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Dimethylglycinium hydrogen maleate‒maleic acid, a new all-organic ferroelectric with an incommensurate phase

A new European platform for advancing regulatory science research

Nanobodies targeting EGFR provide insight into conformations stabilized by glioblastoma mutations

Differential role of internet-based targeted persuasive advertising versus mass advertising on firms with unique qualities in an anchoring perspective

A firm’s primary objective is to enhance its products’ perceived quality through persuasive advertising techniques, thereby influencing consumer purchase decisions. This research paper delves into the effects of different forms of persuasive advertising, specifically mass and Internet-based targeted persuasive advertising, on enhancing perceived product qualities within a competitive duopoly. The analysis takes into consideration a vertical differentiation model. The findings of this study demonstrate that both firms, each producing products with distinctive qualities, can augment the perceived quality of their offerings through the application of persuasive advertising strategies. Notably, a low-quality firm consistently adjusts its perceived quality to a fixed ratio of 4/7, leading to the anchoring effect on perceived quality. Meanwhile, it is observed that the firm manufacturing lower-quality products tend to rely more on mass persuasive advertising in comparison to its rival firm. Furthermore, targeted advertising through online channels proves to be advantageous in reaching a specific population that highly values the price-to-quality ratio. Specifically, a firm with superior quality that engages in Internet-based targeted persuasive advertising stands to gain more incredible benefits than its rival relying on mass persuasive advertising. These findings shed light on the distinct impacts of various persuasive advertising approaches on competitive firms with unique qualities. Essentially, it underscores the significance of strategic advertising decisions in effectively influencing consumers’ perceived product qualities and gaining a competitive edge in the market.

Structure and molecular dynamics of perovskite N(CH3)4MnCl3 crystals of high-temperature phases I and (I′)

Analyzing the spatiotemporal effects of meteorological factors on hand, foot and mouth disease using mixed geographically and temporally weighted autoregressive models

A comprehensive epidemiological analysis of breast cancer in the Eastern Province of Saudi Arabia

Topography-driven variability in atmospheric deposition and soil distribution of cadmium, lead and zinc in a mountainous agricultural area

The effects of robot anthropomorphic characteristics on employees’ anti-robot sabotage

Time series image coding classification theory based on Lagrange multiplier method

An authorizable and preprocessable data transmission scheme based on elliptic curves

Abstract Current data security transmission schemes are based on the idea of signcryption, where the sender performs encryption and generates signatures within a single logical step. However, on one hand, the complexity of signing is relatively low, while the encryption and communication complexities for large amounts of data are high, leading to low overall transmission efficiency. On the other hand, once the receiver obtains the ciphertext, they can decrypt it, reducing the sender’s control over the data. Therefore, this paper proposes a data security transmission scheme that supports authorization and preprocessing. The scheme first preprocesses the computationally expensive data encryption and transmission operations, and then performs the authorization signature to improve efficiency. Specifically, based on the R value from Schnorr’s signature, the sender’s public key, and the receiver’s public key, a one-time public key is computed and used to encrypt the data before sending it to the receiver. The receiver can compute the corresponding one-time private key to decrypt and obtain the plaintext data, but only after receiving the s value from the sender’s Schnorr signature. Additionally, before the authorization signature s is published, the receiver cannot decrypt the data, ensuring both authorization unforgeability and data confidentiality, while also enhancing the sender’s control over the decryption timing. Experimental results show that for a 1KB data transmission, the execution times for the one-time public key generation algorithm, encryption algorithm, authorization algorithm, decryption algorithm, and signature verification algorithm were 3.34/28.37/0.58/3.32/4.58 ms, respectively, indicating high efficiency for each algorithm. Comparison tests show that for data sizes ranging from 50K to 1600K, using the preprocessing method can reduce execution time by about 68%.

Idarucizumab more effectively reverses the anticoagulant effects of dabigatran acylglucuronide than dabigatran

Crosstalk between iron and flavins in the opportunistic fungal pathogen Candida albicans

Network pharmacognosy of Galphimia glauca: Mapping the molecular landscape of a traditional Mexican medicinal plant

This study explores the pharmacological landscape of Galphimia glauca , a traditional Mexican medicinal plant known for its sedative and anti-inflammatory effects. Using network pharmacognosy, we analyzed the interactions of G. glauca ’s bioactive compounds, Galphimines A-I, with human protein targets. SwissTargetPrediction identified 214 unique protein targets across the galphimines, revealing a core-periphery structure in a bipartite network where 41 targets are shared among all compounds. Further interaction analysis using STRING-DB generated a dense protein-protein interaction network comprising 1,386 connections. Centrality analysis highlighted proteins such as SRC, MTOR, and MAPK3 as key nodes involved in cell growth, proliferation, and immune regulation pathways, suggesting these as pivotal mediators of G. glauca ’s pharmacological effects. Community detection with the Walktrap algorithm further segmented the network into functionally relevant modules linked to cell survival, immune response, and inflammation, reflecting the therapeutic effects historically attributed to G. glauca . Our findings underscore the plant’s multi-target therapeutic potential and highlight the value of network-based approaches in understanding traditional medicine. This work lays the groundwork for further studies aimed at refining therapeutic strategies based on G. glauca ’s bioactive compounds and suggests network pharmacognosy as a promising tool for assessing other traditional medicinal plants.

Efficient knowledge distillation and alignment for improved KB-VQA

STIED: a deep learning model for the spatiotemporal detection of focal interictal epileptiform discharges with MEG

Red blood cell distribution width to albumin ratio is associated with osteoarthritis prevalence among US adults with diabetes using data from NHANES 2005 to 2018

Benchmarking validity indices for evolutionary K-means clustering performance

Abstract K-Means is a well-established clustering algorithm widely used in data analysis and various real-world applications. However, its requirement for a predefined number of clusters limits its effectiveness in automatic clustering tasks. To address this, metaheuristic optimisation algorithms have been integrated into K-Means, leading to the development of Evolutionary K-Means clustering approaches. These methods often rely on internal validity indices as fitness functions to automatically determine both the optimal number of clusters and the clustering configuration. However, the effectiveness of internal validity indices is often data-dependent, as most are tailored to specific data characteristics. Consequently, the choice of validity index can significantly influence clustering outcomes. This study evaluates the performance of fifteen internal validity indices within the Enhanced Firefly Algorithm-K-Means (FA-K-Means) framework, an evolutionary approach that integrates Firefly metaheuristics with the classical K-Means algorithm. The performance of each index is assessed across a diverse collection of real-life and synthetic datasets with varying structures. The results reveal that the Calinski-Harabasz (CH) and Silhouette indices consistently outperform others, offering more reliable clustering performance. These findings provide practical guidance for selecting appropriate fitness functions in Evolutionary K-Means algorithms for automatic clustering tasks.

A qualitative interview study on psycho-oncologists’ experiences with patient deaths in Germany

Abstract Despite regular exposure to patient deaths, little research has explored how psycho-oncologists experience and cope with these events. This study examined the unique challenges faced by psycho-oncologists in Germany, aiming to contribute to the broader understanding of professional grief and its impact on healthcare professionals’ mental health and well-being. We conducted 25 semi-structured interviews with psycho-oncologists. The interviews were audiorecorded, transcribed, and analyzed using content analysis. Participants experienced an average of two patient deaths per month. The findings revealed both positive and negative effects of patient deaths on their personal and professional lives. While many participants managed professional grief successfully, most expressed unmet needs for education and information on coping strategies. Peer support was identified as particularly valuable for managing the emotional toll. Overall, patient deaths had significant, varying impacts on psycho-oncologists, highlighting the need for healthcare institutions to implement targeted support and educational interventions to address professional grief and enhance their well-being.

A system solution for a 100 kA class high temperature superconducting line for HL-LHC and for wider energy applications

Abstract The powering of the High Luminosity magnets of the Large Hadron Collider relies on Cold Powering Systems incorporating direct current superconducting lines, called Superconducting Links, based on magnesium diboride cables. A Cold Powering System interconnects the magnets in the accelerator existing tunnel to the power converters in newly excavated galleries that are about 8 m higher than the accelerator tunnel and up to about 100 m distant from the magnets. It feeds circuits rated at different currents and is designed to transfer a total current of up to |117| kA with magnesium diboride and Rare-Earth-Barium-Copper-Oxide technologies. After about ten years of development, the first Cold Powering System was successfully constructed and tested at CERN. The Superconducting Link was measured in a geometrical configuration that included a vertical path simulating the final routing in the accelerator underground. The test campaign validated the mechanical, cryogenic and electrical performance of the system both in steady state conditions and under various transient scenarios. This paper reports on the results of the tests and details the performance of the first ever built magnesium diboride and Rare-Earth-Barium-Copper-Oxide 100 kA class superconducting system.