Different Substrate Selectivity and Product Patterns of Immobilized Thermophilic Lipases From \u3ci\u3eGeobacillus stearothermophilus\u3c/i\u3e, \u3ci\u3eAnoxybacillus flavithermus\u3c/i\u3e, and \u3ci\u3eThermomyces lanuginosus\u3c/i\u3e for Glyceryl Decanoate Synthesis

Lipases can catalyze synthesis reactions in a micro aqueous system, producing useful partial glycerides (mono- and diglycerides), and these compounds are commonly utilized in different products as surfactants. Depending on the microbial sources for lipases, immobilization conditions, and starting substrates for synthesis reaction, the composition and yields of the resulting partial glycerides could be variable. These differences could lead to the final efficacy of partial glycerides as surfactants in targeted products. Therefore, it is necessary to establish a group of immobilized lipases from different microbial sources with information about substrate specificity to produce effective partial glycerides for various product types. Here, lipases from thermophilic Geobacillus stearothermophilus and Anoxybacillus flavithermus were prepared with a simple partial purification method, and after immobilization, these lipases were tested to synthesize partial glycerides using different types of decanoic acids. The distinct product patterns were analyzed using HPLC. Both immobilized lipases showed the highest substrate selectivity to decanoic acids in common, producing mainly glyceryl monodecanoate. However, commercial immobilized lipases from Thermomyces lanuginosus produced the largest glyceryl monodecanoate from methyl decanoate. These results indicate the importance of immobilization conditions like different microbial sources and substrates and the need for their optimal combination

Increasing Transcultural Competence in Clinical Psychologists Through a Web-Based Training: Study Protocol for a Randomized Controlled Trial

Background In mental health care, the number of patients with diverse cultural backgrounds is growing. Nevertheless, evaluated training programs for transcultural competence are missing. Barriers for engaging in transcultural therapy can be identified in patients as well as in therapists. Besides language barriers, clinical psychologists report insecurities, for example, fear of additional expenses when involving a language mediator, ethical concerns such as power imbalances, or fear of lack of knowledge or incorrect handling when working with patients from other cultures. Divergent values and concepts of disease, prejudices, and stereotyping are also among the issues discussed as barriers to optimal psychotherapy care. The planned study aims to empower clinical psychologists to handle both their own as well as patients’ barriers through a web-based training on transcultural competence. Methods The training includes 6 modules, which are unlocked weekly. A total of N = 174 clinical psychologists are randomly assigned to two groups: the training group (TG) works through the complete training over 6 weeks, which includes a variety of practical exercises and self-refections. In addition, participants receive weekly written feedback from a trained psychologist. The waitlist control group (WL) completes the training after the end of the waiting period (2 months after the end of the TG’s training). The primary outcome is transcultural competence. Secondary outcomes consist of experiences in treating people from other cultures (number of patients, satisfaction and experience of competence in treatment, etc.). Data will be collected before and after the training as well as 2 and 6 months after the end of the training. Discussion This randomized controlled trial tests the efficacy of and satisfaction with a web-based training on transcultural competence for German-speaking clinical psychologists. If validated successfully, the training can represent a time- and place-flexible training opportunity that could be integrated into the continuing education of clinical psychologists in the long term. Trial registration DRKS00031105. Registered on 21 February 2023

Ocean Temperatures Do Not Account for a Record-Setting Winter in the U.S. West

The record-setting winter of 2022–2023 came as an answer to both figurative and literal prayers for political leaders, policy makers, and water managers reliant on snowpacks in the Upper Colorado River Basin, a vital source of water for tens of millions of people across the Western United States. But this “drought-busting” winter was not well-predicted, in part because while interannual patterns of tropical ocean temperatures have a well-known relationship to precipitation patterns across much of the American West, the Upper Colorado is part of a liminal region where these connections tend to be comparatively weak. Using historical sea surface temperature and snowpack records, and leveraging a long-term cross-basin relationship to extend the timeline for evaluation, this analysis demonstrates that the 2022–2023 winter did not present in accordance with other high-snowpack winters in this region, and that the associative pattern of surface temperatures in the tropical Pacific, and snow water equivalent in the regions that stored and supplied most of the water to the Colorado River during the 2022–2023 winter, was not substantially different from a historically incoherent arrangement of long-term correlation. These findings suggest that stochastic variability plays an outsized role in influencing water availability in this region, even in extreme years, reinforcing the importance of other trends to inform water policy and management

Improved Forecasting of LEO Satellite Orbital Decay During the 25\u3csup\u3eth\u3c/sup\u3e Solar Cycle Maximum

Planet is a leading provider of global, daily satellite imagery and geospatial solutions. Planet\u27s mission is to image the world every day and make change visible, accessible, and actionable. To enable this mission, Planet operates the world\u27s largest constellation of Earth Observation satellites (about 180 Doves and 20 Skysats) in the LEO environment of 400-550 km. However, this latitude regime became a challenging environment as we approached the solar maximum of the 25th solar cycle. The solar cycle describes an 11-year rotation period of the Sun\u27s magnetic poles, which is characterized by several activities like solar flares and coronal mass ejections. These activities elicit thermal and magnetic responses in Earth\u27s thermosphere (85-600 km), where several LEO satellites operate. The cycle has a period of maximum activity, called the solar maxima, where LEO satellites in particular experience the highest levels of drag, ultimately leading to shorter mission lifetimes. While solar cycles are periodic, the period around the 25th solar cycle saw higher levels of activity compared to the previous cycle. Specifically, during 2023-2025, we observed LEO satellites decay at a faster rate than what was predicted using the Schatten space weather model. The Schatten space weather model has been a reliable workhorse in forecasting the solar flux in the 10.7 cm wavelength range (f10.7), and Earth\u27s geomagnetic indices. These forecasts are needed to predict the atmospheric densities experienced by the satellites. However, as we approach the solar maximum, the Schatten forecasts deviated significantly from the observations. Such discrepancies, if unaccounted for, can be catastrophic to satellites that operate in low Earth orbits. The risk is even more pronounced for small satellites due to their limited maneuverability. To address some of these risks, we adopted the Solar Cycle 25 model developed by the National Center for Atmospheric Research (NCAR). The NCAR model forecasts the f10.7 flux using the observations of the past sunspot cycles, in contrast to relying on modeling solar magnetic cycles alone. In the current work, we present an application of the NCAR model to predict the altitude decay of satellites operating in the 400-550 km altitude range and compare this against the Schatten model during the solar maximum. In both cases, the NRLMSISE 00 model is used to model the atmospheric density. In addition to this, we compare the predicted decay rates to the real data noted from our fleet of satellites that operate in these altitude ranges. The results indicate that during this period, the NCAR model predicts a faster decay compared to the Schatten model and is closer to the decay rates noted from the orbiting satellites. This suggests that the NCAR model can be used as a potential tool to forecast space weather, especially around the solar maximum. Such models can help us build and operate robust spacecraft missions that are better prepared to handle the challenges of aggressive space weather, ultimately leading to improved security and space situational awareness

On Signifiable Computability: Part I: Signification of Real Numbers, Sequences, and Types

Signifiable computability aims to separate what is theoretically computable from what is computable through performable processes on computers with finite amounts of memory. Real numbers and sequences thereof, data types, and instances are treated as finite texts, and memory limitations are made explicit through a requirement that the texts be stored in the available memory on the devices that manipulate them. In Part I of our investigation, we define the concepts of signification and reference of real numbers. We extend signification to number tuples, data types, and data instances and show that data structures representable as tuples of discretely finite numbers are signifiable. From the signification of real tuples, we proceed to the constructive signification of multidimensional matrices and show that any data structure representable as a multidimensional matrix of discretely finite numbers is signifiable

A Systematic Review of the Prevalence of Late Identified Hearing Loss in Childhood

Objectives The objective of this systematic review was to assess the evidence about the prevalence of permanent hearing loss for children not identified from newborn hearing screening (NHS). Design Articles were grouped into three categories based on the methodological approach: (1) all participants received diagnostic testing, (2) otoacoustic emission (OAE) or pure tone screening was completed and those not passing were referred for a diagnostic test, and (3) data were retrieved from archival records. Study characteristics, prevalence, and contextual factors were synthesised and narratively described. Study Sample 30 peer-reviewed articles. Results Prevalence of permanent hearing loss per 1,000 children ranged from 0.32 to 77.87 (M = 7.30; SD = 16.87). Variations in the criteria for inclusion contributed to prevalence differences. Prevalence was higher when unilateral and milder degrees of hearing loss were included, and older children had higher prevalence (M = 13.71; SD = 23.21) than younger children (M = 1.57; SD = 0.86). Conclusion There is scant research on prevalence of childhood hearing loss after NHS that utilised methods to accurately differentiate between permanent and temporary hearing loss. Rigorous research is needed on the prevalence of permanent childhood hearing loss to inform strategies for monitoring, identification, intervention, and management

Examining the Role of Parental Support on Youth\u27s Interest in and Self-Efficacy of Computer Programming

Objectives. The increasing demand for computing skills has led to a rapid rise in the development of new computer science (CS) curricula, many with the goal of equitably broadening participation of underrepresented students in CS. While such initiatives are vital, factors outside of the school environment also play a role in influencing students\u27 interests. In this paper, we examined the effects of students\u27 perceived parental support on their interest in computer programming and explored the mechanisms through which this effect may have been established as students participated in an introductory CS instructional unit. Participants. This instructional unit was implemented with upper primary (grade 5) school students and was designed to broaden trajectories for participation in CS. The participants in the current study (N=170) came from six classrooms in two rural schools in the western United States. Study Method. The seven-week instructional unit began with students playing a commercial CS tabletop board game that highlighted fundamental programming concepts, and transitioned to having students create their own board game levels in the block-based programming language, Scratch. Further, because the board game could be taken home, the instructional unit offered opportunities to involve the family in school-based CS activities. To investigate the effect of students\u27 perception of parental (specifically father and mother) support on their interest in and self-efficacy to pursue CS, we surveyed students before and after the unit\u27s implementations and explored the structural relationship of the data using structural equation modeling (SEM). Results. We present three findings. First, the combined effect of students\u27 perceived mother\u27s and father\u27s support measured prior to the implementation (pre-survey) predicted students\u27 self-efficacy (Std B = 0.37, SE = 0.010, p \u3c .001) and interest in computer programming (Std B = 0.328, SE = 0.134, p \u3c .003) measured after the implementation (post-survey). Secondly, the combined effect of perceived mother and father support (Std B = 0.132, 95% CI [0.039, 0.399], 99% CI [0.017, 0.542]) on students\u27 interest was mediated by whether or not they took the CS board game home. Conclusions. Our findings indicate that perceived parental support has the potential to play an important role in students\u27 self-efficacy and interest in computer programming and that providing opportunities for students to bring CS artifacts home has the potential to further affect students\u27 interest in computer programming

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

With the rapid development of generative Al, teachers are experiencing a new pedagogical challenge, one that promises to forever change the way we approach teaching and learning. As a response to this unprecedented teaching context, this collection-Teaching and Generative Al: Pedagogical Possibilities and Productive Tensions-provides interdisciplinary teachers, librarians, and instructional designers with practical and thoughtful pedagogical resources for navigating the possibilities and challenges of teaching in an Al era. Because our goal with this edited collection is to present nuanced discussions of Al technologies across disciplines, the chapters collectively acknowledge or explore both possibilities and tensions-including the strengths, limitations, ethical considerations, and disciplinary potential and challenges-of teaching in an Al era. As such, the authors in this collection do not simply praise or criticize Al, but thoughtfully acknowledge and explore its complexities within educational settings

Leveraging Generative AI For Sustainable Farm Management Techniques Correspond To Optimization and Agricultural Efficiency Prediction

Sustainable farm management practice is a multifaceted challenge. Uncovering the optimal state for production while reduction of environmental negative impacts and guaranteed inter-generational assets supervision needs balanced management. Also, considering lots of different factors (cost, profit, employment etc), the agricultural based management technique requires rigorous concentration. In this project machine learning models are applied to develop, achieve and improve the farm management techniques. This experiment ensures the resultant impacts being environment friendly and necessary resource availability and efficiency. Predicting the type of crop and rotational recommendations will disclose potentiality of productive agricultural based farming. Additionally, this project is designed to find the optimized farm operations that will show a stable state combining the agricultural efficiency, better resource management and lowering ecologically unfriendly properties. Additionally, generative AI is used to create data for farming management practices

Exploring Peer-Assisted Learning in a High-School-Based Suicide Prevention Intervention

This dissertation evaluated a form of teaching called peer-assisted learning in which people of similar ages and knowledge teach each other a subject. In this dissertation, peer-assisted teaching occurred in a suicide prevention organization called Hope Squad, which operates as individual chapters in high schools. The author first shared details from other researchers\u27 studies on peer-assisted learning, then conducted two studies on this form of instruction in Hope Squad: The first study reported on the experiences peers have from learning from their peers, and the second study reported on peers\u27 experiences teaching their peers. This dissertation may give researchers further insight into the experiences of peer-assisted learning participants. Reported results from this dissertation\u27s studies could also help to guide Hope Squad and other comparable organizations in the resources and support they might provide to their peer-assisted learning participants