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Item Metadata only Morphological and genetic analyses of herbarium specimens clarify the arrival of non-native common reed (phragmites australis subsp. australis) in Kansas (U.S.A.)(Botanical Research Institute of Texas, 2025-12-16)The common reed, Phragmites australis, is a globally distributed grass species with numerous named subspecific taxa. In North America, a non-native Eurasian subspecies has established and is rapidly expanding its range at the expense of a native subspecies. Our understanding of the common reed invasion in North America is possible because diagnostic data can be obtained from freshly collected and herbarium material, allowing the geography of subspecies to be understood through time. In this study, these morphological and genetic tools were used to diagnose subspecies in a set of specimens from Kansas collected between 1936–2024. Morphological and genetic diagnoses of subspecies agreed in 92% of cases. The non-native subspecies is present in Kansas and arrived in the 1970s or 1980s based on morphological or genetic data, respectively. The last native subspecies specimen was observed in the late 1990s, suggesting that statewide invasion could have been rapid. However, relatively recent specimens are not available for large portions of the state, particularly western Kansas. Additional sampling of both herbarium and freshly collected material is needed to fully understand the historic and current distribution of common reed subspecies in Kansas. © 2025 Botanical Research Institute of Texas. All rights reserved.Item Metadata only Submaximal running with blood flow restriction induces similar muscle oxygenation responses relative to maximal unrestricted running(Akademiai Kiado ZRt., 2026-01-20)Purpose: To examine muscle oxygenation during running with and without blood flow restriction (BFR). Methods: Fifteen aerobically trained males randomly completed four, three-minute running bouts at 70%BFR, 80%BFR, and 90%BFR of their top speed with BFR and 100%NOBFR of their top speed without BFR. Oxygenated hemoglobin (O2Hb), deoxygenated Hb (HHb), total Hb (tHb), Hb difference (HbDiff) and muscle tissue oxygenation (StO2) were assessed continuously throughout the running bouts. Separate two-way, 4 (Intensity [70%BFR, 80%BFR, 90%BFR, 100%NOBFR]) × 3 (Time [120, 150, and 180 s]), repeated-measure ANOVA models were constructed to examine O2Hb, HHb, tHb, HbDiff, and StO2 responses. Results: O2Hb decreased (120- [65.25 ± 6.58%] > 150-s [63.72 ± 6.75%]), while HHb increased (120- [14.4 ± 12.55%] < 150- [16.91 ± 12.6%] < 180-s [18.26 ± 12.87%]) (P < 0.001). tHb was similar across time (P = 0.159) and between intensities (P = 0.454). HbDiff decreased (120- [73.56 ± 6.54%] > 150- [71.66 ± 6.61%] > 180-s [70.98 ± 6.93%]). StO2 decreased and then plateaued (120- > 150- and 180-s) during the 70%BFR (51.87 ± 5.09% > 51.20 ± 5.37% and 51.02 ± 5.21%) (P = 0.004), 80%BFR (52.2 ± 3.93% > 51.34 ± 4.17% and 51.01 ± 4.09%) (P = 0.008), and 100%NOBFR (51.69 ± 4.6% > 50.84 ± 4.87% and 50.62 ± 4.89%) (P < 0.001) bouts, while there were no differences for 90%BFR (P > 0.05). Conclusions: Submaximal running with BFR induced similar responses as maximal running without, despite large differences (i.e., ≤30%) in running speed. © 2025 Akadémiai Kiadó, BudapestItem Open Access Demographic bias mitigation at test-time using uncertainty estimation and human–machine partnership(Elsevier Ltd, 2025-03)Facial attribute classification algorithms frequently manifest demographic biases by obtaining differential performance across gender and racial groups. Existing bias mitigation techniques are mostly in-processing techniques, i.e., implemented during the classifier's training stage, that often lack generalizability, require demographically annotated training sets, and exhibit a trade-off between fairness and classification accuracy. In this paper, we propose a technique to mitigate bias at the test time i.e., during the deployment stage, by harnessing prediction uncertainty and human–machine partnership. To this front, we propose to utilize those lowest percentages of test data samples identified as outliers with high prediction uncertainty. These identified uncertain samples at test-time are labeled by human analysts for decision rendering and for subsequently re-training the deep neural network in a continual learning framework. With minimal human involvement and through iterative refinement of the network with human guidance at test-time, we seek to enhance the accuracy as well as the fairness of the already deployed facial attribute classification algorithms. Extensive experiments are conducted on gender and smile attribute classification tasks using four publicly available datasets and with gender and race as the protected attributes. The obtained outcomes consistently demonstrate improved accuracy by up to 2% and 5% for the gender and smile attribute classification tasks, respectively, using our proposed approaches. Further, the demographic bias was significantly reduced, outperforming the State-of-the-Art (SOTA) bias mitigation and baseline techniques by up to 55% for both classification tasks. The demo shall be released on https://github.com/hashtaglensman/HumanintheLoop. © 2024Item Metadata only Managing service systems with overconfident customers(INFORMS Inst.for Operations Res.and the Management Sciences, 2025-10-14)Problem definition: Extensive evidence shows that customers tend to underestimate the variability of service times. The theoretical foundation lies in overconfidence theory, which asserts that decision makers tend to make overly optimistic forecasts about uncertain events. We study how to decide optimal pricing and queue-length information provision policies to manage a service system where customers are overconfident in their beliefs about service times—customers underestimate the variability of service times. Methodology/results: We formulate the problem as a queueing-game-theoretic model to examine the implications of overconfidence. Our models and results generalize those in seminal queueing-economics papers. First, the classical equivalence result breaks down in an unobservable queue: the revenue-maximizing price is strictly higher than the welfaremaximizing price, and consumer surplus is always negative. However, in an observable queue, consumer surplus is always negative for sufficiently low and sufficiently high congestion, but it can be positive or negative for intermediate congestion depending on system features. Second, the revenue-maximizing price is always higher than in the classical model in an unobservable queue, whereas it can be higher or lower in an observable queue. Third, the manager should always reveal queue-length information to improve revenue for both sufficiently low and sufficiently high congestion but strategically decide for intermediate congestion. Finally, customers will not renege in both unobservable and observable queues, owing to the increasing failure rate of perceived service times. Managerial implications: This paper unravels the role of customer overconfidence in service systems and its important implications on the manager’s pricing decision and queue-length information provision policy as well as consumer surplus. © 2025 INFORMS.Item Metadata only Synthesis, crystal growth, linear, and nonlinear optical properties of water-grown giant optical anisotropic thiocyanates ABi(SCN)4(A = Rb, Cs)(American Chemical Society, 2025-12-30)Thiocyanates are materials that constitute the thiocyanate anion, ([SCN])−. The linear shape of SCN– raises the chemical flexibility of the thiocyanates. More importantly, the thiocyanate crystals can be obtained in water under mild conditions. In this work, a thiocyanate system of ABi(SCN)4 (A = Rb, Cs) was studied as potential nonlinear optical (NLO) materials. CsBi(SCN)4 was grown as large millimeter-sized crystals in water at room temperature. The crystal structure of CsBi(SCN)4 was determined by single-crystal X-ray diffraction. CsBi(SCN)4 crystallizes in the orthorhombic space group P21212 (No. 18) with unit cell parameters of a = 11.1943(4) Å, b= 7.8431(3) Å, and c = 6.5510(2) Å. CsBi(SCN)4 is isostructural to previously reported RbBi(SCN)4. CsBi(SCN)4 features a three-dimensional (3D) framework, which consists of [Bi(SCN)4] units and [Cs(SCN)4] units. The UV–Vis measurement found that CsBi(SCN)4 exhibits a moderate band gap of 2.6(1) eV, which was verified by density functional theory (DFT) calculations, indicating an indirect band gap of 2.85 eV. Theoretical studies indicated that RbBi(SCN)4 and CsBi(SCN)4 possess large birefringence of 0.48@1064 and 0.66@546 nm, respectively. Theoretical studies verified that the Bi atoms and SCN– anions significantly contributed to the optical properties of CsBi(SCN)4. CsBi(SCN)4 exhibited excellent chemical stability, which remained unchanged in air for 180 days and was verified by powder X-ray diffraction. Type-I phase-matching behavior, moderate SHG response, large birefringence, easy growth of large crystals, and high chemical stability make CsBi(SCN)4 attractive as a nonlinear optical material. © 2025 American Chemical Society