Abstract: This paper concerns the behaviour of widely used Large Language Models (LLMs) in a prototypical creative task, viz., the Alternative Uses Task (AUT). Previous studies have indicated that LLMs’ average performances on the AUT are at or somewhat above average human levels but have not examined patterns within performance data (such as the Serial Order Effect (SOE)) which could suggest similarities and differences between human and LLM divergent production processes. The present exploratory study tested for and found evidence for human-like SOEs in AUT performance across a range of LLMs.

Abstract: This study investigates the taphonomic history, site formation processes, and paleontological and archaeofaunal record of Casa de Piedra 1 (CP1) in the Argentine Dry Pampas. The assemblage forms a long-time palimpsest that integrates materials spanning different temporal scales, including reworked Late Cretaceous–Paleocene marine animals and Holocene continental zooarchaeological fauna. The record reflects the combined effects of long-term fluvial reworking, surface exposure, vegetation development, pedogenesis, carbonate precipitation, and anthropogenic activities. These processes degraded skeletal preservation and obscured bone surface modifications, yielding a moderate- to low-resolution palimpsest and indicating that observed alteration frequencies represent minimum estimates. The assemblage preserves recurrent evidence of faunal resource exploitation—primarily Rhea sp. eggshells and large vertebrates—aligning with regional archaeozoological patterns and indicating continuity in hunter-gatherer subsistence during the Holocene. Furthermore, CP1 suggests the long-term persistence of arid, open xerophytic habitats throughout the Holocene within a broader framework of regional paleoenvironmental variability. Overall, CP1 illustrates how complex interactions between recurrent human occupations and multi-scale sedimentary and diagenetic processes shape the archaeological record.

Abstract: Subsurface ultrafast excitation of a transparent or\( \beta^{(K)} \) semitransparent solid requires two conditions that compete during propagation: nonlinear refraction must become strong enough to concentrate the field, while multiphoton absorption must remain weak enough that the pulse is not depleted before reaching the target. We formulate this competition in terms of characteristic Kerr and multiphoton-depletion lengths and use silicon as a quantitative test case. In a single-gap energetic approximation, the threshold of a \( K \)-photon interband channel occurs near \( \lambda_K^{(0)}=Khc/E_g \); the reduced coordinate \( x=\lambda E_g/hc \) therefore provides a material-independent way to organize where the lowest energetically allowed absorption order changes. These nominal thresholds do not determine an optimum on their own: phonon assistance, excitonic and multiband structure, and the measured wavelength dependence of \( n_2 \) and \( \beta^{(K)} \) control the actual response. The nonlinear figure of merit (NFOM) satisfies \( L_{\rm MPA}/L_{\rm Kerr}=2\pi\,\mathrm{NFOM} \). At any candidate operating intensity, simultaneous Kerr engagement and limited nonlinear depletion require the pointwise condition \( 2\pi\,\mathrm{NFOM}\gtrsim1 \); for a specified focusing length \( L_f \), the actual overlap is quantified by the interval \( I_{\rm eng}\le I\le I_{\rm dep} \). Using published silicon coefficients, representative \( L_f=100 \) and \( 250~\mu \)\( m \) values give the largest multiplicative operating-band widths near 1.95–2.15 \( \mu \)\( m \), no overlap at 2.55 \( \mu \)\( m \) within this reduced criterion, and narrower bands at 1.55 and 3.25 \( \mu \)\( m \). The calculation also shows why a low-intensity NFOM can greatly exaggerate the useful dynamic range once three-photon absorption becomes important at the operating intensity. Broadband wavelength, duration, energy, and focusing trends are calculated with a spectral UPPE implementation, while a generalized nonlinear Helmholtz equation solved by the finite-element method (NHE–FEM) provides the local scalar-nonparaxial description of strongly localized field–carrier dynamics. The combined framework connects nonlinear material coefficients, field evolution, photoexcited electron–hole carriers, and processing-relevant localization while explicitly separating the calculated electronic stage from subsequent lattice transformation.

Abstract: Accurate and reliable automated medical image classification is important for computer-aided clinical decision support. However, clinical data are often distributed across institutions and cannot be centrally shared because of privacy, governance, and regulatory constraints. Federated Learning (FL) enables collaborative training while keeping data local, but statistical heterogeneity may cause client drift and performance degradation. We propose FedPBN, a personalized FL approach combining client-specific Batch Normalization (BN) with FedProx-based proximal regularization. BN parameters and running statistics remain local, while non-BN parameters are optimized and aggregated according to client data sizes. FedPBN was evaluated on five clients using PathMNIST and BloodMNIST under IID, Dirichlet (α = 0.5), and pathological Label-Skew distributions with ResNet18, DenseNet121, and MobileNetV2, against FedAvg, FedProx, and FedBN. Personalization and generalization were examined using PFPV, GRV, and CPAV. Results show that preserving client-specific BN is critical under severe Label-Skew, whereas GRV can degrade performance; CPAV recovers much of this loss but requires centralized labeled data. MobileNetV2-FedPBN achieved 97.88% accuracy and 96.79% Macro F1 on PathMNIST. Jetson Orin Nano Super deployment further demonstrated practical hospital-side edge inference, with MobileNetV2 offering the best efficiency–performance balance and DenseNet121 the strongest BloodMNIST Client-0 accuracy.

Abstract: Background/Objective: Periodontitis is a chronic inflammatory disease requiring reliable assessment of periodontal tissue involvement. This study evaluated whether quantitative intraoral thermal features could distinguish Stage III/IV periodontitis from periodontal health using machine-learning methods. Materials and Methods: The study included 108 participants, comprising 54 with Stage III/IV periodontitis and 54 healthy controls. Five standardized intraoral thermal views were obtained from each participant, yielding 540 thermal samples. Mean ROI temperature, maximum–minimum temperature variation, thermal asymmetry, and ROI temperature variance were extracted. Eleven machine-learning classifiers were evaluated using thermal features only. Participant-level stratified five-fold cross-validation was applied, while PPD, CAL, and SBI were analyzed separately for clinical comparison. Results: Higher thermal measurements were observed across all five intraoral views in the periodontitis group, accompanied by differences in PPD, CAL, and SBI. XGBoost achieved the highest accuracy (98.15%), followed by Random Forest (97.22%), Logistic Regression (96.30%), AdaBoost (96.30%), and LightGBM (95.37%). The extracted thermal features provided useful discriminatory information between the two groups. Conclusion: Intraoral thermal imaging captured quantitative thermal patterns associated with Stage III/IV periodontitis and showed potential as a non-invasive, non-contact adjunct to periodontal assessment. Manual ROI selection and the absence of independent thermal calibration and explicit reflection-artifact correction limit interpretation of absolute temperature values. Larger multicentre studies are warranted.

Abstract: In this paper, the first and second laws of thermodynamics are applied in the coupled thermal and elastic fields to analyze the energy conversion and entropy change during the thermoelastic effect. The underlying physical mechanism for energy conversion is explained and the specific term which is responsible for energy conversion between the two coupled fields is also identified. As a result, governing equations which directly satisfy the law of conservation of energy are determined for both the elastic and thermal fields. Moreover, variation of the total entropy during the thermoelastic effect is also analyzed. Both contributions to the entropy change at the surface and within the bulk of the system are obtained with straightforward physical contents. In the end, a preliminary discussion on the thermoelastic effect under thermal shock is also presented; governing equations for both fields are also obtained with that for the thermal field being a wave-type equation.

Abstract: Heat stress poses a critical threat to dairy cattle productivity, fertility and welfare, yet the heritable genetic mechanisms underlying individual variation in thermotolerance remain poorly understood. While previous studies have focused predominantly on miRNA expression profiles or coding gene variants, genome-wide identification of regulatory variants within miRNA genes has remained largely unexplored. In this study, whole-genome sequencing was applied to thermotolerant and thermosensitive Holstein cows, phenotypically classified based on reproductive performance under summer heat stress, to identify group-specific genetic variants within miRNA genes. Thermotolerant-specific variants (n=15) were identified across 15 distinct miRNA loci, including one novel SNP. Five variants were located within mature miRNA sequences, and several were associated with predicted changes in minimum free energy (ΔG), suggesting alterations in secondary structure and stability. Two seed-region variants in bta-mir-2883 and bta-mir-2388-3p were predicted to substantially reshape miRNA–mRNA target repertoires, with gains of approximately 3,000 target genes and losses of approximately 600 per miRNA. Functional enrichment analysis revealed a coordinated redistribution of miRNA-mediated regulation: gained targets were enriched in stress-responsive signaling pathways and metabolic adaptation, while lost targets were associated with intracellular trafficking, vesicle-mediated transport, and membrane dynamics. These findings imply that thermotolerance in dairy cows involves a heritable reorganization of post-transcriptional regulation supporting both controlled stress signaling and cellular flexibility. Collectively, these heritable miRNA variants expand the current toolkit for genomic selection by introducing regulatory, non-coding loci as actionable targets for breeding heat-resilient dairy cattle.

Abstract: In tropical and subtropical countries, malaria and leishmaniasis are significant vector-borne parasitic infections that can often be present at the same time, posing a risk of concurrent infections. However, their roles in disease progression and host responses are not well understood. In the present study, we investigated the effects of consecutive infection with L. major and P. berghei in BALB/c mice. BALB/c mice were randomly allocated to naïve, L. major mono-infected, P. berghei mono-infected and co-infected groups. We observed body weight, Leishmania parasite burden in the footpad, and hematological parameters over a 13-day follow-up after malaria infection. Co-infected mice developed more severe disease than either mono-infected group, exhibiting greater body weight reduction, with mean body weight declining to 24.8 ± 2.4 g by Day 13, compared with 28.1 ± 1.5 g in L. major-infected mice and 26.9 ± 1.9 g in P. berghei-infected mice. The co-infected mice also had higher parasitemia than P. berghei mono-infected mice (23.73 ± 3.02% vs. 19.63 ± 3.39%; p = 0.008), and higher Leishmania parasite burden than L. major mono-infected mice (34.00 ± 1.38 vs. 28.92 ± 6.16; p = 0.041). Co-infection induced anemia, thrombocytopenia, leukocytosis, neutrophilia, lymphopenia and monocytosis. These findings show that co-infection with L. major–P. berghei exacerbates disease severity, boosts the burden of malaria, and worsens hematological dysfunctions; thus, highlighting the need for an integrated approach to malaria–leishmaniasis co-infections in endemic areas.

Abstract: Machine-learning predictions are used to assess material properties, monitor manufacturing processes and support inspection and maintenance. Their engineering value depends on whether the information used by a model can be examined and related to the physical task. This narrative review considers interpretable models, feature attribution, response plots, visual explanations and constrained counterfactuals in manufacturing and materials processing. It distinguishes predictive performance from explanation fidelity, physical evidence and decision usefulness. Selected applications illustrate these differences: process–property modelling in additive manufacturing, acoustic monitoring, tool-condition assessment, ultrasonic defect sizing and uncertainty in production processes. A comparison of these examples shows why the prediction target; data representation and validation procedure must be stated before explanation results are interpreted. The review proposes four categories of explanation use—descriptive, diagnostic, prescriptive and governed—and identifies the additional evidence required for each. The main methodological concerns are dependent inputs, unrealistic perturbations, non-independent observations and changes in the model or operating conditions. Explanation methods can help examine a model and guide further investigation, but process changes require separate checks of feasibility and physical consequences. The narrative selection does not establish the prevalence of individual methods across the field.

Abstract: Background: Advanced glycation end products (AGEs) may link diet, systemic inflammation, and cognitive function; however, evidence in healthy young adults is limited. Objective: To examine the associations of dietary AGEs (dAGEs) intake, circulating AGE–RAGE biomarkers, inflammation, and oxidant–antioxidant markers with cognitive performance. Methods: This cross-sectional study included healthy young adults aged 19–26 years. dAGEs intake was estimated independently using a food-frequency questionnaire (FFQ) and a three-day food record (3D-FR). Serum AGEs (sAGEs), soluble RAGE (sRAGE), interleukin-6, tumour necrosis factor-alpha (TNF-α), malondialdehyde, catalase, superoxide dismutase, and glutathione were measured. Cognitive performance was assessed using Digit Span Forward, Backward, and Total scores and Stroop Interference. Separate multivariable linear regression models were adjusted for age, sex, body mass index, and depressive symptoms, with Benjamini–Hochberg false-discovery-rate correction. Covariate-adjusted partial least squares structural equation modelling (PLS-SEM) examined the prespecified AGE–RAGE–inflammation pathways. Results: Neither FFQ-derived nor 3D-FR-derived dAGEs intake was associated with serum AGEs. In the separate regression models, higher sAGEs (β = −0.36, 95% CI −0.54 to −0.16) and TNF-α (β = −0.33, 95% CI −0.53 to −0.13) were associated with poorer Digit Span Backward performance after false-discovery-rate correction. No other cognitive associations remained significant. In PLS-SEM, sAGEs were positively associated with sRAGE (β = 0.505, p < 0.001), and sRAGE was positively associated with inflammation (β = 0.601, p < 0.001). Greater inflammation was associated with poorer Digit Span Backward performance (β = −0.398, 95% CI −0.697 to −0.110, p = 0.009), whereas the direct sRAGE–Digit Span Backward path was not significant. An indirect inverse association between sRAGE and Digit Span Backward through inflammation was supported (β = −0.239, 95% bootstrap CI −0.457 to −0.057). Conclusions: Circulating AGE–RAGE-related and inflammatory activity, rather than estimated dAGEs intake, was associated with selected aspects of cognitive performance in healthy young adults. Longitudinal studies with larger samples are needed to establish temporality and confirm the significance of these associations.

Abstract: Miniaturizing magnetic-field compensation for atomic spin sensors is challenging with conventional 3D wire-wound coils. We report the MEMS design, fabrication and system-level validation of bi-planar coils for a chip-scale spin-exchange relaxation-free (SERF) atomic magnetometer. Confining conductors to two parallel planes preserves full three-axis field control and makes the field accuracy lithography-limited. For an 8 mm × 8 mm footprint with 7.5 mm plane separation, finite-element analysis predicts coil constants of 81.3nT/mA (in-plane) and 438.6nT/mA (normal), with 0.2% and 0.02% non-uniformity over a 2 × 2 × 2 mm³ target volume. Coils were patterned with 40 μm traces and integrated into a 12 × 15 × 43 mm packaged head. Two independent calibrations were performed: reference-coil substitution (giving 68.2 and 396.0 nT/mA; 16.1% and 9.7% below simulation) and in-situ ¹²⁹Xe free-precession calibration in a ϕ3 × 3 mm cell (yielding 74.3 and 433.6 nT/mA; within 8.6% and 1.1% of simulation). The in-situ approach removes the reference scale factor and directly samples the interrogated volume, validating the numerical model. With 1 kHz modulation, the integrated noise floor reached 38fT/Hz^1/2 and enabled ULF-NMR at 100 nT, resolving water-proton precession and linear CuSO₄ relaxometry down to 50 μM.

Abstract: The global burden of dementia is heavily concentrated in low- and middle-income countries (LMICs), yet biological diagnosis of Alzheimer’s Disease (AD) relies on positron emission tomography (PET) and cerebrospinal fluid (CSF) analysis that are operationally inaccessible in these regions. The 2024 Alzheimer’s Association revised criteria recognize sufficiently accurate plasma assays,particularly p-tau217,as Core 1 biomarkers that may support biological diagnosis, offering a scientifically credible pathway to infrastructure-light biological detection and staging. However, the machine learning literature has expanded without principled mapping to the AT(N) biological framework or rigorous consideration of deployability constraints in resource limited settings. We present a systematic scoping review synthesizing 146 included full-text publications (2018–2026) across four multidisciplinary evidence streams, establishing a novel architectural taxonomy that maps deep learning architectural families directly to AT(N) biological targets and connects model inductive biases to specific biomarker categories. We audit major AD datasets, identify critical biases in demographic and biomarker representation, and map pervasive data pathologies—label scarcity, missing modalities, scanner heterogeneity, and population bias—to corresponding ML/DL remediation strategies. Finally, we argue for a shift from binary classification toward continuous, biologically anchored disease-burden scoring, proposing the Alzheimer’s Disease Burden Index (ADBI). The ADBI equations presented herein represent a theoretical and architectural framework designed to guide future prospective validation on multi-ethnic cohorts. This work provides a methodological roadmap for developing globally deployable, equity aware AD diagnostic models.

Abstract: In autosomal dominant polycystic kidney disease (ADPKD), arginine vasopressin (AVP) and copeptin, a marker of AVP secretion, play important roles. This study aimed to investigate the associations between coffee consumption, serum copeptin levels, and echocardiographic parameters in patients with ADPKD. The study included 75 patients with ADPKD. Serum copeptin levels were measured, monthly coffee consumption was recorded in g/month, and transthoracic echocardiography was performed. Copeptin levels were lower in coffee consumers (262.73 vs. 331.28 ng/L; p = 0.009) and were inversely correlated with coffee consumption status (r = −0.329; p = 0.008). After adjustment, the negative association between coffee consumption and copeptin levels remained significant (B = −0.284, β = −0.306; p = 0.030). Mitral annular e′ velocity was higher in coffee consumers (0.92 vs. 0.69 m/s; p = 0.029) and was significantly associated with coffee consumption after adjustment (B = 0.226, β = 0.263; p = 0.033). No significant associations were found with eGFR, left ventricular mass index, ejection fraction, or the E/e′ ratio. Coffee consumption was associated with lower copeptin levels and higher e′ velocity. These findings are hypothesis-generating and do not demonstrate causality, further comparative studies are needed to determine whether these associations are specific to ADPKD.

Abstract: Flexible IC technologies are useful in low-cost applications such as biomedical, wearable sensors and product tracking. This paper presents the design of a fully-differential high gain op amp based on the Pragmatic 600 nm FlexIC thin-film transistor (TFT) technology. This technology allows solely for the implementation of n-type FETs, resistors and capacitors. The proposed op amp implements novel gate-bootstrapping technique at the output stage pull-up and shunt-shunt feedback n-channel FETs resulting in an increased output voltage swing even when sourcing significant output current. The op amp is intended for applications processing periodic signals such as in fast cyclic voltammetry, thus ensuring the repeated charging of the bootstrapping capacitor. It has an open loop gain of 94 dB and a differential output swing of ±3.5 V when operated at a supply voltage of 5 V. Although here a fully-differential op amp is described, the design can be adapted for single-ended applications by removing one of the output stages and the common mode feedback correction circuitry.

Abstract: The first two papers of Principles of Artificial Science I developed a gauge-theoretic architecture for Big Knowledge Assembly Dynamics and then implemented its first concrete mechanism through U(1)-based single-charge knowledge assembly. The present paper advances from Abelian transport to non-Abelian internal assembly. Quantum chromodynamics (QCD) supplies the mathematical scaffold: a three-dimensional internal representation, an SU(3) connection, noncommuting generators, path-ordered transport, interaction-dependent curvature, and composite states built from fractionally charged constituents. The purpose is not to identify economic or cognitive systems with subatomic matter, but to convert shared structures previously developed in Integration Science into an operational interface for Artificial Science. Earlier sub-economic dynamics modeled achievement and fear-of-failure as up- and down-type impulses, introduced fractional market charges, represented Freudian Id-Self-Superego structure as a three-color internal space, and assigned consciousness a gluon-like mediating role. The present paper combines these ingredients with a parallel sub-cognitive triplet - truth, belief, and justification - in which language plays the mediating role. A three-index state with indices (a, f, g) separates color-like internal position a, flavor-like type f, and generation-like intensity g. The generation index is linked to Yang’s trichotomy, grounded in earlier mental-logic experiments in which inference-schema weights formed three empirical clusters. We formulate an SU(3) knowledge-assembly interface, weak and strong criteria of assemblability, a Fractional-Charge and Dominance Assembly Principle, and a non-Abelian account of order-sensitive composition, curvature, and holonomy. Proton-like uud states are interpreted as achievement-dominant but risk-aware active states; neutron-like udd states as fear-dominant but still aspirational standing-by states. Their different persistence is connected to the Better-Life Principle of ordinary rationality. The framework concludes by preparing the transition from strong-like internal binding to SU(2)-type externality-driven state transformation in Artificial Science I (4).

Abstract: Breast cancer remains a leading cause of cancer-related mortality in women, necessitating the identification of robust biomarkers for early detection and prognostic assessment. This study utilizes an integrative transcriptomic approach to evaluate the expression of CCND1 and ITGB1 transcripts in a clinical cohort of 30 patients. Using quantitative Real-Time PCR and 2−∆∆CT analysis, we demonstrate a significant upregulation of both markers in tumor tissues com-pared to normal margins (P < 0.0001). Furthermore, we integrate these clinical findings with large-scale transcriptomic repository data, revealing a statistically detectable, though modest, association (R = 0.068, P = 0.019). These results suggest that the coordinated dysregulation of cell cycle control and cellular adhesion serves as a coordinated molecular axis for breast cancer progression and prognostic assessment.

Abstract: Plants frequently encounter abiotic stresses such as drought, cold, and high light, which severely reduce crop yields. B-box (BBX) transcription factors are emerging as central regulators that link light signalling to stress responses, but their global regulatory networks remain poorly defined. This review synthesises evidence from Arabidopsis and major crops, including tomato, rice, apple, and tobacco, drawing on gene expression analyses, mutant phenotyping, protein interaction assays, and ubiquitination studies. The compiled results show that BBX proteins act as either positive or negative modulators depending on species and stress type. They control stress tolerance by physically interacting with partners like HY5 and PIFs, directly regulating downstream target genes, and undergoing COP1- or MIEL1-mediated proteasomal degradation. Notably, the C-terminal region dictates their functional divergence, as confirmed by domain-swapping experiments. These findings establish BBX proteins as versatile hubs that integrate environmental cues with developmental programmes. The conclusions suggest that precise manipulation of specific BBX members or their regulatory domains offers a viable route to enhance broad-spectrum stress resilience in crops, supporting sustainable food production under changing climates.

Abstract: The „yellow cobblestones“ of Sofia are considered as one of city’s symbols. This high-quality clicker was developed in Budapest in the late 19th century by using a local marl. Since this paving was declared part of Sofia’s cultural heritage, studies to synthesize similar materials were carried out. Unfortunately, the appropriated Bulgarian clays are characterized by a lower MgO amount, which results in a very narrow sintering range. However, some increase for MgO in the parent batch, bringing the composition closer to that of the original, has a positive effect on the sintering, phase composition and structure. This work discusses the possibility to obtain similar clicker by adding asbestos waste containing high percentage of MgO to a selected Bulgarian marl. The process involves pre-calcination of a part of the marl together with the asbestos waste, followed by mixing the resulting grog with the remaining clay, homogenization, pressing and final firing. The studies with Hot Stage Microscopy and Optical Dilatometry demonstrate that the asbestos addition has a positive effect on the widening of sintering interval, while XRD, SEM and pycnometric results elucidate that the samples obtained in this way are characterized by phase composition and structure comparable to the original material.

Abstract: Bovine mastitis remains one of the most economically significant and biologically complex diseases in dairy production, with major implications for animal welfare, antimicrobial use, milk quality and food safety. Conventional diagnostic approaches, including somatic cell count and microbiological culture, are widely used but present limitations in sensitivity, specificity and timeliness, particularly for subclinical infections. In this context, acute phase proteins (APPs) have emerged as promising host-response biomarkers that provide a direct and biologically relevant measure of mammary inflammation. This review critically evaluates the role of key APPs, along with emerging markers such as cathelicidins, lactoferrin and lipopolysaccharide-binding proteins, in identifying and monitoring bovine mastitis. Evidence indicates that APPs, particularly when measured in milk, offer superior sensitivity for early and subclinical disease compared to somatic cell count and can provide additional insights into disease severity, pathogen class, and local immune responses. Importantly, the review extends beyond diagnostics to examine the underexplored relationship between mastitis-associated inflammation, antimicrobial pharmacokinetics and the risk of drug residues in milk. Inflammatory disruption of the blood–milk barrier, altered transporter activity and changes in milk composition can significantly influence drug distribution and persistence, potentially leading to regulatory exceedances. Future perspectives highlight the integration of APPs into multi-marker diagnostic platforms, biosensor technologies, precision dairy systems and “One Health” frameworks.

Abstract: This study examined the attitudes and practices of personnel working in the food and beverage service sector regarding food allergies. The study population consisted of 110 participants working in the food and beverage department of a hotel operating in Beyoğlu, Istanbul. Data were collected using a cross-sectional, descriptive, and correlational research design, through a structured questionnaire consisting of sections measuring demographic information and knowledge, attitudes, and practices related to food allergies. The average attitude score of the participants towards food allergies was 40.19 ± 6.43, which corresponds to 77.3% of the total score and indicates a generally positive attitude. The average practice score regarding food allergies was found to be 21.29 ± 3.47; the proximity of this score to the upper limit of the scale indicates that the participants largely exhibited appropriate and safe practices regarding food allergy management. Furthermore, a moderate, positive, and statistically significant relationship was found between attitude and practice scores (r = 0.436, p < 0.01). The findings indicate that employees in the food and beverage industry adopt conscious and responsible attitudes regarding food allergies and demonstrate behaviors that support these attitudes in practice.