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Exploring the Digital Platform Economy Through a Gendered Lens: Women in Courier Work
No full textDigitalisation has been transforming economic activities tremendously. It has led to the emergence of new businesses and changed the way business is carried out all over the world. Moreover, it has given way to the development and rapid rise of platform based enterprises, which are also referred to as e-platforms. The increase in the sale of goods online also affected the logistics sector and as a consequence the need for couriers to deliver the goods rose as well. The current qualitative study has aimed to shed light on the general working lives of courier women working for e-platforms. Twenty courier women who have been working for the same e-commerce company took part in the study. Data has been collected through focus group discussions and one-to-one interviews. Detailed analysis of in-depth discussions and interviews revealed that the logistics sector seems to be excluding women from the sector to a great extent. Women working as couriers for e-commerce companies have to struggle with very heavy parcels, suffer from the difficulties of working outside, male hostility, gender discrimination, gender-work identity conflict and sexual harassment. Moreover, it was found out that the ‘sole proprietorship’ employment model for couriers is leading to discontent among couriers and seems to be chosen deliberately to transfer the risks and losses to the couriers. © 2024 Copyright held by the owner/author(s
Shap-Based Identification of Potential Acoustic Biomarkers in Patients With Post-Thyroidectomy Voice Disorder
No full textObjective: The objective of this study was to identify potential robust acoustic biomarkers for functional post-thyroidectomy voice disorder (PTVD) that may support early diagnosis and personalized treatment strategies, using acoustic analysis and explainable machine learning methods. Methods: Spectral and cepstral features were extracted from /a/ and /i/ voice recordings collected preoperatively and 4-6 weeks postoperatively from a total of 126 patients. Various Support Vector Machine (SVM) and Boosting models were trained. SHapley Additive exPlanations (SHAP) analysis was applied to enhance interpretability. SHAP values from training and test sets were compared via scatter plots to identify stable candidate biomarkers with high consistency. Results: GentleBoost (AUC = 0.85) and LogitBoost (AUC = 0.81) demonstrated the highest classification performance. Performance metrics across all models were evaluated for statistical significance. DeLong's test was conducted to assess differences between ROC curves. The features iCPP, aCPP, and aHNR were identified as stable candidate biomarkers, exhibiting consistent SHAP distributions in both training and test sets in terms of direction and magnitude. These features showed statistically significant correlations with PTVD (p 0.05) and demonstrated strong effect sizes (Cohen's d = -2.95, -1.13, -0.60). Their diagnostic relevance was further supported by post hoc power analyses (iCPP: 1.00; aCPP: 0.998). Conclusions: SHAP-supported machine learning models offer an objective and clinically meaningful approach for evaluating PTVD. The identified features may serve as potential biomarkers to guide individualized voice therapy decisions during the early postoperative period
Softmax Öznitelikleri ile Özbilgi Damıtma Yoluyla Derin Sinir Ağlarının Görüntü Sınıflandırma Performansının İyileştirilmesi
No full textIsik UniversityThis study proposes a new self-knowledge distillation method to enhance the classification performance of deep learning models. Compared to traditional knowledge distillation, which relies on the softmax outputs of a teacher model, the proposed method provides greater flexibility in learning. In standard distillation, the student model is constrained to mimic the teacher, whereas the proposed approach integrates the teacher's predictions as an additional input, allowing the model to preserve its own learning dynamics. This approach balances the teacher's guidance with independent feature learning, strengthening decision boundaries. The proposed method has been tested on CIFAR-10 and CIFAR-100 datasets and evaluated using basic convolutional neural network and ResNet50 architectures. The results demonstrate that this method offers a valuable performance improvement in applications where classification accuracy is crucial. © 2025 Elsevier B.V., All rights reserved
Eosinophilia and Helminthic Infections in the Black Sea Region of Türkiye
No full textIntroduction: Eosinophils play crucial roles in the cellular and humoral immune responses and usually constitute 1-3% of leukocytes in peripheral blood. Conditions that cause eosinophilia include allergic diseases, drug hypersensitivity, infections, cancers, and immunological or autoimmune diseases. Among parasitic diseases, it has been reported that eosinophilia is most frequently caused by helminth infections such as cystic echinococcosis (CE), fascioliasis, toxocariasis, schistosomiasis, strongyloidiasis, filariasis, and trichinellosis. Methods: The population of the research was taken as the population of Samsun province. A total of 646 sera were taken from patients (278 males and 279 females) with eosinophilia (> 5%), and 89 samples were taken from patients (45 males and 44 females) without eosinophilia ( 5%) which were referred to the XX Public Health Laboratory for hemogram analysis from Samsun province were included in the study. An in-house ELISA was used to investigate F. hepatica, T. spiralis, and E. granulosus antibodies in sera collected from the patients in the eosinophilic and non-eosinophilic groups. Results: In the eosinophilic group (n = 557), seropositivity rates were 0.9% for echinococcosis, 0.5% for fascioliasis, 72.2% for toxocariosis, and 0.5% for trichinellosis, while they were 0.0%, 0.0%, 64%, and 1.1%, respectively, in the non-eosinophilic group (89 cases). Conclusion: Although the results suggest that helminth infections may be relatively rare causes of eosinophilia in our region, more data are required due to the low number of controls. For this purpose, a comprehensive seroprevalence study with a larger control group will investigate other helminthic agents such as ascariasis, strongyloidiasis, and hookworm infections. © 2025 Elsevier B.V., All rights reserved
Measurement of W±-Boson Differential Cross-Sections in Proton–Proton Collisions with Low Pile-Up Data at s=5.02 TeV and 13 TeV with the ATLAS Detector
No full textHigh precision single-differential W±-boson production cross-sections as a function of electron or muon transverse momentum pT or their pseudorapity η, as well as double-differential cross-sections as functions of these variables, are measured in proton–proton collisions at centre-of-mass energies s=5.02 TeV and 13 TeV. The W-boson charge asymmetry as a function of lepton η is also measured. The data, collected in dedicated runs at reduced instantaneous luminosity with the ATLAS detector at the Large Hadron Collider, correspond to integrated luminosities of 255 pb-1 at 5.02 TeV and 338 pb-1 at 13 TeV. The measurements are in agreement with Standard-Model predictions calculated at next-to-next-to-leading-order in the strong coupling constant αs including transverse-momentum resummation at next-to-next-to-leading logarithmic accuracy using several parton distribution functions. The impact of the measured differential cross-sections as a function of lepton η on the determination of these functions is studied using a profiling technique. © 2025 Elsevier B.V., All rights reserved
Impact of Malnutrition on Pupillary Responses in Pediatric Population
No full textPurpose : To investigate the effect of nutritional status on pupillary responses in children aged 5 to 18 years. Methods : This cross-sectional study comprised 92 eyes of malnourished children and 80 eyes of age- and gender-matched healthy children based on BMI Z-score. Serum ferritin, hemoglobin, serum 25-hydroxyvitamin D, and vitamin B12 levels were recorded. Pupillary responses were taken using Sirius topography (CSO, Italy) with the automated pupillometry function. Static pupillometry consisted of pupil diameters at scotopic, mesopic, and photopic luminances. In dynamic pupillometry, the mean pupil dilation speed at the 10th second was calculated by dividing the distance by time in each 0.2 s period. Results : No significant difference was observed between the groups regarding age, gender, visual acuity, and spherical equivalent (p > 0.05). Mean hemoglobin, serum ferritin, serum 25-hydroxyvitamin D, and vitamin B12 levels were lower in malnourished children than healthy children (p 0.001). The malnutrition group had lower mean pupil diameters under all luminance and higher speed of pupil dilation compared to the control group (p 0.05). While malnutrition subgroups were similar in terms of pupil diameters under all luminance (p > 0.05), the speed of pupil dilation was significantly different between the groups (p = 0.024). BMI z-score was positively correlated with mesopic and photopic pupil diameter but also negatively correlated with the speed of pupil dilation (p 0.05). Conclusion : Malnourished children have smaller pupil diameters and higher speed of pupil dilation than healthy controls, indicating an autonomic impairment
A Study of Academics' Perceptions of Ethical Implications of Generative Artificial Intelligence on Scientific Research and Publishing
No full textThis study investigates how scientists, educators, and ethics committee members in T ; uuml;rkiye perceive the opportunities and risks posed by generative AI and the ethical implications for science and education. This study uses a 22-question survey developed by the EOSC-Future and RDA AIDV Working Group. The responses were gathered from 62 universities across 208 universities in T ; uuml;rkiye, with a completion rate of 98.4%. By capturing the diverse perspectives of key academic stakeholders, this study makes three significant contributions to the academic literature: 1) the responsible utilization of technologies such as generative AI depends not only on technological capabilities but also on the ethical conscientiousness of scientists. 2) it is crucial to use generative AI tools with critical human oversight to maintain scientific integrity. 3) Promoting a culture of ethical scholarly practice necessitates the standardization of responsible conduct of research and its integration into the training of scientists.EOSC Future/RDAThe authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the EOSC Future/RDA
The Quest to Discover Supersymmetry at the ATLAS Experiment
No full textSchmitt, Stefan/0000-0001-8387-1853; Islam, Wasikul/0000-0002-5624-5934; Butterworth, Jonathan/0000-0002-5905-5394; Vecchio, Valentina/0000-0002-1351-6757; Gaudio, Gabriella/0000-0002-6833-0933; Jia, Jiangyong/0000-0002-5725-3397; Sahinsoy, Merve/0000-0002-7400-7286; Berta, Peter/0000-0003-0780-0345; Kontaxakis, Pantelis/0000-0002-4860-5979; Cheong, Sanha/0000-0002-2797-6383; Winter, Benedict Tobias/0000-0001-9606-7688; Cristoforetti, Marco/0000-0002-0127-1342; Meloni, Federico/0000-0001-7075-2214; Morii, Masahiro/0000-0001-9324-057X; Azuelos, Georges/0000-0003-4241-022X; Held, Alexander/0000-0002-8924-5885; Lacasta, Carlos/0000-0002-2623-6252; Beau, Tristan/0000-0002-2022-2140; Fox, Harald/0000-0003-3089-6090; Worm, Steven/0000-0002-3865-4996; Price, Darren/0000-0003-2750-9977; Novak, Tadej/0000-0002-3053-0913; Keeler, Richard/0000-0002-0510-4189; Cardillo, Fabio/0000-0002-4478-3524; Mcpherson, Robert/0000-0001-9211-7019; Nikolopoulos, Konstantinos/0000-0002-3048-489X; Munoz Sanchez, Francisca/0000-0002-6374-458X; Cunha Sargedas Sousa, Mario Jose/0000-0001-7991-593X; Beck, Hans Peter/0000-0001-7212-1096; Vincter, Manuella/0000-0002-5338-8972; Schenck, Ferdinand/0000-0001-8279-4753; Kretzschmar, Jan/0000-0002-8515-1355; Quinn, Ryan/0000-0002-0879-6045; Bhatta, Somadutta/0000-0002-9045-3278; Lloyd, Stephen/0000-0002-5073-2264; Elsing, Markus/0000-0002-1213-0545; Bella, Gideon/0000-0002-4009-0990; Koch, Simon Florian/0000-0002-2676-2842; Stanislaus, Beojan/0000-0001-9007-7658; D'Uffizi, Matteo/0000-0003-2499-1649; Redlinger, George/0000-0002-6437-9991; Schultz-Coulon, Hans-Christian/0000-0002-0860-7240; Hance, Michael/0000-0001-8392-0934; Konstantinidis, Nikolaos/0000-0002-4140-6360; Bouhova-Thacker, Evelina/0000-0002-5103-1558; Leblanc, Matt/0000-0001-5977-6418; Alimonti, Gianluca/0000-0002-7128-9046; Bruschi, Marco/0000-0002-4319-4023; Mckee, Shawn/0000-0002-4551-4502; Klein, Lucas/0000-0002-0145-4747; Doglioni, Caterina/0000-0002-1509-0390; Kumar, Mukesh/0000-0003-3681-1588; Pettee, Mariel/0000-0001-9208-3218; Kaji, Toshiaki/0000-0002-6532-7501; Citron, Zvi/0000-0003-1831-6452; Mindur, Bartosz/0000-0002-5511-2611; Mondal, Santu/0000-0002-6965-7380; De La Torre Perez, Hector/0000-0002-4516-5269; Martinez-Agullo, Pablo/0000-0001-8925-9518; Pleier, Marc-Andre/0000-0002-9461-3494; Smirnova, Oxana/0000-0003-2517-531X; Di Luca, Andrea/0000-0002-9074-2133; Dong, Qichen/0000-0002-0117-7831; Gwilliam, Carl/0000-0002-9401-5304; Su, Dong/0000-0001-6980-0215; Rousseau, David/0000-0001-7613-8063; Martoiu, Sorin/0000-0002-4963-9441; Stark, Giordon/0000-0001-6616-3433; Kirk, Julie/0000-0001-8096-7577; Kowalewski, Robert/0000-0002-7314-0990; Mete, Alaettin Serhan/0000-0002-5508-530X; Grinstein, Sebastian/0000-0002-6460-8694; Sampsonidou, Despoina/0000-0003-0384-7672; Rompotis, Nikolaos/0000-0003-2577-1875; Bahmani, Marzieh/0000-0003-4173-0926; Mitsou, Vasiliki A./0000-0002-1533-8886; Terzo, Stefano/0000-0003-3388-3906; Merlassino, Claudia/0000-0002-5445-5938The search for supersymmetry with the ATLAS experiment at the CERN Large Hadron Collider intensified after the discovery of the Higgs boson in 2012. The search programme expanded in both breadth and depth, profiting from the increased integrated luminosity and higher centre-of-mass energy for the collision data collected between 2015 and 2018, and gaining new sensitivity to unexplored areas of supersymmetry parameter space through the use of novel experimental signatures and innovative analysis techniques. This report summarises the supersymmetry searches at ATLAS using up to 140 fb(-1) of pp collisions at root s = 13 TeV, including the limits set on the production of gluinos, squarks, and electroweakinos for scenarios with or without R-parity conservation, and including models where some of the supersymmetric particles are long-lived. (c) 2024 CERN for the benefit of the ATLAS Collaboration. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW; FWF, Austria; ANAS; CNPq; FAPESP, Brazil; NSERC; CFI, Canada; NSFC, China; MEYS CR, Czech Republic; DNRF; DNSRC, Denmark; IN2P3-CNRS; CEA-DRF/IRFU, France; BMBF; MPG, Germany; RGC and Hong Kong SAR, China; ISF; Benoziyo Center, Israel; INFN, Italy; MEXT; JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MEiN, Poland; FCT, Portugal; MNE/IFA, Romania; MESTD, Serbia; MSSR, Slovakia; SRC; Wallenberg Foundation, Sweden; SNSF and Cantons of Bern and Geneva, Switzerland; NSTC, Taipei; STFC/UKRI, United Kingdom; DOE; NSF, United States of America; BCKDF; CANARIE; CRC; DRAC, Canada [PRIMUS 21/SCI/017, UNCE SCI/013]; Czech Republic; ERC; ERDF; Marie Sklodowska-Curie Actions, European Union; Investissements d'Avenir Labex, Investissements d'Avenir Idex; ANR, France; DFG; AvH Foundation, Germany - EU-ESF; Greek NSRF, Greece; BSF-NSF; NCN [UMO-2019/34/E/ST2/00393, UMO-2020/37/B/ST2/01043, UMO-2021/40/C/ST2/00187, UMO-2022/47/O/ST2/00148]; La Caixa Banking Foundation [NextGenEU PCI2022-135018-2]; CERCA Programme Generalitat de Catalunya; PROMETEO [CIDEGENT/2019/023, CIDEGENT/2019/027]; Generalitat Valenciana, Spain; Goran Gustafssons Stiftelse, Sweden; Royal Society; Leverhulme Trust, United Kingdom; CERN: European Organization for Nuclear Research (CERN PJAS); Chile: Agencia Nacional de Investigacion y Desarrollo (FONDECYT) [1190886]; FONDECYT [1230987]; China: National Natural Science Foundation of China [NSFC -12175119, NSFC 12275265, NSFC-12075060]; Czech Republic: PRIMUS Research Programme [PRIMUS/21/SCI/017]; EU [ERC -101002463]; European Union: European Research Council [ERC -948254, ERC 101089007, MUCCA -CHIST-ERA-19-XAI-00]; European Union [FAIR-NextGenerationEU PE00000013]; Italian Center for High Performance Computing, Big Data and Quantum Computing (ICSC); France: Agence Nationale de la Recherche [ANR-20-CE31-0013, ANR-21-CE31-0013, ANR-21CE31-0022, ANR-22-EDIR-0002]; Investissements d'Avenir Labex; Germany: Baden-Wurttemberg Stiftung; Deutsche Forschungsgemeinschaft [DFG -469666862, DFG -CR 312/52]; Ministero dell'Universita e della Ricerca [-20223N7F8K -PNRR M4.C2.1.1]; Japan Society for the Promotion of Science (JSPS KAKENHI) [JP21H05085, JP22H01227, JP22H04944, JP22KK0227, RCN-314472]; Polish National Agency for Academic Exchange [PPN/PPO/2020/1/00002/U/00001]; Polish National Science Centre (NCN) [2021/42/E/ST2/00350]; NCN OPUS [2022/47/B/ST2/03059]; Slovenian Research Agency [J1-3010]; BBVA Foundation [LEO22-1-603]; Generalitat Valenciana; FEDER [IDIFEDER/2018/048]; MICIN FEDER [PID2021-125273NB, RYC2019-028510-I, RYC2021-031273-I, RYC2022-038164-I]; Swedish Research Council [VR 2018-00482, VR 2022-03845, VR 2022-04683, 2021-03651]; Knut and Alice Wallenberg Foundation [KAW 2017.0100, KAW 2018.0157, KAW 2018.0458, KAW 2019.0447, SNSF -PCEFP2_194658]; ULeverhulme Trust (Leverhulme Trust) [RPG-2020-004]; United States of America; Neubauer Family FoundationWe gratefully acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; ANID, Chile; CAS, MOST and NSFC, China; Minciencias, Colombia; MEYS CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS and CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF and MPG, Germany; GSRI, Greece; RGC and Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MEiN, Poland; FCT, Portugal; MNE/IFA, Romania; MESTD, Serbia; MSSR, Slovakia; ARIS and MVZI, Slovenia; DSI/NRF, South Africa; MICIU/AEI, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; NSTC, Taipei; TENMAK, Turkiye; STFC/UKRI, United Kingdom; DOE and NSF, United States of America. Individual groups and members have received support from BCKDF, CANARIE, CRC and DRAC, Canada; CERN-CZ, PRIMUS 21/SCI/017 and UNCE SCI/013, Czech Republic; COST, ERC, ERDF, Horizon 2020, ICSC-NextGenerationEU and Marie Sklodowska-Curie Actions, European Union; Investissements d'Avenir Labex, Investissements d'Avenir Idex and ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and MINERVA, Israel; Norwegian Financial Mechanism 2014-2021, Norway; NCN and NAWA, Poland; La Caixa Banking Foundation, CERCA Programme Generalitat de Catalunya and PROMETEO and GenT Programmes Generalitat Valenciana, Spain; Goran Gustafssons Stiftelse, Sweden; The Royal Society and Leverhulme Trust, United Kingdom. In addition, individual members wish to acknowledge support from CERN: European Organization for Nuclear Research (CERN PJAS); Chile: Agencia Nacional de Investigacion y Desarrollo (FONDECYT 1190886, FONDECYT 1210400, FONDECYT 1230812, FONDECYT 1230987); China: National Natural Science Foundation of China (NSFC -12175119, NSFC 12275265, NSFC-12075060); Czech Republic: PRIMUS Research Programme (PRIMUS/21/SCI/017); EU: H2020 European Research Council (ERC -101002463); European Union: European Research Council (ERC -948254, ERC 101089007), Horizon 2020 Framework Programme (MUCCA -CHIST-ERA-19-XAI-00), European Union, Future Artificial Intelligence Research (FAIR-NextGenerationEU PE00000013), Italian Center for High Performance Computing, Big Data and Quantum Computing (ICSC, NextGenerationEU); France: Agence Nationale de la Recherche (ANR-20-CE31-0013, ANR-21-CE31-0013, ANR-21CE31-0022, ANR-22-EDIR-0002), Investissements d'Avenir Labex (ANR-11-LABX-0012); Germany: Baden-Wurttemberg Stiftung (BW Stiftung-Postdoc Eliteprogramme), Deutsche Forschungsgemeinschaft (DFG -469666862, DFG -CR 312/52); Italy: Istituto Nazionale di Fisica Nucleare (ICSC, NextGenerationEU), Ministero dell'Universita e della Ricerca (PRIN -20223N7F8K -PNRR M4.C2.1.1); Japan: Japan Society for the Promotion of Science (JSPS KAKENHI JP21H05085, JSPS KAKENHI JP22H01227, JSPS KAKENHI JP22H04944, JSPS KAKENHI JP22KK0227); Netherlands: Netherlands Organisation for Scientific Research (NWO Veni 2020 -VI.Veni.202.179); Norway: Research Council of Norway (RCN-314472); Poland: Polish National Agency for Academic Exchange (PPN/PPO/2020/1/00002/U/00001), Polish National Science Centre (NCN 2021/42/E/ST2/00350, NCN OPUS nr 2022/47/B/ST2/03059, NCN UMO-2019/34/E/ST2/00393, UMO-2020/37/B/ST2/01043, UMO-2021/40/C/ST2/00187, UMO-2022/47/O/ST2/00148); Slovenia: Slovenian Research Agency (ARIS grant J1-3010); Spain: BBVA Foundation (LEO22-1-603), Generalitat Valenciana (Artemisa, FEDER, IDIFEDER/2018/048), La Caixa Banking Foundation (LCF/BQ/PI20/11760025), Ministry of Science and Innovation (MCIN ; NextGenEU PCI2022-135018-2, MICIN ; FEDER PID2021-125273NB, RYC2019-028510-I, RYC2020-030254-I, RYC2021-031273-I, RYC2022-038164-I), PROMETEO and GenT Programmes Generalitat Valenciana (CIDEGENT/2019/023, CIDEGENT/2019/027); Sweden: Swedish Research Council (VR 2018-00482, VR 2022-03845, VR 2022-04683, VR grant 2021-03651), Knut and Alice Wallenberg Foundation (KAW 2017.0100, KAW 2018.0157, KAW 2018.0458, KAW 2019.0447, KAW 2022.0358); Switzerland: Swiss National Science Foundation (SNSF -PCEFP2_194658); United Kingdom: ULeverhulme Trust (Leverhulme Trust RPG-2020-004); United States of America: U.S. Department of Energy (ECA DE-AC02-76SF00515), Neubauer Family Foundation
Design and Simulation of SWIR NbN-InGaAs Photodetector with AlGaAs Barrier
No full textThe article discusses the simulation of an nBn-InGaAs photodetector using Silvaco TCAD at 300 K, focusing on optimizing the barrier performance and reducing the valence band offset. It explores the device-s electrical and optical behaviors, including dark current, photocurrent, and capacitance. The results show a peak responsivity of 0.91 A/W at 1.55 μm and a junction capacitance of 9 pF at -5 V. Adding an anti-reflection coating notably improved the optical performance, highlighting the structure-s potential for efficient infrared photodetection. © 2025 Elsevier B.V., All rights reserved
Products of General Fibonomial Coefficients via Matrices
No full textAs a sequential analogue of binomial coefficients, we consider general Fibonomial coefficients with indices in arithmetic progressions. We give a recurrence relation and a generating matrix for the products of these coefficients. We find explicitly the spectrum of the generating matrix by constructing new relationships between the coefficients and characteristic polynomials of general Pascal matrices. We derive various identities for the general Fibonomial coefficients. Finally, we present a matrix approach to derive a formula for sums of these coefficients. © 2025 Elsevier B.V., All rights reserved