populations less than 500 000; and with the most veterans or white residents. Firearm suicide rates were 3.4 times higher in cities with the highest firearms dealer rates (9.8 per 100 000 population) than the lowest (2.9). In adjusted regression models, city firearms dealer rates were associated with firearm suicide rates, and results depended on dealer type, city size and poverty level.

Discussion and conclusions

City firearms dealers play an important role in access to lethal means, especially in small cities and through pawnshops. These findings hold implications for how cities can engage firearms dealers as suicide prevention partners.
Ethnic group, socioeconomic position and pregnancy outcome: a mediation model through latent class
Authors: Henderson Ian , Quenby Siobhan
Published: January 2025

Background

Preterm birth (PTB) and small-for-gestational-age (SGA) disproportionately affect women who are Black or Asian. Structural racism produces health inequalities. Identifying latent socioeconomic classes may help to understand the role socioeconomic position (SEP) plays in this inequality.

Methods

We included women from the baseline survey of the UK-based Millennium Cohort Study who had a live singleton pregnancy and gave birth from 1 September 2000 to 11 January 2002. Relative risks (RR) with 95% confidence intervals (CI) for PTB and SGA were estimated for ethnic groups compared with women who were white, with adjustment for SEP. Latent SEP classes were then identified using diverse prospective socioeconomic data. Mediation of health inequality via SEP and latent SEP class was tested.

Results

Among 17 701 included women, 6.7% (95% CI 6.2%, 7.1%) experienced PTB and 7.0% (6.5%, 7.5%) SGA. We found evidence that the association between ethnic groups and PTB was mediated by latent SEP class for women who were Bangladeshi, Black African, Black Caribbean and Pakistani, with indirect ‘effects’ of RR 1.08 (1.01, 1.16), 1.07 (1.01, 1.14), 1.06 (1.00, 1.12) and 1.06 (1.00, 1.13), respectively, relative to White. When using the simple measures of maternal education, household income and marital status, we found no evidence of mediation except for a potential protective effect among Indian women, relative to White. We found similar evidence for SGA, with indirect effects through latent SEP class of RR 1.35 (1.19, 1.52), 1.32 (1.17, 1.48), 1.26 (1.12, 1.41), 1.27 (1.13, 1.42), respectively. When using the simple measures, we found evidence of mediation only among Black African and Black Caribbean women, with RR 1.16 (1.04, 1.30) and 1.12 (1.00, 1.26), respectively, relative to White.

Conclusion

The determinants of inequality appeared to differ by ethnicity. We demonstrated the mediating role of individual-level SEP and a role for latent class analysis to interpret complex combinations of socioeconomic data.
Effect of radiotherapy exposure on fruquintinib plus sintilimab treatment in refractory microsatellite stable metastatic colorectal cancer: a prospective observation study
Authors: Cheng Mingxia , Jin Min , Yang Shengli , Zhao Lei , Yu Dandan , Lin Zhenyu , Li Pindong , Huang Chuying , Liu Junli , Wang Jing , Xue Jun , Ma Hong , Hu Jianli , Yang Kunyu , Zhang Tao , Liu Hongli
Published: January 2025

Background

Immune checkpoint inhibitors (ICIs) in combination with antiangiogenic drugs have shown promising outcomes in the third-line and subsequent treatments of patients with microsatellite stable metastatic colorectal cancer (MSS-mCRC). Radiotherapy (RT) may enhance the antitumor effect of immunotherapy. However, the effect of RT exposure on patients receiving ICIs and targeted therapy remains unclear. This study aimed to investigate the association between RT exposure and clinical responses to fruquintinib (a highly selective tyrosine kinase inhibitor of vascular endothelial growth factor receptor) plus sintilimab (an anti-programmed death 1 antibody; F&S) in previously treated patients with MSS-mCRC and to explore predictive biomarkers.

Methods

In this prospective observational study, patients with mCRC receiving F&S as third-line or subsequent treatment were enrolled. Eligible patients were divided into the RT cohort (RTC) and the non-RT cohort (NRTC) according to their RT history. The primary endpoint was the objective response rate (ORR). Secondary endpoints included disease control rate (DCR), progression-free survival (PFS), overall survival (OS), and safety. Pretreatment fecal and serum samples were collected for microbiome analysis, metabolome analysis, and immune signatures to identify biomarkers for treatment.

Results

A total of 55 patients were included, of which 25 were in the RTC and 30 in the NRTC. Better ORR (28.0% vs 6.7%, p=0.048), DCR (80.0% vs 36.7%, p=0.002), median PFS (6.2 vs 2.7 months, p<0.001), and median OS (14.8 vs 5.9 months, p=0.019) were noted in patients with RTC than those with NRTC. The enrichment ofLactobacillus,Bifidobacterium, and PC(20:5(5Z,8Z,11Z,14Z,17Z)/20:3(8Z,11Z,14Z)) in RTC significantly predicted better DCR and PFS, whereas guanosine and interleukin-10 predominated in patients with NRTC were negatively correlated with PFS and OS.

Conclusions

Patients with RT exposure benefited significantly from F&S in the third-line or subsequent treatment for MSS-mCRC. Gut microbiota, metabolites, and cytokines may help predict F&S outcomes for mCRC, which may be helpful in treatment decision-making.

Trial registration number

ClinicalTrials.gov identifier:NCT05635149.
Bleomycin sclerotherapy for venous vascular malformations of the tongue
Authors: Agid Noa , Itsekzon Ze'ev , Hendriks Eef J , Terbrugge Karel , Agid Ronit
Published: January 2025

Background

Venous vascular malformations (VVMs) are congenital vascular anomalies, often impacting quality of life due to discomfort, swelling, and functional impairments. This study evaluates the efficacy of bleomycin sclerotherapy as a treatment for symptomatic VVMs of the tongue.

Methods

We conducted a retrospective review of all patients treated with this method in our institution between 2004 and 2024. Sclerotherapy procedures were performed under general anesthesia in the neuroangiography suite with fluoroscopic guidance using a negative subtraction technique. Outcomes were assessed through subjective patient reports and magnetic resonance imaging (MRI) where available.

Results

In total, 140 percutaneous bleomycin sclerotherapy procedures were performed on 36 patients (aged 19–80) with tongue VVMs. On average, patients required 2.06±1.8 treatment sessions and 2.29±1.4 procedures per session. The average interval between treatment sessions was 28.6±19.4 months. Per procedure, the total units of bleomycin injected was 11.2±3.9 mg/mL (2–15 mg/mL). Results revealed that 93.8% of procedures yielded subjective symptom improvement. Follow-up imaging was available in 14 patients and confirmed lesion reduction in nine (64.3%). Post-procedural complications were minimal, with transient swelling as the most common.

Conclusion

Percutaneous bleomycin sclerotherapy presents an effective, well-tolerated treatment for tongue VVMs, offering significant symptom relief. To our knowledge, this study represents the largest retrospective series of bleomycin sclerotherapy for tongue VVMs to date. Our findings support bleomycin sclerotherapy as a valuable option for managing VVMs in this challenging anatomical site.
Detection and Diagnosis of ECH Signal Wearable System for Sportsperson using Improved Monkey-based Search Support Vector Machine
Authors: Grandhi Sri Harsha , Gudivaka Basava Ramanjaneyulu , Gudivaka Rajya Lakshmi , Gudivaka Raj Kumar , Basani Dinesh Kumar Reddy , Kamruzzaman M. M.
Published: January 2025

In the recent past, numerous frameworks have been designed to take decision support from samples for analyzing ECG signal data classification with wearable devices to prevent health risks in sports. As various frameworks permit a distinctive set of results, assessing the framework’s classification control in examination with other order frameworks or in correlation with human specialists is hard. The order precision is generally utilized as a measure of classification execution in this research. A novel hybrid Improved Monkey-based search (IMS) and support vector machine (SVM) technique have been designed and developed in this research for the health risk identification in ECGs. It incorporates handling of noise, extraction of signals, rule-based beat classification, and sliding window arrangement using a wearable device for the sportsperson. It can be executed continuously and can give clarifications to the analytic choices, and maximum scores have been acquired in terms of sensitivity and specificity (98.1% and 98.5% correspondingly using collective accuracy gross information, and 98.8% using aggregate average statistics, which has been shown in this research. Finally, experimental analysis has exposed that the hybrid Improved Monkey-based search (IMS) and support vector machine (SVM) technique achieve high precision (99.01%) in analyses of the heart rate for the sportsperson.
Educational Quality Evaluation Model Based on Deep Learning Theory
Authors: Yu Liu , Fang Wang
Published: January 2025

In order to solve the problem that the expression ability and generalization ability of shallow learning networks to complex functions are limited, and to improve the accuracy of college education quality evaluation, a college education quality evaluation method based on a deep learning network is proposed. Starting from the three aspects of the educational environment, educational quality, and student development, this paper constructs an educational quality evaluation index system including three primary indicators and nine secondary indicators. Take the secondary index in the evaluation index system as the input of the deep learning network, optimize the weights of each layer of the deep learning network by using the unsupervised pre-training model, determine the conditional probability distribution and joint probability distribution of each layer in the restricted Boltzmann machine (RBM) based on the bottom-up unsupervised learning process, and the output layer optimizes the parameters of each layer according to the input differential mean opinion score (DMOS) value and constructs the regression model between the abstract primary index and DMOS value, The objective evaluation results of education quality are obtained according to the prediction of a regression model. The test results show that the linear correlation coefficient and grade correlation coefficient between the evaluation results of this method and the subjective evaluation results are closer to 1.
Evaluation Mechanism of Patriotism Education for College Students based on Big Data Analysis in the Network Era
Authors: Ling Cai , Xiaowei Huang , Wenjuan Li
Published: January 2025

The network age has brought new opportunities and challenges for colleges and universities in conducting patriotism education for college students. To enhance the teaching quality of patriotism education, this paper presents research on an evaluation mechanism for college students’ patriotism education in the context of the network era. By examining the value logic, practical logic, and reality logic, it is suggested that patriotism education should be structured to ensure the practical transformation of students’ understanding of patriotism, highlighting the value-leading function, rational guarantee function, and reality-adjustment function. Based on the evaluation requirements for patriotism education under the network-age framework, and aligning with the college students’ patriotism education model, the clustering algorithm from big data analysis is chosen to develop an evaluation index system. This system encompasses classroom lectures, assignments, and themed websites. Using this index system, an evaluation model for patriotism education in the network age is constructed, with results generated through a fuzzy evaluation matrix. Experimental findings demonstrate that this approach is effective in evaluating patriotism education for college students and can significantly enhance the quality of its teaching.
Machine Learning-assisted Intelligent Teaching System (ML-ITS) for College Online English Learning
Authors: Yan Fang
Published: January 2025

The challenging characteristics of college online English learning for students are lack of communication, ineffective time management, and lack of social interaction. Employing Machine Learning (ML) to manage the classroom is a necessary trend in the evolution of English language instruction that will increase the level of instructor control in English language online instruction. Hence this paper, Machine Learning Assisted Intelligent Teaching System (ML-ITS) has been proposed to help ease the burden on English instructors while simultaneously enhancing students’ writing skills via practice. Additionally, the study integrates the location algorithm to find students in real time and builds the system function module via requirement analysis. It helps throughout the learning process at several stages, including creating tests, revising materials, receiving feedback to help improve, and analyzing performance. Furthermore, this research efficiently and promptly grasps the students’ learning state by analyzing their data using intelligent database processing. As this paper’s conclusion shows, the methodology put out here may ease the load on students and instructors while promoting change in English language instruction and quality-oriented higher education.¡Abs¿
Emotional Recognition of Crisis Groups in Sports Events Based on Cloud Computing
Authors: Zhongwei Liu , Peng Jianjie
Published: January 2025

In sports events, a large amount of data closely related to the event is generated due to the involvement of a wide range of audiences, media and participants. These data contain rich emotional information, reflecting the emotional tendencies of the group toward the event. Especially in the crisis of sports events, changes in group emotions have a significant impact on the direction and outcome of the event. Therefore, in order to effectively monitor and analyze the emotional dynamics in sports events, a cloud computing based method for identifying group emotions in sports event crises is proposed. By collecting data related to the event, including audience feedback, media reports and social media comments, and integrating these data into a unified cloud computing platform. Subsequently, the data are cleaned and denoised to eliminate irrelevant information and noise. In order to unify data formats and standardize processing, the optimal segmentation function is adopted, which adaptively segments data based on its characteristics and distribution, thereby improving the accuracy and efficiency of data processing. On this basis, extract features related to crisis emotion recognition in sports events and complete data preprocessing work. Next, based on the dynamic evolution structure of the development law of crisis public opinion in sports events, the weights of each indicator were calculated by constructing group emotion recognition indicators. These indicators and weights together constitute the group emotion recognition model in sports event crises. Through cloud computing technology, real-time monitoring and recognition of group emotions during sports event crises have been achieved. The experimental results show that the recognition trend using this method is highly consistent with the actual development trend of the event, demonstrating excellent stability and convergence. By comparing the average fitness and mean square error of different methods, it was found that the recognition performance of this method is significantly better than other methods in the reference literature. In the recognition results of specific competition events, the recognition results of this method are completely consistent with the actual situation, accurately identifying positive and negative emotions in the actual situation. In addition, this method can effectively identify athletes’ emotional tendencies in different types of competitions, and has good robustness and practical application value. Therefore, this method provides a more reliable and effective tool for research and application in related fields, with broad application prospects.
Deep Learning on Network Traffic Prediction: Recent Advances, Analysis, and Future Directions
Authors: Aouedi Ons , Le Van An , Piamrat Kandaraj , Ji Yusheng
Published: January 2025

From the perspective of telecommunications, next-generation networks, or beyond 5G, will inevitably face the challenge of a growing number of users and devices. Such growth results in high-traffic generation with limited network resources. Thus, the analysis of the traffic and the precise forecast of user demands is essential for developing an intelligent network. In this line, Machine Learning (ML) and especially Deep Learning (DL) models can further benefit from the huge amount of network data. They can act in the background to analyze and predict traffic conditions more accurately than ever and help to optimize the design and management of network services. Recently, a significant amount of research effort has been devoted to this area, greatly advancing network traffic prediction (NTP) abilities. In this article, we bring together NTP and DL-based models and present recent advances in DL for NTP. We provide a detailed explanation of popular approaches and categorize the literature based on these approaches. In addition, as a technical study, we conduct different data analyses and experiments with several DL-based models for traffic prediction. Finally, discussions regarding the challenges and future directions are provided.
Feature-Oriented Modelling and Analysis of a Self-Adaptive Robotic System
Authors: Päßler Juliane , ter Beek Maurice H. , Damiani Ferruccio , Dubslaff Clemens , Johnsen Einar Broch , Tapia Tarifa Silvia Lizeth
Published: January 2025

Improved autonomy in robotic systems is needed for innovation in, e.g., the marine sector. Autonomous robots that are let loose in hazardous environments, such as underwater, need to handle uncertainties that stem from both their environment and internal state. While self-adaptation is crucial to cope with these uncertainties, bad decisions may cause the robot to get lost or even to cause severe environmental damage. Autonomous, self-adaptive robots that operate in uncontrolled environments full of uncertainties need to be reliable! Since these uncertainties are hard to replicate in test deployments, we need methods to formally analyse self-adaptive robots operating in uncontrolled environments. In this paper, we show how feature-oriented techniques can be used to formally model and analyse self-adaptive robotic systems in the presence of such uncertainties. Self-adaptive systems can be organised as two-layered systems with a
managed
subsystem handling the domain concerns and a
managing
subsystem implementing the adaptation logic. We consider a case study of an autonomous underwater vehicle (AUV) for pipeline inspection, in which the managed subsystem of the AUV is modelled as a family of systems, where each family member corresponds to a valid configuration of the AUV which can be seen as an operating mode of the AUV’s behaviour. The managing subsystem of the AUV is modelled as a control layer that is capable of dynamically switching between such valid configurations, depending on both environmental and internal uncertainties. These uncertainties are captured in a probabilistic and highly configurable model. Our modelling approach allows us to exploit powerful formal methods for feature-oriented systems, which we illustrate by analysing safety properties, energy consumption, and multi-objective properties, as well as performing parameter synthesis to analyse to what extent environmental conditions affect the AUV. The case study is realised in the probabilistic feature-oriented modelling language and verification tool ProFeat, and in particular exploits family-based probabilistic and parametric model checking.
Effect of Short‐Term Stress and Interaction of Salinity and Ammonia‐N Levels, Associated With Food Deprivation on Fatty Acid Profile and Body Composition in Nile Tilapia (Oreochromis niloticus)
Authors: Ebrahimi Eisa , Motamedi-Tehrani Javad , Peyghan Rahim
Published: January 2025

High levels of nitrogen compounds can lead to acute toxicity in aquatic organisms. Ammonia, a by‐product of protein breakdown, is the most prevalent contaminant in freshwater environments. Increasing salinity in water sources can cause fluctuations in salinity levels within breeding ponds. The interaction of these elements can occur in breeding ponds, significantly impacting the physiology and quality of the aquatic products. The purpose of this study was to examine the relationship between salinity and ammonia‐N stress and their effects on the quality and fatty acid profile of tilapia fish (Oreochromis niloticus). The fish were divided into 12 distinct treatment groups, each characterized by varying salinity levels (0, 4, 8, and 12 ppt) and different concentrations of ammonia‐N (0, 50% of 50% lethal concentration [LC50]‐96 h, and 30% of LC50‐96 h) arranged in a factorial design. The calculated LC50‐96 h for ammonia‐N was 0.86 mg/L. Significant increases were observed in cortisol and glucose levels associated with various salinity treatments and ammonia levels. The levels of carcass protein in the salinity treatments (4, 8, and 12 ppt) did not show any significant differences when compared to the control treatment. However, the protein percentage at 50% of LC50‐96 h of ammonia‐N was lower than that of the control treatment. In salinity treatments and ammonia levels (50% and 30% of LC50‐96 h of ammonia‐N), a significant increase in the percentage of lipid, highly unsaturated fatty acids (HUFA), eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA) was observed. To draw the conclusion, our assessment indicates that a salinity concentration of 8 ppt over a 96‐h period without feeding has produced positive effects on the quality of tilapia carcasses.
Selection of Nonlethal Early Biomarkers to Predict Gilthead Seabream (Sparus aurata) Growth
Authors: Angelakopoulos Rafael , Tsipourlianos Andreas , Moutou Katerina A. , Fytsili Alexia E. , Tsingene Anthi , Galliopoulou Eleni , Papaharisis Leonidas , Mamuris Zissis , Giannoulis Themistoklis , Dimitroglou Arkadios
Published: January 2025

One of the main challenges in aquaculture is the constant search for sustainable alternative feed ingredients that can successfully replace fishmeal (FM) without any negative effects on fish growth and health. The goal of the present study was to develop a toolbox for rapidly anticipating the dynamics of fish growth following the introduction of a new feed; nonlethal, biochemical, and molecular markers that provide insights into physiological changes in the fish. A nutritional challenge by feeding a conventional feed rich in FM protein (FM diet) versus an experimental feed rich in plant protein (PP) and low FM inclusion (PP diet), in 20 different families of gilthead sea bream (Sparus aurata) was performed. Fifteen and 30 days after the initiation of the nutritional challenge, the transcriptional response of gilthead seabream erythrocytes along with classical hematological biochemical markers were compared. Zootechnical, biochemical, and transcriptome data from each family under different dietary treatments were combined into a classification model to identify variables that can predict the growth rate at the end of the 14‐month farming period (July 2018–September 2019). A highly accurate model was produced (A > 80%) based on the combination of seven markers (five molecular and two biochemical markers) and with high potential in separating faster and slower growing fish as early as 30 days after the initiation of feeding.
Effect of Salinity on Nursery Bi‐Culture of Pacific White Leg Shrimp (Litopenaeus vannamei) and Giant Prawn (Macrobrachium rosenbergii) in a Biofloc System
Authors: Halim Md. Abdul , Aziz Dania , Arshad Aziz , Wong Nur Leena W. S. , Karim Murni , Islam Md. Ariful , Syukri Fadhil , Rahi Md. Lifat
Published: January 2025

The current study was carried out to examine the effects of four different experimental salinities (T1 = 0‰, T2 = 5‰, T3 = 10‰, and T4 = 15‰) on growth, water quality, proximate composition, total bacterial (TB), and hemocyte counts of white leg shrimp (Litopenaeus vannamei) and giant prawn (Macrobrachium rosenbergii) in biofloc based nursery bi‐culture system for 6 weeks. A total of 12 cylindrical plastic tanks (125 L) filled up 100 L water for rearing L. vannamei and M. rosenbergii post‐larvae (PLs) at an equal ratio: (50 L. vannamei: 50 M. rosenbergii). At the end of the experiment, for L. vannamei, the significantly higher (p < 0.05) growth rate was recorded in T4 (15‰) compared to the other treatments. For M. rosenbergii, a significantly higher (p < 0.05) growth rate was recorded in T2 (5‰) than in other treatments. Similar to growth, the best (p < 0.05) feed conversion ratio (FCR) for ‐L. vannamei was found at T4 (15‰) while it was at T2 (5‰) forM. rosenbergii. Gross return, net profit, and benefit–cost ratio (BCR) analysis revealed higher profit T4 (15‰) than T3 (10‰), T2 (5‰), and T1 (0‰). TB counts were found to be significantly greater (p < 0.05) in T4 than other treatments. Hemocyte counts for L. vannamei were significantly higher (p < 0.05) in T4 (15‰) than T3 (10‰), T2 (5‰), and T1 (0‰) and for M. rosenbergii hemocyte was significantly higher (p < 0.05) in T1 (0‰) than T2 (5 ‰), T3 (10 ‰), and T4 (15‰). Therefore, it can be suggested that 15‰ salinity will be the best condition for the nursery bi‐culture of white leg shrimp (L. vannamei) and giant prawn (M. rosenbergii) in the biofloc system.
Evaluation and Comparison Germplasm Resource of Two Species of Macrobrachium in China (M. hainanense and M. nipponense)
Authors: Eddine Khadraoui Djamel , Gao Zijian , Daka Peter , Zhang Wenyi , Jiang Sufei , Xiong Yiwei , Qiao Hui , Fu Hongtuo
Published: January 2025

The Macrobrachium genus thrives in freshwater and brackish environments. M. hainanense, a nocturnal freshwater prawn, is economically significant in China due to its delicious meat and rich nutrition. Its distribution is limited to regions like Zhejiang, Guangdong, Guangxi, Fujian, and Hainan due to breeding habits near estuaries and low‐temperature tolerance. Despite its economic importance, there are limited studies on M. hainanense, particularly regarding its germplasm resources. This study investigates the growth traits, nutritional composition, enzyme activity, and genetic diversity and structure of seven M. nipponense populations and three M. hainanense populations to inform sustainable aquaculture and conservation efforts, comparing them with the new hybrid varieties of M. nipponense, which successfully cultivated, Because of its fast growth, high adaptability, and strong reproductive capacity was chosen as a control sample due to its well‐established quality, economic value, reputation, ensuring competitive comparison. The amino acids, fatty acids, and physiological and biochemical indicators among M. hainanense populations and M. nipponense populations showed significant differentiation. M. hainanense populations showed minor differences in nutritional components except for total sugar and astaxanthin content that were significantly different, whereas M. nipponense populations showed almost no differences. Essential amino acids in M. hainanense comprised 34.42%–37.53% of the total amino acid content. Differences in glycine, isoleucine, and cystine were notable in M. hainanense, while glycine and proline differed in M. nipponense. Fatty acid components varied among the populations studied. Genetic diversity analysis revealed that the polymorphism information content (PIC) values for M. hainanense were higher than those for M. nipponense. The Changhua River (CH) and Nandu River (ND) populations of M. hainanense had the lowest nucleotide diversity, while the Oujiang River (OU) population had the highest. The OU population also exhibited the greatest genetic diversity, with the lowest inbreeding coefficient, while the CH population had the highest. There was slight genetic differentiation among M. hainanense populations, with geographical isolation and artificial selection contributing to genetic structure differences. This study is the first to examine population‐wide genetic variability in M. hainanense, highlighting the need for comprehensive conservation and breeding strategies to maintain and enhance genetic variability in this species. The study concludes that both M. hainanense and M. nipponense have rich protein content and low‐fat content, with varied genetic relationships and differentiation among populations.
Identification and Characterization of a Protease Producing Bacillus cereus Strain From Tannery Waste for Efficient Dehairing of Goat Skin
Authors: Uddin Md. Ekhlas , Sheikh Md. Ramjan , Asaduzzaman Md. , Ahmed Sohel , Kundu Sukalyan Kumar , Sina Abu Ali Ibn
Published: January 2025

Environmental pollution has been a significant concern for the last few years. The leather industry significantly contributes to the economy but is one of Bangladesh’s most prominent polluting industries. It is also responsible for several severe diseases such as cancer, lung diseases, and heart diseases of leather workers because they use bleaching agents and chemicals, and these have numerous adverse effects on human health. The study was aimed at isolating, identifying, and molecularly characterizing bacteria that produce protease enzymes that are highly capable of dehairing goat hide. Several attempts were made to isolate and identify protease‐producing bacterial strains from different soil samples of tannery wastes. Initially, a total of four isolates were selected from tannery soil. After the different phenotypic and morphological characterization, one isolate (BS2) showed Gram‐positive, rod‐shaped, and spore‐forming characteristics and could produce novel hair‐degrading protease enzymes. The growth profile and protease activity of the bacteria at 37°C were observed; a basal level of extracellular protease increased with time. The enzyme’s proteolytic activity was measured, and the unit of enzyme activity of the enzyme sample was 18.1. The ExPASy server (ProtParam) tool was used to estimate the physicochemical characteristics of the proteins and found molecular weight (MW) (7375.94 Da), aliphatic index (71.56), instability index (II, 80.63), Grand Average of Hydropathy (GRAVY) (−0.231), and isoelectric point (11.41). The protein–protein interactions (PPI) networks were generated using the Search Tool for the Retrieval of Interacting Genes (STRING) database and Cytoscape software. The PSIPRED v.4.0 and SAVES v.6.0 programs were used to determine the secondary and three‐dimensional assembly of the selected protein. They found alpha helix (16, 25.00%), extended strand (6, 9.38%), beta‐turn (5, 7.81%), and random coil (37, 57.81%). DNA isolation and purification were carried out, and the purity ratio was ~2.17 at 260 and 280 nm. Polymerase chain reaction (PCR) for amplifying the 16S rRNA gene was conducted, and the isolate was authentically recognized as Bacillus cereus (BS2) based on morphological, biochemical, and molecular analyses. The quantitative assessment has shown that 40 mL of culture centrifugation could dehair 2 × 1 cm of goat leather sample in 9 h. This potential bacterial strain can be used in the leather industry as an ecofriendly alternative to chemical dehairing, which can reduce environmental pollution and the risk of severe diseases among leather industry workers.
Optimizing Edible Sorghum Bowls: Effects of Roasting and Edible Flower Powder Enhancement on Technological, Nutritional, Antioxidant, and Functional Properties
Authors: Manivel Devatha , Paramasivam Raajeswari , Roy Swarup
Published: January 2025

The widespread reliance on single‐use plastics (SUPs) has fostered a global throwaway culture, especially in the food packaging industry, where convenience and low cost have driven their adoption, posing serious environmental threats, particularly to marine ecosystems and biodiversity. Edible and ecofriendly packaging made from millet, specifically sorghum (Sorghum bicolor (L.) Moench), is a promising solution to mitigate SUP consumption and promote sustainability. This study explores the development of edible sorghum bowls, enhanced through roasting and incorporating 3 g of hibiscus and rose flower powders. The standardized sorghum bowl was analyzed for nutritional value; optical, technological, functional, and mechanical properties; and shelf life, and the results were discussed. The bowls, 18.5 g of average weight, dimensions of 10.2 cm, and a thickness of 3 mm, were baked in a unique bowl‐shaped mold at 80°C for 7 min. Enhancing the bowls with flower powder improved their optical properties and nutrient content. The addition of flower powder also increased phytochemical levels, according to qualitative analysis, while roasting sorghum reduced tannin and phytic acid content. The IC50 values revealed that hibiscus (47.74 mg/mL) and rose (39.87 mg/mL) enrichment boosted antioxidant activity. Sensory evaluations favored roasted bowls across all attributes, while Fourier transform infrared spectroscopy (FTIR) and thermogravimetric analyzer (TGA) analyses confirmed significant structural changes. The enhanced bowls exhibited greater hardness and hold hot or cold snacks for 90 min without compromising structural integrity. Additionally, these bowls demonstrated an extended shelf life, low microbial count (1 × 101CFU/g), reduced toxicity (3%–10% mortality in brine shrimp assays), and complete biodegradation within 15 days in wet soil. These findings indicate that sorghum‐based edible bowls present a nutritious, viable, less toxic alternative to SUPs, appealing to a broad demographic, especially in the food and tourism sector, and contributing to environmental conservation by reducing plastic waste and suitable for wide consumption.
Classification of Severity of Lung Parenchyma Using Saliency and Discrete Cosine Transform Energy in Computed Tomography of Patients With COVID‐19
Authors: Tello-Mijares Santiago , Flores Francisco , Woo Fomuy
Published: January 2025

This study proposes an automated system for assessing lung damage severity in coronavirus disease 2019 (COVID‐19) patients using computed tomography (CT) images. These preprocessed CT images identify the extent of pulmonary parenchyma (PP) and ground‐glass opacity and pulmonary infiltrates (GGO‐PIs). Two types of images—saliency (Q) image and discrete cosine transform (DCT) energy image—were generated from these images. A final fused (FF) image combining Q and DCT of PP and GGO‐PI images was then obtained. Five convolutional neural networks (CNNs) and five classic classification techniques, trained using FF and grayscale PP images, were tested. Our study is aimed at showing that a CNN model, with preprocessed images as input, has significant advantages over grayscale images. Previous work in this field primarily focused on grayscale images, which presented some limitations. This paper demonstrates how optimal results can be obtained by using the FF image rather than just the grayscale PP image. As a result, CNN models outperformed traditional artificial intelligence classification techniques. Of these, Vgg16Net performed best, delivering top‐tier classification results for COVID‐19 severity assessment, with a recall rate of 95.38%, precision of 96%, accuracy of 95.84%, and area under the receiver operating characteristic (AUROC) curve of 0.9585; in addition, the Vgg16Net delivers the lowest false negative (FN) results. The dataset, comprising 44 COVID‐19 patients, was split equally, with half used for training and half for testing.
Ultrasonication‐Induced Modification of Finger Millet and Barnyard Millet Flours: Phytoconstituents and Antioxidant Capacity, Functional Properties, and Microstructural Arrangement
Authors: Bhandari Manisha , Sharma Rajan , Bobade Hanuman , Sharma Savita , Pathania Shivani
Published: January 2025

The current study is aimed at studying the effect of ultrasonication on finger millet and barnyard millet flours which were processed for 10, 15, and 20 min at a constant amplitude of 30% and 30 kHz frequency at a maximum power of 750 W and 220 V. Ultrasonication resulted in modification of functional, structural, color, thermal, and molecular interactions and bioactive properties of millet flours. Ultrasonication resulted in decrement of water absorption capacity (1.51–1.36 and 1.51–1.05 g/g), swelling power (7.68–5.34 and 5.87–4.50 g/g), and foaming stability, while an increment was observed in water solubility index (3.59–8.41% and 3.03–10.94%), oil absorption capacity (1.98–2.16 g/g and 1.93–2.07 g/g), foaming capacity (12.00–17.00% and 18.00–25.00%), and paste clarity (51.20–61.00%T and 58.50–63.60%T) in finger millet and barnyard flours. An increase in bioactive components was observed till 15 min was observed, followed by reduction on further treatment. Ultrasonication triggers cavitation, which causes cell wall fractures and subsequent breakdown, ultimately reducing particle size. The resulting particle size reduction increases the surface area, enhancing functional properties. Ultrasonication reduced the enthalpy of millet flours by disrupting amorphous regions. Concurrently, processing altered surface topography, modified functional groups, and changed crystal structure. Also, the antinutritional factors (phytates and tannins) were reduced linearly on an increase in the time period of ultrasonication. This study shows that ultrasonication improves the functional properties of finger millet and barnyard millet flours.
Dynamic Vibration Characteristics and Mitigation of the Stress‐Ribbon Bridge by Using a Rail‐Damper System
Authors: Xu Kun , Wang HanShuo , Wang Meng , Liu Bin , Nagarajaiah Satish , Han Qiang
Published: January 2025

Due to its simple and beautiful architectural appearance, the stress‐ribbon bridge (SRB) has been gradually built around the world as a pedestrian or traffic bridge. However, as characterized by low bending stiffness and low damping ratio features, SRB is prone to the dynamic effects of external excitations, such as pedestrians, vehicles, and/or winds. To control the vertical vibration of the SRB, a rail‐damper system is proposed in this study. In the proposed scheme, the rotation of the handrails triggered by the flexural deformation of the SRB is utilized to drive the viscous dampers installed between the adjacent handrails. The governing equations of the proposed control system are established. The key design parameters and their influences on the dynamic properties of the control system are systematically investigated. The control performances of the proposed rail‐damper system are further investigated through an SRB numerical model subjected to pedestrian excitations. It is discovered that the rail‐damper system can offer considerable supplemental damping to the structural modes through reasonable design, achieving satisfactory control performances. To gain the excellent effect of the proposed rail‐damper system in real applications, a nondimensional rail stiffness of no less than 1000 is recommended, and the stiffness of the damper should be controlled as small as possible.