Nature Of Communication Research Articles

Differential Impact of Domain Stratified Non-R882 DNMT3A Mutations in Myeloid Neoplasms

Introduction: DNMT3A mutations are present in approximately 20% of acute myeloid leukemia (AML) patients and other myeloid neoplasms (MN) and are considered the earliest clonal event in leukemogenesis. In AML, 50-60% of DNMT3A mutations are heterozygous missense mutations affecting codon R882, which were shown to be dominant-negative in multiple studies. In contrast, there is still a complete lack of data related to the biological impact of a substantial number of widely dispersed non-R882 mutations and their clinical implications. It is possible that mutations in different DNMT3A domains are unique, leading to specific molecular characteristics and clinical phenotypes. Domain-based characterization and phenotypic effects of non-R882 mutations in more granularity is needed to understand the significance of DNMT3A mutations in MN. Methods: We conducted a large retrospective analysis of 16,565 MN patients by screening publicly available databases of AACR GENIE (v 13.1, n=4167), cBioPortal (Cerami et al., 2012, n=3669) along with Karmanos Cancer Institute (n=800) and a previously published metanalytic cohort (Awada et al., Blood 2021 and Kewan et al., Nature Communications, 2023). Clinical characteristics and genomic data were extracted for DNMT3A MT patients to study associated mutational signatures with respect to various biological characteristics. Chi square test was used for analysis of various parameters and KM curves were used to estimate overall survival (OS). Results: DNMT3A MT was found in 17.5% (2903/16,565) of patients in the whole cohort. Of these, 1635 patients had one or more DNMT3A non-R882 mutations, with pAML in 920 (56.3%), sAML in 355 (21.7%), MDS in 259 (15.8%), MPN in 68 (4.2%) and MDS/MPN in 33(2.0%) patients. Among 2088 non-R882 mutations, the most common type is missense (59%, n=1232), followed by frameshift (16.5%, n=345) and nonsense (12.3%, n=256) mutations. 78 (5%) patients had mutations in the N-terminal domain (NTD), 231 (14.1%) in Pro-Trp-Trp-Pro (PWWP) domain, 311 (19%) in ATRX-DNMT3-DNMT3L (ADD) domain and 777 (47.5%) in the methyltransferase (MTase) domain (p=0.0001). Patients with more than one domain or with splice site mutations were excluded. The median age of patients was 67.6 (59-74.8) ys. and male:female ratio showed no difference across domains (p=0.73 & p=0.64 resp.). Patients with NTD MT were less frequently pAML when compared to the other three domains [38.5% vs. 56%, p=0.002]; however, there was no domain distribution pattern observed for sAML and MDS patients. NTD was enriched with abnormal cytogenetics [58% vs 37%, p=0.0034]. NTD MT patients had only numerically lower BM blast percentage, WBC, and platelet counts. In domain-specific analysis, NTD MT had worse OS than non-NTD MT in pAML [8.2 vs. 15 mo., p=0.002], with no difference in sAML and MDS disease groups. PWWP MT had worse OS than non-PWWP MT in sAML alone [5.2 vs 10.6 mo., p=0.012]. ADD MT status was not related to prognostic outcome in any disease groups. Mtase MT had better OS than non-Mtase MT [11 vs 8 mo., p = 0.003] in sAML alone. In NTD MT pAML patients with poor OS, frameshift MT and abnormal karyotype were enriched than in the non-NTD MT group [31% vs 17.9%, p=0.04 and 57.9% vs 29.1%, p = 0.001, resp.]. PWWP MT sAML patients with worse OS had lower missense [43.2 vs 75.5, p=0.000006], higher nonsense [34.1 vs 9.7, p=0.00006] and abnormal karyotype [68.4% vs 49.1%, p= 0.0086] than in non-PWWP MT. Mtase MT sAML patients with better OS had higher missense [80.2% vs 59.2%, p= 0.002] and lower nonsense mutations [7.3% vs 20.8%, p=0.01]. CEBPA [10% vs 1.7%, p=0.02] and CSF3R [10% vs 2.9%, p=0.03] were mostly co-mutated in NTD MT pAML patients and NRAS [17% vs 7%, p=0.016] in PWWP MT sAML patients. Mtase MT sAML patients had less BCOR [6% vs 13%, p=0.03] and WT1 [1.8% vs 7%, p=0.04] than in non-Mtase MT group. Conclusion: non-R882 DNMT3AMT conveys differential prognosis based on the locus. It conferred poor prognosis in pAML, with more frameshift mutations and abnormal cytogenetics. PWWP MT is associated with worse and MTase MT with better outcomes in the sAML group. This is the first analysis to not only explore the non-R882 mutations at length but also reveal the significance of domain specific non-R882 DNMT3A MT in AML. Our study emphasizes the need to include the domain-based impact of DNMT3A mutational status in the prognostic schema for AML, which may help guide treatment plans and encourage further molecular analysis.

Non-Canonical Double Mutant DNMT3A mutations: Clinical and Biological Significance in Myeloid Neoplasms

Introduction: DNMT3A is well accepted as an ancestral lesion in clonal hematopoiesis. Canonical R882 mutations ( MT) enriched in acute myeloid leukemia are considered dominant negative. In contrast, the functional impact of non-R882 lesions is quite heterogeneous and largely present in clonal hematopoiesis of indeterminate potential (CHIP) and myeloid neoplasms (MN). While it has been shown that a single non-R882 DNMT3AMT may not be as functionally impactful as R882, little is known about whether double mutant non-R882 DNMT3A (monoallelic or hemi/heterozygous biallelic) has a similar functional/biological impact as R882 canonical lesion. Studying this aspect is only feasible in a larger cohort of sequencing studies. We performed an extensive analysis to compare the prognostic outcome between single canonical and non-canonical double mutant DNMT3AMT in MN. Methods: Multiple datasets were used to construct a larger cohort of 16,565 MN patients with sequencing data. This included MN patients from Karmanos Cancer Institute and a publicly available metanalytic cohort including Awada et al., Blood 2021, Kewan et al., Nature Communications 2023, cBioPortal (Cerami et al., 2012) and AACR GENIE (v 13.1). Patients with known DNMT3A mutational status were included in the final analysis. Baseline clinical and molecular characteristics were noted. The chi-square test was used to study various parameters described, and the Kaplan-Meier curves were used for survival analyses. Results: DNMT3A was mutated in 18% (2903/16,565) of all MN which included primary acute myeloid leukemia (pAML, n=1910), secondary (sAML, n=531), myeloproliferative neoplasms (MPN, n=100), myelodysplastic syndrome/myeloproliferative neoplasm (MDS/MPN, n=57), myelodysplastic syndrome (MDS, n=305) in the whole cohort. We analyzed 2903 DNMT3AMT MN and further classified them; 41%(n=1191/2903) had single R882, 48%(n=1407/2903) with single non-R882, 8%(n=226/2903) had double mutations at non-R882 locus, 1%(n=39/2903) was homozygous for R882 and 1% (n=40/2903) with mutations at R882 and non-R882 positions. Among non-R882 mutations, missense was more common [38%(85/226)] than nonsense [4%(9/226)], frameshift [1%(2/226)], and all others [57%(130/226)] (including splice-site, insertions, deletions, and other combinations in double non-R882 mutations). Double non-R882 were common in older MN patients [median age 68(37-89) vs. 63(18-96) yrs. in single R882 DNMT3AMT, p=<0.0001]. Double non-R882 compared to single R882 DNMT3AMT were less enriched in pAML and more in sAML [67 vs. 78%, p=0.0012 and 20 vs. 14%, p=0.010 resp]. Double non-R882 was more associated with abnormal karyotype, had lower WBC and BM blast percentage vs. single R882 DNMT3AMT [45 vs. 25%, p<0.0001, median WBC 11(0.5-280) vs 28 (0.1-427)x10 3/mm 3, p<0.010 and median BM blasts 55(0-100) vs 70(0-100),%, p<0.015 resp.]. Median overall survival (OS) was better in single R882 [17 vs. 13 mo. in double non-R882 DNMT3AMT patients, p=0.0013]. Single R882 with normal cytogenetics had better median OS than double non-R882 with normal and abnormal cytogenetics [20 vs. 15 mo., p=0.047 and 20 vs. 11 mo., p=<0.0001 resp.]. Median OS in single R882 was better than in double non-R882 DNMT3AMT p&sAML patients [16 vs. 13 mo., p=0.0267 and 15 vs. 11 mo., p=0.098 resp]. IDH2 (33% vs. 17%, p=<0.0001), BCOR (14% vs. 8%, p=0.003) and ASXL1 (14% vs. 7%, p=0.003) were the most common associated mutations in double non-R882 whereas FLT3 (25% vs. 37%, p=0.0009) and NPM1 (19% vs. 42%, p=<0.0001) were common in single R882 DNMT3AMT MN. Also, a minority [20/226(9%)] of double non-R882were homozygous and had poor median OS [11.5 vs 13.5 mo., p=0.69)] than double non-homozygous non-R882 DNMT3AMT. Our analysis reveals a poor prognosis for double non-R882 vs. single R882 DNMT3AMT patients. Double non-R882 DNMT3AMT patients were older, more enriched with abnormal cytogenetics, and co-mutated with other poor prognostic mutations such as BCOR and ASXL1. BCOR and ASXL1 co-mutated patients are observed to have worse outcomes in myeloid neoplasms (data not shown here). Our ongoing analysis, to be presented at the ASH meeting, will determine if treatment and transplant may alter poor outcomes in this unique subgroup of DNMT3AMT patients. Biallelic homozygous non-R882 DNMT3AMT is rare and carries a worse prognosis, and further studies are needed to elucidate this unique subgroup of AML.

PCR- A Paradigm Shift with A Robust Quantum Jump

Nature Communications has recognized the article titled "Engineered Helicase Replaces Thermocycler in DNA Amplification While Retaining Desired PCR Characteristics" as one of the top 25 best papers published in 2022. Gavrilov et al. (2022) engineered helicase which replaces thermocycler in DNA amplification while retaining desired PCR characteristics. No experiment was so advanced that of Gavrilov et al. LAMP (Loop-Mediated Isothermal Amplification) is limited to producing only short amplicons. SHARP (SSB-Helicase Assisted Rapid PCR) was invented in 2022. We were waiting over a year for reactions from scientific community and then employed SHARP. Gavrilov et al. showed costly PCR machine is not needed for SHARP. It has huge implication for Covid-19 research and prevention in India.

Development of an Industrial Safety System Based on Voice Assistant

Currently, there are limitations in the human–machine interfaces (HMIs) used in industry, either due to the characteristics of users’ cognitive abilities or interfaces, which hinder communication and interaction between humans and equipment. For this reason, this work presents an alternative interaction model based on a voice assistant, Alexa, which promotes more natural, intuitive, direct, and understandable communication. The purpose of this work is the development of an industrial safety system for a controlled electric motor based on Alexa voice assistant, which allows the monitoring of its operating parameters, such as phase current, housing temperature, and rotor vibration, as well as making it possible to control ignition and shut down and change the rotation of the motor with a prior password, as a safety measure. Commercial smart devices and Arduino-compatible modules were used to achieve this, providing them with the Internet of Things (IoT) feature. In addition, several software platforms, such as Blynk, Tuya Smart, Node Red, and Voiceflow, are used to perform data transmission, device management, and programming of the Alexa skill, oriented to the execution of the security and run system. This shows the potential capacity of voice assistants in the industry to deliver information more naturally to humans and obtain optimal notifications. However, problems were evidenced, such as the influence of noise in the environment when communicating with the assistant, the vocalization of words, low voice tones, and accents typical of the language, that will increase the security level of the system and prevent potential identity theft.

Improving social interaction of the visually impaired individuals through conversational assistive technology

PurposeAssistive technology has been developed to assist the visually impaired individuals in their social interactions. Specifically designed to enhance communication skills, facilitate social engagement and improve the overall quality of life, conversational assistive technologies include speech recognition APIs, text-to-speech APIs and various communication tools that are real. Enable real-time interaction. Using natural language processing (NLP) and machine learning algorithms, the technology analyzes spoken language and provides appropriate responses, offering an immersive experience through voice commands, audio feedback and vibration alerts.Design/methodology/approachThese technologies have demonstrated their ability to promote self-confidence and self-reliance in visually impaired individuals during social interactions. Moreover, they promise to improve social competence and foster better relationships. In short, assistive technology in conversation stands as a promising tool that empowers the visually impaired individuals, elevating the quality of their social engagement.FindingsThe main benefit of assistive communication technology is that it will help visually impaired people overcome communication barriers in social contexts. This technology helps them communicate effectively with acquaintances, family, co-workers and even strangers in public places. By enabling smoother and more natural communication, it works to reduce feelings of isolation and increase overall quality of life.Originality/valueResearch findings include successful activity recognition, aligning with activities on which the VGG-16 model was trained, such as hugging, shaking hands, talking, walking, waving and more. The originality of this study lies in its approach to address the challenges faced by the visually impaired individuals in their social interactions through modern technology. Research adds to the body of knowledge in the area of assistive technologies, which contribute to the empowerment and social inclusion of the visually impaired individuals.

Assessing Foreign-Language Students’ Speaking Performance through a Digital Platform: Challenges and Findings

Online assessment of foreign-language learners, particularly of their oral skills, is a challenge for both students and teachers. Assessing language skills face to face, during a conversation between the examiner and the candidate, facilitates natural communication and is likely to provide a more accurate assessment of the student’s language proficiency level. A change in the scenario and the use of digital tools can intimidate students and take away the naturalness and warmth of the interview. The purpose of this paper is to examine the suitability of Blackboard Collaborate as a learning management system for assessing English speaking skill and other factors that influence students’ online performance. A total of 180 students from 7 different undergraduate programs in the fields of technology, environmental sciences and health sciences were assessed according to the structure of a standardized test. Using a mixed-methods approach, their results were contrasted with responses to a final survey to examine the positive or negative impact of online testing on students’ attitudes, performance and achievement. The Blackboard digital platform proves to be a suitable and convenient online framework for optimal speaking performance, and the examiner’s attitude is also a determining factor in students’ success.

Heterogeneous impacts of climate change news on China's financial markets

This paper investigates the influence of climate change news on China's major assets: stocks, exchange rates, treasury bonds and green bonds. Using 1.4 million articles from 2017 to 2022, we create climate change news indices (CCNIs) spanning natural disasters, climate governance, energy transition, climate cooperation, and climate communication. We establish CCNI–return and CCNI–value-at-risk connectedness networks for asset returns and extreme risks, respectively. The findings suggest a moderate effect of climate change news on Chinese financial markets. Both natural disasters and energy transition news affect treasury and green bond returns. Energy transition news notably influences extreme risks for green bonds. Dynamic analysis shows that policies related to climate governance and energy transition can affect treasury and green bond returns in specific periods, while negative news related to natural disasters and energy transition increase extreme risks for stocks and green bonds. Our study underscores the need to enhance China's green financial system in order to effectively address climate change.

Translation as a Learning Method in English Language Teaching

"The Translation Method" in teaching English represents a historically significant approach, rooted in the early methodologies of language instruction. Here we explore the evolution, principles, and controversies surrounding this method within the context of teaching English as a second or foreign language. Historically, translation was extensively used as a primary tool for language learning, aiming to help students understand English texts by comparing them with their native languages. While this method fell out of Favor in communicative language teaching paradigms, it continues to be debated and revisited in modern educational contexts. In this article we delves into the strengths of the translation method, emphasizing its role in developing students' analytical and critical thinking skills. By engaging with complex linguistic structures and cultural nuances, students can deepen their understanding of both languages. Additionally, the method can provide a bridge for learners to grasp challenging concepts in English through the familiarity of their native language. However, the abstract also addresses the criticisms and challenges associated with the translation method. Detractors argue that an overemphasis on translation can hinder natural language acquisition and oral communication skills. Furthermore, it might not align with the communicative and immersive approaches favoured in contemporary language pedagogy, Evolution, Principles, Teaching, etc. The translation method can be integrated into modern language classrooms, emphasizing its judicious use as a supplementary tool. It explores how technology, such as translation software and interactive exercises, can enhance the method's effectiveness. Additionally, the abstract touches on the importance of balancing traditional methods with communicative and immersive techniques, ensuring a comprehensive and adaptable language learning experience.

What drives financial market growth in Africa?

This paper studies the determinants of financial market growth in 41 African countries during the period 1996–2017. Using the International Monetary Fund's Financial Markets Index, the results obtained from the generalized system method of moments reveal that gross domestic product per capita, foreign direct investment, domestic credit to the private sector, interest rate, natural resource rents, information and communication technology, and human capital have a positive and significant effect on financial market growth in Africa, while the level of investment, savings rate, trade openness, and the consumer price index are significant but negative. Moreover, additional results reveal that the effect of these determinants depends on the subregion in which the financial markets are located. Based on these results, we propose that African country leaders take into account specific subregional conditions to foster the growth of their financial markets.

Speech data collection system for KUI, a Low resourced tribal language

<p>A new generation of speech translation technology is being developed to enable natural cross-language communication. Research efforts must focus on large vocabulary, spontaneous speech, and speaker variances to accommodate the varying demands of speech recognition technologies. These are important issues that need to be resolved for the general application of voice recognition in realistic settings. Most languages with limited resources don’t even have any speech data. Creating speech corpora is extremely difficult and time-consuming. Among all, KUI is regarded as one of the low-resource languages. In this paper, we developed the speech dataset for the KUI language to document and preserve their culture, tradition, and history for future generations. We also discuss the design, data collection procedures, and implementations and outline the different research possibilities using our KUI dataset. This paper mainly describes the GUI and method for the collection of KUI speech more quickly. In this section, the statistics of the people who helped and contributed to the collection of this KUI dataset have been provided. This study details a novel method of gathering data for any speech dataset. Using this process, we collected 60 hours of speech data sampled at 16 kHz by three different devices such as a Zoom recorder, Mobile, and Laptop from 80 different speakers. Each speaker contributed 500 sentences in the KUI language. A GUI application is designed to capture the speeches of numerous speakers in the KUI language. Several guidelines are proposed and used for the collection of the KUI speech dataset. All the guidelines are based on real-time experience gained during the data collection process by our team members.</p>

An intelligent conversational agent for educating the general public about HIV

The article presents a Spanish conversational agent that focuses on raising awareness about HIV. The agent aims to provide natural communication, personalized information based on user requests, and a centralized source of information about HIV. The core of the agent’s logic is formed by a natural language understanding conversational model, supported by a knowledge base of medical responses and real conversations with users. An empirical study was conducted with 71 users to evaluate the agent’s effectiveness as a sexual health educational tool. The results show that HIV knowledge raised by 18.44% after using the agent. That, and the positive user experience support the agent’s role as a tool for raising HIV prevention and awareness.

Effect of productive capacities on tax revenue mobilization: Evidence from Sub‐Saharan African countries

This paper analyzes the effects of productive capacities on tax revenue mobilization in 37 Sub‐Saharan African countries. Using the Generalized Method of Moment (GMM) approach, the results show that productive capacities measured by the aggregate Productive Capacity Index (PCI) and its eight components, namely human and natural capital, energy, transport, Information and communication technologies, private sector, institutions and structural change positively and significantly affect total tax revenue mobilization. For example, an increase in one point of the PCI corresponds to an increase in total tax revenues by 0.0016 point. The effect of productive capacities also remains positive and significant on tax revenues, even when disaggregated into direct and indirect taxes. This paper contributes empirically to highlighting the importance of productive capacity in tax revenue mobilization. Hence, strengthening productive capacities is important to enhance tax revenue mobilization in Sub‐Saharan African countries. To meet the current challenges of mobilizing the fiscal resources needed to meet international agendas, Sub‐Saharan African countries must not only work to strengthen overall productive capacity, but also promote the quality of institutions, transport and energy, invest in human capital, create the conditions for real structural transformation, promote good digital governance and a more dynamic private sector.

Who is calling? Optimizing source identification from marmoset vocalizations with hierarchical machine learning classifiers.

With their highly social nature and complex vocal communication system, marmosets are important models for comparative studies of vocal communication and, eventually, language evolution. However, our knowledge about marmoset vocalizations predominantly originates from playback studies or vocal interactions between dyads, and there is a need to move towards studying group-level communication dynamics. Efficient source identification from marmoset vocalizations is essential for this challenge, and machine learning algorithms (MLAs) can aid it. Here we built a pipeline capable of plentiful feature extraction, meaningful feature selection, and supervised classification of vocalizations of up to 18 marmosets. We optimized the classifier by building a hierarchical MLA that first learned to determine the sex of the source, narrowed down the possible source individuals based on their sex and then determined the source identity. We were able to correctly identify the source individual with high precisions (87.21%-94.42%, depending on call type, and up to 97.79% after the removal of twins from the dataset). We also examine the robustness of identification across varying sample sizes. Our pipeline is a promising tool not only for source identification from marmoset vocalizations but also for analysing vocalizations of other species.

Using Affect as a Communication Modality to Improve Human-Robot Communication in Robot-Assisted Search and Rescue Scenarios

Emotions can provide a natural communication modality to complement the existing multi-modal capabilities of social robots, such as text and speech, in many domains. We conducted three online studies with 112, 223, and 151 participants, respectively, to investigate the benefits of using emotions as a communication modality for Search And Rescue (SAR) robots. In the first experiment, we investigated the feasibility of conveying information related to SAR situations through robots' emotions, resulting in mappings from SAR situations to emotions. The second study used Affect Control Theory as an alternative method for deriving such mappings. This method is more flexible, e.g. allows for such mappings to be adjusted for different emotion sets and different robots. In the third experiment, we created affective expressions for an appearance-constrained outdoor field research robot using LEDs as an expressive channel. Using these affective expressions in a variety of simulated SAR situations, we evaluated the effect of these expressions on participants' (in the role rescue workers) situational awareness. Our results and proposed methodologies (a) provide insights on how emotions could help conveying messages in the context of SAR, and (b) show evidence on the effectiveness of adding emotions as a communication modality in a (simulated) SAR communication context.

A Preliminary Investigation of the Effects of Open Review on Citation Impact

ABSTRACTThis study investigates the impact of open review on citation counts of academic articles. By collecting articles published in the material science area of Nature Communications from 2014 to 2018, we exploit the adoption of voluntary open review in 2016 to examine how article citation counts are associated with open review using propensity score matching and regression analysis. OLS regression results show that open review comes at the expense of fewer citations received by articles. Specifically, open‐reviewed articles received 44% fewer citations than their non‐open‐reviewed counterparts. An additional mediation analysis reveals that this decrease in citations may be partially attributed to the lengthening of the review cycle of articles that were open reviewed–open‐reviewed articles experienced 16% longer review cycles; every 16% extension of the review cycle led to 5.8% fewer citations. Results remained qualitatively similar when we restricted the citation windows to three years since publication. Contrary to previous findings concerning the positive effects on articles’ citation impact, our preliminary results call for additional efforts in identifying the costs and benefits associated with open review.

Фактор клишированности в описании словосодержащего семиозиса: норма и границы языка

The article presents a number of observations on the methods of not quite convincing definition of the " language norm" and "language boundaries" within the framework of the traditional language model, the main methodological constant of which is a priori confidence that the content ("meaning", "meaning", "semantics", " content plan, etc.) exists in direct connection with the verbal substrate. As a result, contradictory statements arise: “The norm exists objectively”, at the same time “The norm exists subjectively”; "Norm is single", at the same time "Norm is multiple"; “The norm is manifested in synchrony”, at the same time “The norm is manifested in diachrony”; “Language coincides with the norm”, at the same time “Language does not coincide with the norm”; “Language belongs to the researcher”, at the same time “Language belongs to the user”; “Language has unity”, at the same time “Language consists of varieties of a language”. To solve the same problems, the concept of cliché and semiotic action is proposed as tools, which more correctly reflect the essence of natural speaking-writing and at the output give a more harmonious picture (model) of what is happening. According to the communicative model, in natural communication, the source of content produced and received is personal semiotic influence (polymodal, multifactorial, multichannel, not necessarily word-containing). In order to achieve changes in external cognitive states (which have not yet occurred at the time of the action, but are only planned), the semiotic actor makes attempts to influence, manifesting actional modes of his consciousness under given conditions in complex ways. In view of this, in a natural act, the novelty sought by the actor is generated and understood, which constitutes the meaning formation of a given semiotic act. The concept of cliché in relation to words and other "signs", assuming the procedural (actional) principle of formation of any semiotic content, allows us to separate the clichwd (mechanical, meaningless, behavioral) "language", including verbal, from the meaning-forming semiotic influence, to emphasize the deep conventionality of construction "systemic" and "universal" "language".

Investigating AI Teammate Communication Strategies and Their Impact in Human-AI Teams for Effective Teamwork

Recently, AI is integrating into teams to collaborate with humans as a teammate with the goal of achieving unprecedented team outcomes. Much of the coordination between humans and AI teammates relies on human-AI communication, which is challenging due to AI's limitations on natural language communication. Thus, it is essential to identify and develop effective communication strategies for AI teammates in human-AI teams to facilitate the coordination process. Through interviews with 60 participants who collaborated with an AI teammate in a multiplayer online game, in this paper, we explore communication strategies that humans expect AI teammates to apply to support human-AI coordination and collaboration in dyadic teaming environments, and how the AI teammate's communication can impact teaming processes. Our findings highlight four communication strategies AI teammates should apply to support their coordination with humans in dyadic teaming environments. We also find that AI teammates' proactive communication with humans could facilitate the development of human trust and situation awareness, whereas AI lacking such proactive communication is often not perceived as a teammate. Our study extends the current CSCW/HCI research on human-AI communication in teaming environments by shedding light on how communication should be structured in dyadic human-AI teams for effective and smooth collaboration.

Fish-inspired robotic algorithm: mimicking behaviour and communication of schooling fish.

This study aims to present a novel flocking algorithm for robotic fish that will aid the study of fish in their natural environment. The algorithm, fish-inspired robotic algorithm (FIRA), amalgamates the standard flocking behaviors of attraction, alignment, and repulsion, together with predator avoidance, foraging, general obstacle avoidance, and wandering. The novelty of the FIRA algorithm is the combination of predictive elements to counteract processing delays from sensors and the addition of memory. Furthermore, FIRA is specifically designed to work with an indirect communication method that leads to superior performance in collision avoidance, exploration, foraging, and the emergence of realistic behaviors. By leveraging a high-latency, non-guaranteed communication methodology inspired by stigmergy methods inherent in nature, FIRA successfully addresses some of the obstacles associated with underwater communication. This breakthrough enables the realization of inexpensive, multi-agent swarms while concurrently harnessing the advantages of tetherless communication. FIRA provides a computational light control algorithm for further research with low-cost, low-computing agents. Eventually, FIRA will be used to assimilate robots into a school of biological fish, to study or influence the school. This study endeavors to demonstrate the effectiveness of FIRA by simulating it using a digital twin of a bio-inspired robotic fish. The simulation incorporates the robot's motion and sensors in a realistic, real-time environment with the algorithm used to direct the movements of individual agents. The performance of FIRA was tested against other collective flocking algorithms to determine its effectiveness. From the experiments, it was determined that FIRA outperformed the other algorithms in both collision avoidance and exploration. These experiments establish FIRA as a viable flocking algorithm to mimic fish behavior in robotics.

HUMAN ANTIMICROBIAL PEPTIDES (REVIEW)

Relevance. The relevance of the antimicrobial peptides study is justified by the serious problem of antibiotic resistance, which presents a worrisome prospect of a significant number of deaths and economic losses in the future. In recent years, scientists have increasingly focused on natural substances, such as antimicrobial peptides, which do not induce bacterial resistance and may be safer for the human body compared to antibiotics. Aim of the research. This review article aims to structure the scientific literature on exploring the potential applications and generation of peptide complexes from the human body. Material and methods. The following databases were used for information retrieval: PubMed, American Society for Microbiology, ResearchGate, Frontiers Research Foundation, Public Library of Science, BioRxiv, Nature Communications, European Commission. Results. The paper provides a description, structure, history of discovery, and research on antimicrobial peptides derived from the human body. The biological properties of these peptides are outlined. The prospects for further studying their properties and developing new-generation antibacterial drugs from them are presented. Conclusions. The investigation of human antimicrobial peptides and the development of innovative drugs based on them represent a promising direction in modern biotechnology. The systematic analysis of scientific data regarding the possibility of obtaining and utilizing peptide complexes from the human body signifies a significant step in the development of novel and effective antimicrobial drugs capable of overcoming the growing threat of antibiotic resistance and aiding in the fight against infectious diseases.

A constrained multi-channel hear-through filter design approach using active control formulations

In many daily communication environments, especially during a pandemic era, partitioning structures are placed between people for security or virus concerns, for example, partitions in classrooms, banks, and retail stores. Distortion occurs when sound propagates through these partitions, which can cause distractions in communication and degrade the service quality. In the current work, a constrained multi-channel active hear-through system is proposed to provide a solution to provide more natural sound communication environments and prevent sound distortions due to partitioning structures. The proposed method can preserve both the spectrum and the spatial distribution of the original sound field (the sound field when the partition is absent). This research opens the potential for future development of multi-channel two-way communication systems and improvement in existing augmented reality techniques. Experimental results show that, compared with the traditional direct inverse filter design method, the proposed method can reduce the comb-filtering effect effectively. The constraints applied to the filter design procedure can also prevent instability caused by the acoustic feedback loop.