bluuebunny/crossref_metadata_2025 huggingface dataset:
Learning from COVID-19: Government Leaders’ Perspectives to Improve Effective Risk Communication
Authors: Savoia Elena , Piltch-Loeb Rachael , Stanton Eva H. , Koh Howard K.
Published: November 2023

Background
The coronavirus disease 2019 (COVID-19) pandemic highlighted the challenges of effective emergency risk communication (ERC) to protect public health, including the difficulty in tackling the spread of inaccurate information. This study aimed to understand those challenges and potential solutions by interviewing leading government spokespersons and their advisors from around the world with experience during large scale emergencies. Interviews were conducted with 27 individuals representing governments from 19 countries across five continents. Thematic analysis, using both a deductive and inductive approach, organized and identified salient themes and patterns that emerged from the interview data.
Results
The thematic analysis of the interviews’ data led to the identification of 9 principles of communication: 1) Timeliness, 2) Transparency, 3) Coordination, 4) Accuracy and Consistency, 5) Accountability and Integrity, 6) Independence from politics, 7) Responsiveness, 8) Equity, 9) Trust and Empathy. We also developed 36recommendations actionable by government agencies to enhance the practice of the 9 principles. Examples include the need for: proactive communication strategies, permanent communication task forces integrated into preparedness and response efforts, robust processes to enhance open discussion of controversial topics within government agencies, clarification of how various branches of governmentcoordinate to oversee specific aspects of the overall communication, and development of relationships across public and private entities ahead of a crisis.
Conclusions
Our findings suggest key practical recommendations for leaders of government agencies to enhance ERC capabilities going forward. Before a crisis, they must constantly review internal processes and integrate ERC functions into overall communication planning efforts. During a crisis, they must coordinate roles and responsibilities across branches of governments, strive to communicate to a range of populations to uphold equity, maintain transparency by avoiding information voids on controversial issues and build trust by building relationships with a variety of community leaders. After a crisis, government agencies should continue the practice of social listening to hear more about the public’s informational needs, strengthen civic participation processes, and understand how an always evolving information environment can best be leveraged during future crises.
Half dome carbon nitride nanostructures
Authors: Torre Alessandro La
Published: November 2023

We report on a new form of nanoscale carbon nitride in the shape of single layer half dome structures grown on the step edges of boron nitride sheets. The half-dome structures are formed spontaneously at high temperature in high vacuum using Fe2O3 capped with N(CH3)4OH supported on BN sheets. During the combustion process, the BN support first acted as a reducing agent for the transformation of the iron oxide in metallic iron and, second, as a source of nitrogen that permitted the transformation of the organic capping agent in sp1 CN chains linked with sp2 CN domains. During Ostwald ripening, smaller nanoparticles migrate towards larger nanoparticles, and when the nanoparticles cross the step edges of few-layer boron nitride sheets, a half-dome structure is formed. The propensity of FeNPs to catalyse the formation of the half dome containing cyanopolyynes species has been shown for the first time. The coexistence of carbon nitride atoms in two well-defined hybridization states within CN@HDS may offer functional features characteristic of carbyne and carbon nitride.
Ultrasonographic and power doppler parameters of nails fail to differentiated between onychodystrophy in patients with psoriasis vulgaris or psoriatic arthritis
Authors: Tanaka Anber Ancel , Werner Betina , Bragatto Annelise Correa Bueno , Skare Thelma Larocca , Stadler Bárbara
Published: November 2023

Background: Nail involvement is frequent in patients with psoriasis (Pso) and psoriatic arthritis (PsA) and there is a relationship between nail involvement and inflammation of the enthesis. The main objective of the present study is to describe the ultrasound findings and clinical characteristics of nails from patients with psoriasis and psoriatic arthritis with and without nail dystrophy.
Methods: A cross-sectional study including consecutive patients with PsO and PsA was carried out. The study patients were divided into 4 groups, totaling 120 participants. Group 1: patients with psoriasis vulgaris and clinically normal nails; Group 2: patients with psoriasis vulgaris and onychodystrophy; Group 3: patients with psoriatic arthritis and clinically normal nails; Group 4: patients with psoriatic arthritis and onychodystrophy; All patients were submitted to dermatological and rheumatological clinical analysis. Ultrasound examinations was performed by a single examiner, blinded to all clinical data, with ultrasound high resolution, in B-mode or gray-scale (GS), Power Doppler (PD) and Spectral Doppler.
Results: A significant difference was found between the groups regarding the variable Psoriasis Area and Severity Index (PASI) (p = 0.008) and body surface area (BSA) (p = 0.005), with patients with psoriatic arthritis having lower PASI and BSA compared to patients with only cutaneous psoriasis. A positive relationship was found with the average ultrasound thickness of the nail bed and the Nail Psoriasis Severity Index (NAPSI)by the spermann test (p = 0.0072). When we grouped patients with psoriasis and psoriatic arthritis, there was no significant difference between the cutaneous psoriasis groups and the psoriatic arthritis groups in terms of nail plate GS (p = 0.44), nail bed PD (p = 0.12).
Conclusion: Greater nail bed thickness indicates early psoriatic nail disease, as confirmed in our study correlating NAPSI with nail bed thickness. Ultrasonography is a low-cost exam, promising in the evaluation, showing that the ultrasound grayscale is consistent with those who have dystrophic nails, but it can't distinguish psoriasis from psoriatic arthritis, even in those with nail dystrophy.
Classification of Human Walking Context using a Single-Point Accelerometer
Authors: Baroudi Loubna , Barton Kira , Cain Stephen Matthew , Shorter Kenneth Alex
Published: November 2023

Real-world walking data offers rich insights into a person's mobility. Yet, daily life variations can alter these patterns, making the data challenging to interpret. As such, it is essential to integrate context for the extraction of meaningful information from real-world movement data. In this work, we leveraged the relationship between the characteristics of a walking bout and context to build a classification algorithm to distinguish between indoor and outdoor walks. We used data from 20 participants wearing an accelerometer on the thigh over a week. Their walking bouts were isolated and labeled using GPS and self-reporting data. We trained and validated two machine learning models, random forest and ensemble Support Vector Machine, using a leave-one-participant-out validation scheme on 15 subjects. The 5 remaining subjects were used as a testing set to choose a final model. The chosen model achieved an accuracy of 0.941, an F1-score of 0.963, and an AUC of 0.931. This validated model was then used to label the walks from a different dataset with 15 participants wearing the same accelerometer. Finally, we characterized the differences between indoor and outdoor walks using the ensemble of the data. We found that participants walked significantly faster, longer, and more continuously when walking outdoors compared to indoors. These results demonstrate how movement data alone can be used to obtain accurate information on important contextual factors. These factors can then be leveraged to enhance our understanding and interpretation of real-world movement data, providing deeper insights into a person's health.
Extracellular vesicle-mediated Transfer of miRNA-1 from Primary tumor Repress Distant Metastasis Growth
Authors: Cho Je-Yoel , Kim Hui-Su , Lee Kang-Hoon , Son Keun-Hong , Shin Tae-Jin
Published: November 2023

Metastases originate from primary tumors and conquer distant organs. Growing evidence suggest that metastases are under control of primary tumors even out of the primary territory, however, how primary tumors remotely control metastases remains unclear. Here, we discovered a molecular mechanism by which a primary tumor suppresses the metastatic growth. Interestingly, we found that extracellular vesicles (EVs) derived from a primary tumor has an ability to inhibit the growth of metastases in vitro and in vivo. miR-1 was particularly enriched in the primary tumor-derived EVs (pTDEs) and responsible for the suppression of metastatic growth. Mechanistically, intracellular ROS and DNA damage were induced, which led to the cell cycle arrest. Collectively, our data demonstrate that the primary tumor restricts distant metastatic cancer by miR-1 in pTDEs which can potentially be used as an anticancer drug for metastasis.
Modelling Optimal Release Behaviour of Software under Fuzzy environment involving Change point
Authors: Kushwaha Shivani , Kumar Ajay
Published: November 2023

A software release schedule has been explored in this paper based on cost and reliability considerations using a change point paradigm. The goal of this study is to model the uncertainties that are present in the estimated model parameters. First, the LSE technique has been used to estimate unknown model parameters and then, by using Triangular Fuzzy Numbers (TFNs), fuzzification of the parameters has been done. As software testing is done by humans, and their behaviour is subjective, the notions of fuzzy set theory is extremely valuable in developing SRGMs. Finally, the predicted total software cost and fuzzy reliability growth are calculated. Using software testing data from real-world applications at different levels of uncertainty, the performance of the proposed model is illustrated. The computed results indicate that the proposed model produces a realistically more accurate insight of reliability metrics, specifically software reliability and total software cost in a fuzzy environment.
Social network structure is robust to parasite induced changes in contact behavior
Authors: Morris Alex M.M , Innocent Giles T , Cunningham Emma J.A , Croft Darren P , Athanasiadou Spiridoula , Hutchings Michael R , Smith Lesley A
Published: November 2023

Understanding how parasitism may affect social behavior and social networks is key to understanding the impact of infection on a population. Infection can disrupt social networks by altering the behavior of both infected individuals (e.g. by reducing activity) and the behavior of uninfected individuals (e.g. avoiding sick individuals), both of which can have an impact on social group dynamics and parasite transmission. Here we test experimentally how parasitism affects social contact behavior and social network structure using a common parasite infection of sheep. Three treatment groups, each with 4 replicate social groups were established (i) Parasitised; all lambs were infected with a parasitic nematode, (ii) Nonparasitised; all lambs remained uninfected (iii) Mixed; part of each group were infected, and part of the group remained uninfected. Contact behaviours of each individual was recorded using proximity loggers during four phases of infection (pre-parasite, pre-patent, patentparasite, post-parasite). We found infected individuals in the parasitised and mixed groups reduced contact frequency following infection. Infected individuals in mixed groups however reduced contact frequency to a greater extent than infected animals in the fully parasitised group. Despite the reduction in contacts between infected animals in the mixed group, the social network structure was unaffected, as non-infected individual’s maintained pre-parasite levels of social interactions with their infected conspecifics. These results demonstrate how infection can impact the social behavior of all animals within a group, and how the expression of behavioral change may depend on the parasitic status of all group members and the response of uninfected conspecifics.
Exploiting Cooperative Pathogen Behavior for Enhanced Antibiotic Potency: A Trojan Horse Approach
Authors: Mutlu Alper , Vanderpool Emily , Rumbaugh Kendra , Diggle Stephen , Griffin Ashleigh
Published: November 2023

Antimicrobial resistance poses an escalating global threat, rendering traditional drug development approaches increasingly ineffective. Thus, novel alternatives to antibiotic-based therapies are needed. Exploiting pathogen cooperation as a strategy for combating resistant infections has been proposed but lacks experimental validation. Empirical findings demonstrate the successful invasion of cooperating populations by non-cooperating cheats, effectively reducing virulence in vitro and in vivo. The idea of harnessing cooperative behaviors for therapeutic benefit involves exploitation of the invasive capabilities of cheats to drive medically beneficial traits into infecting populations of cells. In this study, we employed Pseudomonas aeruginosa quorum sensing cheats to drive antibiotic sensitivity into both in vitro and in vivo resistant populations. We demonstrated the successful invasion of cheats, followed by increased antibiotic effectiveness against cheat-invaded populations, thereby establishing an experimental proof of principle for the potential application of the Trojan strategy in fighting resistant infections.
Distribution structure of the great gerbil (Rhombomys opimus Licht, 1823) in the western part of the Betpakdala desert of Kazakhstan: biotransformation of arid lands
Authors: Abdel Ziyat Zh. , Meka-Mechenko Tatyana V. , Zhumadilova Zauresh B. , Shakiev Nurbol N. , Yessimseit Duman T. , Abdeliyev Beck Z. , Mussagaliyeva Raikhan S. , Abdirassilova Aigul A. , ISSAEVA Svetlana B. , Meka-Mechenko Vladimir G. , Sadovskaya Veronika P. , Sayakova Zaure Z. , Kulemin Maxim V.
Published: November 2023

It is well known that the earth's climate changes that occur as a result of global climate change are changing the biosphere of our planet as a whole. As a result, many animal species change their geographical ranges, seasonal activity, migration patterns, abundance and interaction with other species, including microorganisms, the facts of which are observed in the deserts of Kazakhstan. The main carrier of the causative agent of the plague in the desert natural focus of the Betpakdala plague of Kazakhstan is the great gerbil (Rhombonus opimus), where the plague epizootic was first discovered in 1959, the area of which was then 30.0 thousand. km2 until 1990. Due to the rapid industrial development of the Betpakdala desert, the impact of global climate change on earth and other factors over the past 30 years, the area of this natural plague outbreak has increased by 50.12% (60.14 thousand km2) in the northern direction due to the biological transformation of the area of the main carrier, which led to the expansion of plague epizootics among rodents. At the same time, the plague microbe was also involved in the transformation process, increasing its natural area of the pistil (the area of distribution of the microbe), which increased the risk of infection of people with plague infection. The paper presents our results of epizootological monitoring for the period 2009–2022 (50.0 thousand km2) and laboratory studies of 522376 samples of field material for plague. The structure of the focus was shown, and the reason for the expansion of the settlement area of the rodent population was revealed. The number of sectors with different levels of epidemic danger and epizootic activity were determined, and the main phenotypic and genotypic properties of Yersinia pestis strains circulating in this natural plague focus were also given.
The January 2022 Hunga eruption cooled the southern hemisphere in 2022
Authors: Gupta Ashok , Mittal Tushar , Fauria Kristen , Bennartz Ralf , Kok Jasper
Published: November 2023

Explosive volcanic eruptions can profoundly cool Earth's climate by injecting sulfate aerosols into the stratosphere1. However, the submarine explosive eruption of Hunga Volcano in 2022 was unusual in that it injected into the stratosphere a massive amount of water vapor2,3, which warms the climate, and a much smaller amount of sulfur dioxide4 than previous explosive eruptions of similar magnitude. It has therefore been proposed that the Hunga eruption produced a net warming effect due to enhanced stratospheric water vapor, thereby increasing the chances that Earth’s temperature would temporarily breach the 1.5° C threshold specified in the Paris Climate Accord5. However, accounting for the cooling produced by sulfate aerosols is crucial in understanding the effects of Hunga eruption6. Here, we combine satellite observations of stratospheric composition with idealized radiative transfer model simulations to show that the Hunga eruption produced a net instantaneous clear-sky radiative energy loss of -0.48 ± 0.04 Wm-2 at the top-of-atmosphere in the southern hemisphere, resulting from its effects on stratospheric water vapor, aerosols, and ozone. Using an emulator of a two-layer energy balance model7-8, we estimate that this energy loss resulted in a cooling of -0.1 K in the southern hemisphere at the end of 2022 following the eruption. We find that the cooling produced by sulfate aerosols due to the scattering of sunlight overwhelmed the warming by stratospheric water vapor. This occurred in part because the sulfur dioxide turning into sulfate aerosols affecting optical depth was unusually efficient compared to previous subaerial eruptions. We also find that the decreased stratospheric ozone led to a cooling effect that nearly balanced the warming caused by increased stratospheric water vapor. We thus conclude that the Hunga eruption did not warm5, but rather cooled the planet with a strong hemispherical asymmetry.
Continuously tuneable laser in the full visible spectrum formed in 10 minutes with cholesteric liquid crystal cells based on the electrothermal effect
Authors: Jeong Mi-Yun , Kwak Keumcheol , Nam Youngwoo , Choi Hyeon-Jong
Published: November 2023

Wavelength-tuneable lasers could play a crucial role across many fields, and their applications continue to expand with advancements. Cholesteric liquid crystal (CLC) devices have been developed and have enabled good wavelength-tuneable lasers. In CLC devices, pitch control is required to tune the desired wavelength. However, pitch control takes a long time and is difficult, which limits the speed and range of laser wavelength tuning. Here, by applying a voltage once, we realized CLC pitch gradient arrays that achieve continuous wavelength tuning over 500 nm in only 10 min through the electrothermal effect while continuously generating laser lines in the full visible spectrum. The laser wavelength could be rapidly tuned over the full visible spectrum by moving within the array in the wedge cell. This new device has potential in many fields that require active laser tuning and could be the basis for future practical laser devices in the optical industry.
Performance analysis of FSO Communications in desert environments
Authors: Sliti Maha , Mrabet Manel
Published: November 2023

Free Space Optical (FSO) communication systems offer high-speed data transfer and secure connectivity, making them suitable for various applications. However , severe weather, especially in desert environments like duststorms and fogs, can significantly impact their efficiency. This paper analyzes the performance of FSO communication systems in desert environments, focusing on the interaction between FSO technology and challenging atmospheric conditions like duststorms and fogs. The research aims to enhance the design and operation of FSO communication systems in these environments, where reliable connections are critical. The study explores various modulation techniques (AM, Duobinary RZ, Modified Duobinary RZ, RZ, and NRZ) to mitigate weather-induced attenuation under duststorm and fog conditions. Real-time visibility data from the meteorological department and Optisystem software were used to estimate attenuation under duststorm and fog conditions in Qassim, Saudi Arabia. The study found that the duo-binary RZ modulation technique offers better performance parameters for maximum link distance, a better Q-factor value, a lower bit error rate, and better received optical power at 25 dB/km attenuation.
Statistical analysis of flow field variations via independent component analysis
Authors: Laichter J. , Kranz P. , Kaiser S.A.
Published: November 2023

The link between in-cylinder flow and subsequent combustion in a single-cylinder gasoline spark-ignition (SI) engine operating slightly lean is analyzed via independent component analysis (ICA). Experimentally, the two in-plane components of the velocity are measured in the central cylinder plane by high-speed particle image velocimetry (PIV) with the engine running at 1500 rpm in skip-fired mode. In 213 cycles, measurements are made during the late compression stroke before ignition with approximately 1° crank angle temporal resolution. ICA then decomposes the set of 213 flow fields at each time step, yielding a set of “typical” flow patterns – the independent components (IC). The temporal coherence between the ICs is then examined in a persistence analysis, comparing each IC with the one from the previous time step starting at ignition timing and going backwards in time. The results show which ICs persist how long throughout the compression stroke. To investigate the link between the ICs and combustion, the crank angle at which 10% of the fuel are burned (CA10) in each cycle is correlated with the extent to which a given IC can be found in each flow field. For the operating condition examined here, this analysis finds that a vortex center around the spark plug is strongly linked with fast-burning combustion, while slow-burning cycles typically have a vortex center located on the exhaust side.
Physiologically Based RadioPharmacoKinetic (PBRPK) Modeling to Simulate and Analyze Radiopharmaceutical Therapies: Studies of Non-Linearities, Multi-Bolus Injections, and Albumin Binding
Authors: Fele-Paranj Ali , Saboury Babak , Uribe Carlos , Rahmim Arman
Published: November 2023

Background: We aimed to develop a publicly shared computational physiologically based pharmacokinetic (PBPK) model to reliably simulate and analyze radiopharmaceutical therapies (RPTs), including probing of hot-cold ligand competitions as well as alternative injection scenarios and drug designs, towards optimal therapies.
Results: To handle the complexity of PBPK models (over 150 differential equations), a scalable modeling notation called the ”reaction graph” is introduced, enabling easy inclusion of various interactions. We refer to this as physiologically based radiopharmacokinetic (PBRPK) modeling, fine-tuned specifically for radiopharmaceuticals. As three important applications, we used our PBRPK model to (i) study the effect of competition between hot and cold species on delivered doses to tumors and organs at risk. In addition, (ii) we evaluated an alternative paradigm of utilizing multi-bolus injections in RPTs instead of prevalent single injections. Finally, (iii) we used PBRPK modeling to study the impact of varying albumin-binding affinities by ligands, and the implications for RPTs.
We found that competition between labeled and unlabeled ligands can lead to non-linear relations between injected activity and the delivered dose to a particular organ, in the sense that doubling the injected activity does not necessarily result in a doubled dose delivered to a particular organ (a false intuition from external beam radiotherapy). In addition, we observed that fractionating injections can lead to a higher payload of dose delivery to organs, though not a differential dose delivery to the tumor. By contrast, we found out that increased albumin-binding affinities of the injected ligands can lead to such a differential effect in delivering more doses to tumors, and this can be attributed to a number of factors that PBRPK allows us to probe.
Conclusions: Advanced computational PBRPK modeling enables simulation and analysis of a variety of intervention and drug design scenarios, towards more optimal delivery of RPTs.
The Biomechanical Effects of Backpack Weight on Foot Plantar Pressures Among Long-Distance Hikers: Observational study
Authors: Moya-Cuenca Coral , Zúnica-García Sara , Gracia-Sánchez Alba , García-Cremades Santi , Oltra-Romero Ana María , Chicharro-Luna Esther
Published: November 2023

Background Hiking is a prevalent activity with most participants carrying gear in backpacks. Though health experts recommend backpack weight not surpass 10–15% of a hiker's body weight, the effects on foot plantar pressures remain unclear.Methods Our cross-sectional observational study aimed to assess how varying backpack weights impact foot plantar pressure distribution during walking. We enlisted hikers who had covered at least 20 km in the preceding 24 hours. We recorded participants' sociodemographic and clinical details and utilized the Podoprint® platform to measure the area, force, and pressure on the forefoot, rearfoot, and entire foot. Measurements were taken without a backpack, with the hiker's actual backpack, and with backpacks loaded to 10% and 20% of the hiker's body weight.Results Results revealed a consistently higher force on the right foot across all conditions. Relative to no backpack, forefoot pressure increased by 5.41% and 8.73% with backpacks weighing 10% and 20% of body weight, respectively (p = 0.005), while increases for the rearfoot were 5.01% and 10.17% (p = 0.015), and for the entire foot, 5.04% and 9.61% (p = 0.002).Conclusions Surpassing 10% of body weight significantly altered foot pressure in both static and dynamic analyses. Our findings underscore the importance of adhering to recommended backpack weight guidelines to mitigate undue foot pressure during hiking.
A Privacy-Preserving Federated Learning Framework for Blockchain Networks
Authors: Abuzied Youssif , Ghanem Mohamed , Dawoud Fadi , Gamal Habiba , Soliman Eslam , Sharara Hossam , Elbatt Tamer
Published: November 2023

In this paper we introduce a scalable, privacy-preserving, federated learningframework, coined FLoBC, based on the concept of distributed ledgers underlyingblockchains. This is motivated by the rapid growth of data worldwide, especiallydecentralized data which calls for scalable, decenteralized machine learning mod-els which is capable of preserving the privacy of the data of the participatingusers. Towards this objective, we first motivate and define the problem scope. Wethen introduce the proposed FLoBC system architecture hinging on a number ofkey pillars, namely parallelism, decentralization and node update synchroniza-tion. In particular, we examine a number of known node update synchronizationpolicies and examine their performance merits and design trade-offs. Finally, wecompare the proposed federated learning system to a centralized learning systembaseline to demonstrate its performance merits. Our main finding in this paperis that our proposed decentralized learning framework was able to achieve com-parable performance to a classic centralized learning system, while distributingthe model training process across multiple nodes without sharing their actualdata. This provides a scalable, privacy-preserving solution for training a varietyof large machine learning models.
TOMAS: Topology Optimization of Multiscale Fluid-Flow Devices using Variational Autoencoders and Super-Shapes
Authors: Padhy Rahul Kumar , Suresh Krishnan , Chandrasekhar Aaditya
Published: November 2023

In this paper, we present a framework for multiscale topology optimization of fluid-flow devices. The objective is to minimize dissipated power, subject to a desired contact-area. The proposed strategy is to design optimal microstructures in individual finite element cells, while simultaneously optimizing the overall fluid flow. In particular, parameterized super-shapes are chosen here to represent microstructures since they exhibit a wide range of permeability and contact area. To avoid repeated homogenization, a finite set of these super-shapes are analyzed a priori, and a variational autoencoder (VAE) is trained on their fluid constitutive properties (permeability), contact area and shape parameters. The resulting differentiable latent space is integrated with a coordinate neural network to carry out a global multi-scale fluid flow optimization. The latent space enables the use of new microstructures that were not present in the original data-set. The proposed method is illustrated using numerous examples in 2D
Overview of the proposed method: A dataset of shape parameters of super-shapes, contact areas, and homogenized permeability tensors is used to train a variational autoencoder (VAE). The resulting latent space is then used for global multiscale optimization of fluid flow.
Study on the influence and intervention of psychological resilience on academic emotion of urban primary school students: based on cognitive-behavioral group counseling
Authors: Li Shuang , Chen Xiao-mei , Sun Chong-yong
Published: November 2023

This study delves deeply into the interrelationship between urban primary school students' psychological resilience and their academic emotions, shedding light on the transformative impact of cognitive behavioral group counseling on enhancing psychological resilience. With a sample size of 575 students across five schools in Huangshan City, Anhui Province, we distributed meticulously designed questionnaires. Our findings elucidate that a robust psychological resilience not only augments positive academic emotions (t = 0.374, 0.591, P < 0.01) but also diminishes the prevalence of negative ones (t= -0.541, -0.664, P < 0.01).Taking our research a notch higher, we enlisted 36 students and bifurcated them into two distinct groups: experimental and control. While the former underwent a structured regimen of cognitive behavioral group counseling designed to boost psychological resilience, the latter participated in after-school sports activities. Pre-intervention assessments showcased negligible disparities in both psychological resilience and academic emotions between the groups (P > 0.05). However, post-intervention revealed a notable enhancement in the psychological resilience of the experimental group (t = 2.546, P < 0.05). This group also demonstrated a significant upswing in positive academic emotions compared to the control group (t = 2.546, 3.607, P < 0.01) and a marked reduction in negative academic emotions (t=-3.761, -2.038, P < 0.05).The symbiotic relationship between psychological resilience and academic emotions in urban primary school students becomes evident through our study. Moreover, the prowess of cognitive behavioral group counseling as a potent tool for elevating psychological resilience and academic emotions is undeniably showcased. Such profound revelations carry monumental implications for educators and psychologists who are passionate about cultivating a student populace that is not only academically inclined but also emotionally balanced and resilient.
Response surface optimization of solvent tolerant cold active lipase production by Pseudomonas sp. VITCLP4
Authors: Lakshimi V Iswareya , Kavitha M
Published: November 2023

The yield of solvent-tolerant cold active lipase from halo-tolerant Pseudomonas sp. VITCLP4 was improved by applying statistical methods to precisely combine medium components and other conditions. Two-level Plackett–Burman (PB) design was utilized to screen the most significant variables from a set of eleven variables that influence lipase production. Analysis of variance revealed that Tween-80, peptone, and KH2PO4 were statistically significant. Optimum levels of selected variables were ascertained by one-factor-at-a-time (OFAT) analysis. The optimum values and interactive effects of the selected three components were established by response surface methodology (RSM) based on the face-centered central composite design (FCCCD) using a three-level-three-factor approach. The optimized medium containing Tween-80, 0.5% (v/v), peptone, 0.75% (w/v), KH2PO4, 0.05% (w/v), yeast extract, 0.1% (w/v), olive oil, 0.2% (v/v) and inoculum size, 0.2% (v/v) resulted in maximum lipase production of 1342 Units ml− 1 min− 1 with 7.8 fold increase in the yield. This study provides insights into enhancing the lipase production statistically with optimized resources that can be utilized in bioprocess studies and industrial applications.
Responses of Soil and Vegetation Properties to Chemical Fertilization in Restoring Coal Gangue Hills in an Alpine Mining Area
Authors: Jin Liqun , Li Xilai , Sun Huafang , Zhang Jing , Zhang Yufang , Gao Jay
Published: November 2023

During the coal mining operation, the accumulated soil in coal gangue hills often suffers from nutrient deficiencies, which can be overcome using fertilizer supplementation. The supplementation of exogenous nutrients has proven to be an effective means of enhancing physicochemical conditions of these soils and promoting vegetation reestablishment. This study aimed to investigate the characteristics of plant growth and soil properties in vegetation restoration to a coal gangue hill, focusing on artificially seeded grasslands in a high-altitude mining area as the research subject. Over a period of three consecutive years, varying gradients of nitrogen and phosphorus supplements were applied to the coal gangue hill. Furthermore, the interrelationships between plants and soil factors at different dosages of chemical fertilization were analyzed so as to determine the appropriate fertilization level conducive to the ecological system's restoration in the area. The results of this study revealed significant responses (P < 0.05) in vegetation height, coverage, and biomass to nitrogen and phosphorus dosage, leading to a significant increase in the availability of soil nutrients (P < 0.05). Apart from moss coverage, fertilizer dosage exhibited a significant positive correlation (P< 0.05) with various vegetation characteristics, as well as a highly significant positive correlation (P < 0.05) with soil nutrient availability. Notably, no significant differences (P > 0.05) were observed in soil physical properties with varying nitrogen and phosphorus amendments. In conclusion, nitrogen and phosphorus supplementation is beneficial for promoting vegetation growth and improving soil chemical properties in high-altitude mining areas with coal gangue hills. The recommended minimum dosage is 40g/m² of urea in combination with 30g/m² of diammonium phosphate. This supplement should be applied continuously. Considering the capacity of the mining area's ecosystem to self-repair and the costs of ecological restoration, it is advisable to utilize organic fertilizers and sheep manure in the next phase of restoration.
Identifying pre-service teachers’ approaches to science and mathematics communication
Authors: Saribas Deniz , Ceyhan Gaye Defne , Thompson Alia
Published: November 2023

In a world where misinformation and distorted scientific facts are prevalent, the importance of science and mathematics communication cannot be overstated. This study investigates how pre-service teachers approach the communication of science and mathematics topics. Through content analysis, we explored their topic choices, target audiences, communication tools, reasons behind these choices, and core communication skills. The study included pre-service teachers at a public research university who were enrolled in the chemistry education program (n = 11), the physics education program (n = 16), the science education program (n = 37), and the mathematics education program (n = 72). Our findings indicate a diverse range of preferences; pre-service teachers often favored contextualized science topics rooted in real-life issues, while mathematics topics were approached with a tendency toward decontextualization. Furthermore, these future educators predominantly aimed their communications at K-12 students, particularly those in middle school, with the general public also being a prominent choice. Despite diverse tool preferences, storytelling, and narrative techniques, as well as two-way dialogue with the audience, were seldom employed. The results of this study highlight the need to rethink teacher education programs, and integrate interdisciplinary contexts and a multi-way dialogue to communicate science and mathematics topics. Our insights underscore the necessity for comprehensive training in science and mathematics communication within teacher education programs, to further enhance science and mathematics education and literacy in the 21st century.
k-shortest path: average-case analysis and practical improvements
Authors:   , Schickedanz Alexander
Published: November 2023

The single-source shortest-path problem is a fundamental problem in computer science. We consider a generalization of the shortest-path problem, the $k$-shortest path problem. Let $G$ be a directed edge-weighted graph with $n$ nodes and $m$ edges and $s,t$ be two fixed nodes. The goal is to compute $k$ paths $P_1,\dots,P_k$ between two fixed nodes $s$ and $t$ in non-decreasing order of their length such that all other paths between $s$ and $t$ are at least as long as the $k$\nth path $P_k$. We focus on the version of the $k$-shortest path problem where the paths are not allowed to visit nodes multiple times, sometime referred to as $k$-shortest simple path problem. The probably best known $k$-shortest path algorithm is Yen's algorithm. It has a worst-case time complexity of O(kn\cdot scp(n,m)), where scp(n,m) is the complexity of the single-source shortest-path algorithm used as a subroutine. In case of Dijkstra's algorithm scp(n,m) is O(m + n\log n). One of the more recent improvements of Yen's algorithm is by Feng. Even though Feng's algorithm is much faster in practice, it has the same worst-case complexity as Yen's algorithm. The main results presented in this thesis are upper bounds on the average-case of Yen's and Feng's algorithm, as well as practical improvements and a parallel implementation of Yen's and Feng's algorithms including these improvements. The implementation is publicly available under GPLv3 open source license. We show in our analysis that Yen's algorithm has an average-case complexity of O(k \log(n)\cdot scp(n,m)) on G(n,p) graphs with at least logarithmic average-degree and random edge weights following a distribution with certain properties. On G(n,p) graphs with constant to logarithmic average-degree and uniform random edge-weights over $[0;1]$, we show an average-case complexity of O(k\cdot\frac{\log^2 n}{np}\cdot scp(n,m)). Feng's algorithm has an even better average-case complexity of O(k\cdot scp(n,m)) on unweighted G(n,p) graphs with logarithmic average-degree and for constant values of $k$. We further provide evidence that the same holds true for G(n,p) graphs with uniform random edge-weights over $[0;1]$. On the practical side, we suggest new heuristics to prune even more single-source shortest-path computations than Feng's algorithm and evaluate all presented algorithms on G(n,p) and Grid graphs with up to 256 million nodes. We demonstrate speedups by a factor of up to 40 compared to Feng's algorithm. Finally we discuss two ways to parallelize the suggested algorithms and evaluate them on grid graphs showing speedups by a factor of 2 using 4 threads and by a factor of up to 8 using 16 threads, respectively.
On the propeller wake evolution using large eddy simulations and physics-informed space-time decomposition
Authors:   Chongqing Southwest Research Institute for Water Transport Engineering, Chongqing Jiaotong University, Zhang Zhan
Published: November 2023

A novel modal analysis methodology, denoted as the physics informed sparsity-promoting dynamic mode decomposition (pi-SPDMD) model, was introduced for the reduction and reconstruction analysis of intricate propeller wake flows, aiming to provide insight into the inherent flow structures spanning diverse temporal and spatial scales. Large-Eddy Simulation (LES) was employed to numerically model the wake dynamics of a four-bladed propeller, providing a comprehensive resolution from the proximate to the distant wake regions. The findings indicate that the pi-SPDMD model enhances the efficiency of the sparse-promoting algorithm, producing modes that gravitate towards stability, and the resulting decomposition maintains commendable physical fidelity. Integrating the results from the LES solution and the modal decomposition of pi-SPDMD, the tip vortex exhibits a uniform topological configuration with notable coherence in the proximate domain. In this region, the large-scale vortex is the dominant feature of the propeller wake, and there is a marked intermittency in the turbulence. In the mid-field, the tip vortex system transitions into fine-scale vortices, rapidly diminishing in coherence due to the onset of elliptic instability and subsequent secondary vortex generation. As the tip vortex structures related to physical quantities become fully discretized, the small-scale turbulent patterns quickly intermingle, leading to a more homogeneous distribution in the distant wake.
Impact of Biogenic Magnetite Formation and Transformation on Biogeochemical Cycles
Authors: Kappler Andreas , Thompson Aaron , Mansor Muammar
Published: November 2023

Magnetite is a redox-active mineral that can form from both abiotic and biotic processes, and plays an active role in different biogeochemical cycles. Biogenic magnetite particles have properties that differ from their abiogenic counterparts in a variety of ways, including their size, chemical purity, magnetic properties, and association with biomass-derived organic matter. These properties directly influence magnetite reactivity—in particular its sorbent and redox behavior—affecting its association with metals, oxyanions, and other compounds in the environment. Biogenic (and abiogenic) magnetite particles are involved in redox processes by storing electrons, functioning as biogeobatteries, and by transferring electrons between microbial cells or between cells and inorganic constituents. Thus, magnetite influences the fate of contaminants and nutrients in the environment.
Magnetic Guidance in Multicellular Prokaryotes and Eukaryotes
Authors: Leão Pedro , Lefèvre Christopher T.
Published: November 2023

Some organisms have the unique capacity to geolocate and navigate in response to the Earth’s magnetic field lines. Migratory birds and fishes are the best-documented animals that evolved this capacity to guide their movements. In the microbial world, magnetotactic bacteria (MTB) and multicellular magnetotactic prokaryotes (MMPs) have been the only known magnetoreceptive microorganisms for decades. Some microeukaryotes also orient their motility axis along magnetic field lines thanks to the exploitation of MTB magnetism. The magnetic guidance of these prokaryotes and eukaryotes is due to the biomineralization of magnetic crystals. This article provides a brief overview of the current knowledge concerning the different multicellular prokaryotes and micro/macroeukaryotes capable of magnetoreception. We also discuss the evolution of this unique ability.
ALCALOIDES SESQUITERPÊNICOS ISOLADOS DE Maytenus distichophylla (CELASTRACEAE)
Authors: de Figueiredo Pedro Thiago , Duarte Marcelo , Cordeiro Laísa , Menezes Renata , Lima Edeltrudes , Scotti Marcus , Tavares Josean , Costa Vicente , da Silva Marcelo
Published: November 2023

SESQUITERPENES ALKALOIDS FROM Maytenus distichophylla (CELASTRACEAE). The phytochemical study of the roots of Maytenus distichophylla Mart. ex Reissek (Celastraceae), resulted in the isolation of the seven sesquiterpenes pyridine alkaloids euojaponine F (1), euojaponine K (2), ebinifoline W-I (3), wilforine (4), maiteine (5), euojaponine A (6) and ebinifoline E-II (7). The structures of compounds were established using spectroscopic techniques such as 1D and 2D NMR. All compounds were subjected to an in silico study through of a predictive model and then submitted to in vitro testing against S. epidermidis, P. aeruginosa, C. parapsilosis and C. albicans for evaluation of their antimicrobial activity. The compounds tested showed bacterial and fungal growth inhibition with MIC values 1024 and 256 µg mL-1, respectively.
Evaluation of Total Concentrations and Bioaccessible Fractions of Essential and Toxic Elements in Amaranth, Quinoa and Chia by MIP OES
Authors: Clasen Caroline , Silva Sandy , Ribeiro Kaiane , Ribeiro Anderson , Vieira Mariana
Published: November 2023

The total concentrations and the bioaccessible fractions of Al, B, Ba, Ca, Cu, Fe, K, Mg, Mn, Na, Ni, V and Zn were evaluated in 10 samples of pseudocereals, being 3 of amaranth, 3 of quinoa and 4 of chia. The samples were decomposed in a digester block with a reflux system under conditions optimized and the analyses were performed by microwave-induced plasma optical emission spectrometry. In all grains investigated, the highest total concentrations were found for the macroelements K, Mg and Ca, as well as the microelements Fe, Mn, and Zn. When the bioaccessible fraction was evaluated, negative correlations were observed between the content of total phenolic compounds and the bioaccessibility for most elements, in all samples. Among the elements considered essential in our diet, K (99%) and Cu (59%) presented the highest percentages of bioaccessible fraction. Among those elements considered potentially toxic, Ba did not exceed 15% bioaccessible fraction and Al presented concentrations lower than the limit of detection in all samples.
The Cutting-edge of CRISPR for Cancer Treatment and its Future
Prospects
Authors: Liau Kah Man , Ooi An Gie , Mah Chian Huey , Yong Penny , Kee Ling Siik , Loo Cheng Ze , Tay Ming Yu , Foo Jhi Biau , Hamzah Sharina
Published: November 2023

CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) is a versatile
technology that allows precise modification of genes. One of its most promising applications is
in cancer treatment. By targeting and editing specific genes involved in cancer development and
progression, CRISPR has the potential to become a powerful tool in the fight against cancer.
This review aims to assess the recent progress in CRISPR technology for cancer research and to
examine the obstacles and potential strategies to address them. The two most commonly used
CRISPR systems for gene editing are CRISPR/Cas9 and CRISPR/Cas12a. CRISPR/Cas9 employs
different repairing systems, including homologous recombination (HR) and nonhomologous
end joining (NHEJ), to introduce precise modifications to the target genes. However,
off-target effects and low editing efficiency are some of the main challenges associated with
this technology. To overcome these issues, researchers are exploring new delivery methods and
developing CRISPR/Cas systems with improved specificity. Moreover, there are ethical concerns
surrounding using CRISPR in gene editing, including the potential for unintended consequences
and the creation of genetically modified organisms. It is important to address these issues
through rigorous testing and strict regulations. Despite these challenges, the potential benefits
of CRISPR in cancer therapy cannot be overlooked. By introducing precise modifications to
cancer cells, CRISPR could offer a targeted and effective treatment option for patients with different
types of cancer. Further investigation and development of CRISPR technology are necessary
to overcome the existing challenges and harness its full potential in cancer therapy.