bluuebunny/crossref_metadata_2025_split huggingface dataset:
Detection of Woody Breast Condition in Broiler Breast Fillets Using Light Scattering Imaging
Authors: Cai Jiaxu , Lu Yuzhen 
Published: January 2025

HighlightsBroadband light scattering images were acquired from broiler breast fillets affected with woody breast (WB).Both deep-learning-based and hand-crafted features were extracted from scattering images for model development.The hand-crafted scattering image features performed better in differentiating normal from WB-affected samples.An overall accuracy of 92.3% was achieved by the model based on selected hand-crafted scattering features.Abstract. Muscular myopathies such as woody or wooden breast, which impair the eating quality and marketability of poultry products, are threatening the profitability of poultry industries worldwide, with an estimated annual loss exceeding $500 million for the United States (U.S.) poultry industry. WB-affected fillets are characterized by abnormal tissue hardness and muscle rigidity with varying degrees of severity. The assessment of WB conditions at processing facilities currently relies on tactile palpation combined with a visual examination by trained personnel. This approach is subjective, labor-intensive, costly, and may induce contamination due to physical contact. Optical imaging technology offers a promising alternative for objective and non-invasive quality assessment of broiler meat. This study presents a novel investigation of light scattering imaging (LSI) that captures light-scattering characteristics of meat tissues for the detection of WB conditions in broiler breast fillets. Broadband scattering images, induced under the illumination of a highly focused broadband light beam, were acquired from broiler meat samples. Two types of image features, i.e., (1) deep-learning-based and (2) hand-crafted scattering features, were extracted for building classification models using regularized linear discriminant analysis to differentiate samples into two categories, i.e., “Normal” (no WB) and “Defective” (WB-affected). Deep-learning-based features yielded an overall classification accuracy of 80.4%, while an accuracy of 91.7% was obtained by hand-crafted scattering features, representing a significant improvement of 11.3% (P &lt; 0.01). Furthermore, feature reduction approaches, including MRMR (minimum redundancy maximum relevance) and PCA (principal component analysis), were conducted to reduce the model complexity, leading to a further accuracy improvement to 92.3% with the top-ranked 65 features identified by MRMR and 25 principal components (PCs), respectively. This study has demonstrated the LSI technique is promising for WB assessment of broiler breast meat. Keywords: Light scattering, Machine learning, Optical imaging, Poultry, Woody breast.
Optimization of Material Removal Rate and Electrode Wear Rate in EDM Machining of D2 Steel Using Al–Cu–SiC Nanocomposite Powder Metallurgy Electrodes: a Taguchi and ANN-based Approach
Authors: K. Reetabai  , V. Naveenprabhu  , Rajesh Mohan  , Vinitha Nithianantharaj  , Venkat Prasat Sridhar  , S. Naveen  , Justin Sam George  
Published: January 2025

In this research study, a novel Al–Cu–SiC composite tool, created using the powder metallurgy (P/M) technique, was used for the electrical discharge machining of D2 steel, and the effects of important process parameters were investigated. The experimental runs were organized using a Taguchi-based design, and prediction models were constructed using artificial neural network techniques. This study was focused on machining performance, employing material removal rate (MRR) and electrode wear rate (EWR) as essential performance indicators and peak current, dielectric flushing pressure, and pulse on time as crucial input parameters. To evaluate the significance and suitability of the regression models created, an Analysis of Variance was conducted. The results showed that Al–Cu–SiC P/M electrodes were more sensitive to peak current and pulse duration. Increasing pulse duration significantly influenced MRR and EWR, with optimal values (MRR of 0.5880 g/min and minimal EWR) attained at a current of 9 A and a pulse length of 80 μs. Taguchi analysis identified pulse duration as the primary determinant; Regression equations emphasized pulse duration and current as critical factors for MRR, whereas ANN optimization effectively forecasted EDM results (R > 0.97), demonstrating decreased errors and reliable model performance across datasets.
Impact of Tool Pin Profiles and Nanopowder Addition to Nugget Zone on FSW of Aluminum Alloys
Authors: R. Chandana  , K. Saraswathamma  
Published: January 2025

Friction stir welding (FSW) process is a type of solid-state welding process. FSW is preferred due to no chemical reaction, melting, secondary phase formation and microstructure-controlled process. The absence of smoke and spark can be categorized as an eco-friendly welding process. In this work, the FSW process is carried out on AA 2024 and AA 7075 aluminum alloys with Al2O3 filled in the nugget zone. The micro hole is performed before welding on the nugget zone to fill nanoparticle addition. Process parameters considered are tool pin profile, tool rotational speed, and welding speed. Three different types of tool pin profiles are considered namely square, hexagon and circular in cross-section. Taguchi L9 experimental steps are followed to perform the experiments. Performance parameters considered are tensile strength, bending strength and micro hardness of the welded sample. The performance of FSW samples is influenced by material mixing, which is significantly influenced with tool pin profile. Tool pin profile is directly influenced by contact area, material mixing, fine refined structure and appropriate heat. The result of experimentation is understood as better pulsating action, stir action and material mixing with hexagon pin profile and nano Al2O3 filled in the nugget zone. Characterization study is carried out on wedded area on FSW sample to evaluate microstructure changes to realize the weld quality. It is noticed that fine refinement structure after FSW and provides good mechanical properties.
Enabling ROADM in mode division multiplexing networks with mode-selective switches
Authors: Sajjanam Morrison Sunami , Safaee S. Mohammad Reza , Ma Zhaoqi , Rogers Rebecca , Gostimirovic Dusan , Rahbardar Mojaver Kaveh , Liboiron-Ladouceur Odile 
Published: January 2025

Mode division multiplexing (MDM) enhances optical communication systems by introducing an additional multiplexing dimension. We designed and validated a reconfigurable optical add/drop multiplexer (ROADM) prototype using MDM as an optical subsystem targeting data center interconnects and metro optical networks. Our MDM-ROADM employs a mode-selective switch at each node, selectively de/multiplexing the first three transverse-electric (TE) modes. Key components are based on 220 nm silicon photonics, using subwavelength grating structures and inverse design methodology. Machine learning-based fabrication correction, via our tool PreFab, improved mode selectivity by 57% for mode-selective thermo-optic phase shifters. We also developed mode filters for two modes with a crosstalk of −9dB for TE0 and −15dB for TE1 within a 35 nm wavelength range. Experimental validation using TE0 and TE1 modes at 1555 nm shows an aggregate payload transmission of 80 Gb/s NRZ and a PAM-4 transmission at 40 Gbaud with a bit error rate of 1.1×10−9 and 3.8×10−3, respectively.
Graphene-assisted electromagnetically induced transparency-like terahertz bio-sensor for ultrasensitive detection using optics-enhanced sensing
Authors: Wang YaRu , Yao HaiYun , Liang LanJu , Yan Xin , Wang ZiQun , Hu XiaoFei , Li ZhenHua , Li YuanPing , Lv YiYing , Yang Qi Li 
Published: January 2025

In recent years, biosensors based on terahertz metamaterials have emerged as a prominent area of research. However, studies focusing on enhancing biosensing performance through optical pumping to improve sensitivity are scarce. This paper proposes a graphene-based electromagnetically induced transparency-like (EIT-like) optics-enhanced terahertz metamaterials biosensor. Using this biosensing platform, we successfully detected glycine through amplitude modulation, achieving a limit of detection (LOD) of 1 pg/mL. Additionally, we developed an optics-enhanced sensing method where the conductivity of graphene is reduced, resulting in a significant increase in the amplitude of the device's transmission spectrum as optics-enhanced. Experimental results demonstrate that the change in the transmission amplitude at varying concentrations exhibits a quasi-linear relationship as the optical-energy-density is varied from 0 µJ/cm2 to 119.7 µJ/cm2. For a low concentration of glycine (32 pg/mL), the optics-enhanced sensing peak amplitude rate of change (AR) reached a maximum of 857.5% at an optical-energy-density of 119.7 µJ/cm2. Furthermore, the graphene-based terahertz metasurfaces biosensor (Gra + Ms) successfully detected a glycine concentration of 1 pg/mL, which would have been undetectable in the absence of optics. These findings suggest that the sensitivity of the Gra + Ms sensor is significantly enhanced under the optical pumping, allowing for more precise detection of low glycine concentrations. This study offers a promising new direction for the practical application of terahertz metamaterials in biosensing.
Participatory research towards the control of snakebite envenoming and other illnesses in a riverine community of the Western Brazilian Amazon
Authors: Santos Alícia Patrine Cacau , Silva Evellyn Antonieta Rondon Tomé , Gama Hiran Sátiro Souza da , Cordeiro Jady Shayenne Mota , Oliveira Ana Paula Silva , Araújo Jéssica Albuquerque , Dávila Rafaela Nunes , Amazonas Júnior Hélio Afonso , Farias Altair Seabra , Sachett Jacqueline Almeida Gonçalves , Machado Vinícius Azevedo , Monteiro Wuelton Marcelo , Murta Felipe Leão Gomes 
Published: January 2025

Background
Riverine communities face various health problems, which involve geographical and cultural barriers to accessing care, in addition to a lack of financial investments in services aimed at these communities, resulting in a process of invisibility for the population living in these regions. In this scenario, the significant burden of snakebite envenoming (SBE) highlights the need for participatory research to address ways to minimize this situation. Thus, this study aimed to describe the priority health problems identified by this population and the ranking of SBEs in that context, mapping solutions according to the local reality.

Methodology/Principal findings
This study was conducted in Limeira, a riverine community located in Tabatinga, in the extreme Western Brazilian Amazonia, on the borders with Peru and Colombia. The research lasted approximately one year, from 2021 to 2022.It is a participatory study that followed three steps: baseline assessment of the community, community assembly, and final data analysis.
The study included a total of 42 participants in the sociodemographic survey, which served as the basis for the subsequent stages of data collection. Of these 42 individuals, 32 participated in the qualitative interviews, and 20 took part in the community assembly. Participants emphasized snakebite envenoming as a significant health issue, though not the only one, and reported frequent encounters with snakes, underscoring its severity as a concern. The qualitative analysis identified three main themes: Snakebites in the Community, which focused on personal experiences with snakes; Common Health Problems, which addressed other health issues faced by community members; and Community Defining Solutions, which discussed strategies and solutions proposed by the community to address these challenges.

Conclusions/Significance
Improvements in health care delivery to populations living in Amazonian communities are possible with the judicious use of tested integrated interventions, particularly when the community identifies various concurrent health problems. SBE control programs in remote areas of the Brazilian Amazon should be planned with a multidisciplinary and intercultural approach, preferably integrated with broader interventions that address the population’s needs for a range of health issues.
Characteristics influencing COVID-19 testing and vaccination among Spanish-speaking Latine persons in North Carolina
Authors: Aguilar-Palma Sandy K. , McCoy Thomas P. , Mann-Jackson Lilli , Alonzo Jorge , Jibriel Mohammed Sheikh Eldin , Johnson Dorcas Mabiala , Locklear Tony , Tanner Amanda E. , Hall Mark A. , Bertoni Alain G. , Sucaldito Ana D. , Russell Laurie P. , Rhodes Scott D. 
Published: January 2025

Background
Latine populations in the United States continue to be disproportionately affected by COVID-19 with high rates of infection and mortality. Our community-based participatory research partnership examined factors associated with COVID-19 testing and vaccination within a particularly hidden, underserved, and vulnerable population: Spanish-speaking Latines.

Methods
In 2023, native Spanish-speaking Latine interviewers conducted phone-based structured individual assessments with 180 Spanish-speaking, predominantly immigrant Latines across North Carolina. We used univariate and multivariable logistic regression analyses to examine associations between participant characteristics and COVID-19 testing and vaccination.

Results
Participant mean age was 41.7 (SD = 13), and 77.2% of the sample reported being cisgender women. Most participants reported immigrating from Latin American countries (89.9%), being uninsured (66.1%), and lacking US immigration documentation (51.1%). While most reported ever being COVID-19 tested (83.3%) and ever being vaccinated against COVID-19 (84.4%), only 24% were up to date with vaccination. Nearly half of the sample reported one or more barriers to COVID-19 testing, and over one-quarter reported one or more barriers to COVID-19 vaccination. Higher educational attainment was significantly associated with ever being tested (P = .031). Fewer concerns about the vaccine, including fewer worries about side effects and having more confidence in vaccine effectiveness and safety, was associated with ever being vaccinated (P < .001).

Conclusions
Spanish-speaking Latines face barriers to getting tested and vaccinated against COVID-19. Although ever testing and ever vaccination rates were high, being up to date with recommended vaccinations was low. Educational attainment and concerns about the vaccine were associated with COVID-19 testing and vaccination, respectively. Our findings suggest the need for culturally congruent strategies to address the challenges facing Spanish-speaking Latines in the United States.
Anti-oxidation enhancement, inflammation alleviation, and microbial composition optimization of using tussah (Antheraea pernyi) silk fibroin peptides for hyperglycaemia remission
Authors: Mi Rui , Li Xuejun , Li Yajie , Du Xingfan 
Published: January 2025

Objective
This study aimed to evaluate the positive effects on anti-oxidation, anti-inflammation, and microbial composition optimization of diabetic mice using tussah (Antheraea pernyi) silk fibroin peptides (TSFP), providing the theoretical foundation for making the use of silk resources of A. pernyi and incorporating as a supplement into the hypoglycemic foods.

Method
The animal model of diabetes was established successfully. Alloxan-induced diabetic mice were orally administered using TSFP, and the hypoglycaemic effects in vivo were systematically investigated.

Results
The results indicated that TSFP could significantly reduce the fasting blood glucose (FBG) levels and suppress the mRNA expression of glycometabolism genes of diabetic mice. In addition, the TSFP could ameliorate the lipid dysbolism and contribute to a higher anti-oxidation capacity. Moreover, TSFP could alleviate pathological damages and hinder inflammatory processes of diabetic mice. Besides, the supplementation of TSFP presented a greater ability to shape and optimize the gut microbial composition by enriching the profitable bacteria and inhibiting the pathogenic microorganisms. Correlation analysis also revealed that the abundances of functional bacteria in the TSFP-treated groups exhibited better correlations with serum parameters, which would be of positive significance for blood glucose regulation and inflammation remission.

Conclusions
These results collectively corroborated the feasibility and superiority of using TSFP for hyperglycaemia remission via anti-oxidation enhancement, inflammation alleviation, and microbial composition optimization, contributing to a safely feasible and biologically efficient strategy for improving anti-diabetic effects.
The relationship of constitutional-exogenous obesity and hormonalmicroelement status in adolescent boys with delayed sexual development
Authors: Drukker N. A. , Palieva N. V. , Petrov Y. A. , Рopova V. A. 
Published: January 2025

BACKGROUND: Childhood obesity and the rate of its spread is a serious threat to the reproductive health of the nation, especially among boys, being a background for delaying sexual development and further disrupting fertility.AIM: To study the peculiarities of the ratio of the level of leptin and a number of toxic and essential chemical trace elements in biological environments in adolescent boys aged 13–14 years with obesity and delayed sexual development.MATERIALS AND METHODS: Three groups of adolescents aged 13–14 years were studied and formed: the main ones — with constitutional exogenous obesity of 1–2 degrees (1–20 boys without secondary signs of puberty; 2 — 24 boys with 2–4 stages of puberty according to Tanner) and comparisons (3 — 15 boys with normal body weight and without deviations in puberty). The level of lead, zinc, selenium, chromium and manganese in the morning urine was determined by the absorption method; in the blood serum — leptin, by the method of enzyme immunoassay. Statistical analysis of the data was carried out in the MeoCape 11.4.2 Statistica environment, nonparametric Spearman correlation analysis and calculation of the Student’s t-test for independent samples, the reliability of the results at p< 0.05.RESULTS: It was found that adolescents with obesity are characterized by a certain shift in the content of toxic and essential trace elements, the vector of which is shifted towards the predominance of levels of toxic chemical elements, in particular, ead, and a decrease in essential toxic elements, such as zinc, selenium, chromium and manganese. However, a more pronounced shift in the values in the imbalance of trace elements already violates not only the metabolic processes in the body of adolescent children, but also leads to a violation of puberty - to a delay in sexual development. CONCLUSION: In the body of adolescent boys with obesity and delayed sexual development, the processes of oxidative stress, tissue hypoxia are progressing against the background of excess leptin, accumulation of heavy metals and deficiency of essential trace elements. Less pronounced shifts in the content of leptin and trace elements in adolescent boys are determined by a failure in neuroendocrine regulation, but does not affect the level of puberty. The homeostasis of the hormonal-microelement composition ensures the harmonious development of adolescent boys.
Clinical, hormonal and molecular genetic characteristics of patients with 46,XY disorders of sex development associated with variants in the HSD17B3 gene
Authors: Kalinchenko N. Y. , Makretskaya N. A. , Kolodkina A. A. , Ioutsi V. A. , Petrov V. M. , Tyulpakov A. N. 
Published: January 2025

BACKGROUND: Deficiency of 17β-hydroxysteroid dehydrogenase type 3 (HSD17B3) is a rare variant of 46,XY disorders of sex development (DSD).AIM: To give clinical, hormonal and molecular genetic characteristics of cases of 46,XY DSD associated with variants in the HSD17B3 gene.MATERIALS AND METHODS: The study included 310 patients with 46,XY DSD for the period from 2015 to 2019. The patients underwent a comprehensive examination, including a study of the steroid profile by high-performance liquid chromatography with tandem mass spectrometric detection, as well as a molecular genetic analysis using NGS.RESULTS: According to the results of molecular genetic studies, biallelic nucleotide substitutions in the HSD17B3 gene were detected in 13 cases, which accounted for 4.2% of the total number of patients with 46,XY DSD. All 13 patients with biallelic variants in the HSD17B3 gene were registered as females. The ratio of androstenedione/testosterone concentrations in the blood in this group ranged from 1.4 to 8.9. 2 variants in the HSD17B3 gene were found in several patients: c.277+4A>T (on 6 chromosomes) and c.729_735del:p.V243fs (on 9 chromosomes). 4 novel variants have been identified. Monoallelic nucleotide substitutions in the HSD17B3 gene were detected in 7 cases, which accounted for 2.3% of the total number of patients with 46,XY DSD. External genitalia in this group corresponded to Prader stages 3–4. In 1 patient, a pathogenic variant c.277+4A>T was detected in the HSD17B3 gene, in other cases variants with uncertain significance were detected.CONCLUSION: In the structure of 46,XY DSD, patients with biallelic variants in the HSD17B3 gene were identified in 4.2% of cases, with monoallelic variants — in 2.3% of cases. 4 novel variants were found in the HSD17B3 gene.
Development of prognostic clinical and genetic models of the risk of low bone mineral density using neural network training
Authors: Yalaev B. I. , Novikov A. V. , Minniakhmetov I. R. , Khusainova R. I. 
Published: January 2025

BACKGROUND: Osteoporosis is a common age-related disease with disabling consequences, the early diagnosis of which is difficult due to its long and hidden course, which often leads to diagnosis only after a fracture. In this regard, great expectations are placed on advanced developments in machine learning technologies aimed at predicting osteoporosis at an early stage of development, including the use of large data sets containing information on genetic and clinical predictors of the disease. Nevertheless, the inclusion of DNA markers in prediction models is fraught with a number of difficulties due to the complex polygenic and heterogeneous nature of the disease. Currently, the predictive power of neural network models is insufficient for their incorporation into modern osteoporosis diagnostic protocols. Studies in this area are sporadic, but are widely demanded, as their results are of great importance for preventive medicine. This leads to the need to search for the most effective machine learning approaches and optimise the selection of genetic markers as input parameters to neural network models.AIM: to evaluate the effectiveness of machine learning and neural network analysis to develop predictive risk models for osteoporosis based on clinical predictors and genetic markers of osteoporetic fractures.MATERIALS AND METHODS: The predictive models were trained using a database of genotyping and clinical characteristics of 701 women and 501 men living in the Volga-Ural region of Russia. Anthropometric parameters, data on gender, bone mineral density level, and the results of genotyping of 152 polymorphic loci of candidate genes and replication loci of the GEFOS consortium’s full genome-wide association search were included as input parameters.RESULTS: It was found that the model for predicting low bone mineral density, including 6 polymorphic variants of the OPG gene (rs2073618, rs2073617, rs7844539, rs3102735, rs3134069) and 5 polymorphic variants of microRNA binding sites in the mRNA of genes involved in bone metabolism (COL11A1 — rs1031820, FGF2 — rs6854081, miR-146 — rs2910164, ZNF239 — rs10793442, SPARC — rs1054204 and VDR — rs11540149) (AUC=0.81 for men and AUC=0.82 for women).CONCLUSION: The results confirm the promising application of machine learning to predict the risk of osteoporosis at the preclinical stage of the disease based on the analysis of clinical and genetic factors.