Future Acquisition Research Articles

How is Big Data reshaping preclinical aging research?

The exponential scientific and technological progress during the past 30 years has favored the comprehensive characterization of aging processes with their multivariate nature, leading to the advent of Big Data in preclinical aging research. Spanning from molecular omics to organism-level deep phenotyping, Big Data demands large computational resources for storage and analysis, as well as new analytical tools and conceptual frameworks to gain novel insights leading to discovery. Systems biology has emerged as a paradigm that utilizes Big Data to gain insightful information enabling a better understanding of living organisms, visualized as multilayered networks of interacting molecules, cells, tissues and organs at different spatiotemporal scales. In this framework, where aging, health and disease represent emergent states from an evolving dynamic complex system, context given by, for example, strain, sex and feeding times, becomes paramount for defining the biological trajectory of an organism. Using bioinformatics and artificial intelligence, the systems biology approach is leading to remarkable advances in our understanding of the underlying mechanism of aging biology and assisting in creative experimental study designs in animal models. Future in-depth knowledge acquisition will depend on the ability to fully integrate information from different spatiotemporal scales in organisms, which will probably require the adoption of theories and methods from the field of complex systems. Here we review state-of-the-art approaches in preclinical research, with a focus on rodent models, that are leading to conceptual and/or technical advances in leveraging Big Data to understand basic aging biology and its full translational potential.

1549. Risk Factors, Risk Perception, and Long-acting PrEP Awareness and Interest among US Women: A National Survey

Abstract Background Cisgender women account for approximately 20% of incident HIV diagnoses in the US. However, only 10% of women who could benefit from HIV pre-exposure prophylaxis (PrEP) have been prescribed PrEP. US women face several challenges that may affect their seeking HIV prevention services, such as lack of PrEP awareness. Understanding these challenges may improve PrEP uptake, especially as innovative PrEP options, such as long-acting (LA) injectable PrEP, become available. This study explored interest in using LA-PrEP by factors that may increase risk of HIV acquisition. Methods Cisgender women were recruited between November 2021 – March 2022 though targeted social media ads on Facebook, Instagram, and Tinder to complete an online, self-administered survey. Eligible participants were cisgender women who were: 18+ years, current US residents, reported penetrative sex in the past six months, and reported an unknown or negative HIV status. The survey included questions on demographics, sexual health and behavior, LA-PrEP awareness, and LA-PrEP interest. Descriptive statistics were calculated using SAS v9.4. Results 1,834 eligible women completed the survey (median age: 28 years (IQR: 25, 33); Geography: South – 65%, West – 21%, Northeast – 7.3%, Midwest – 6.8%; Race: Black, non-Hispanic – 34%, White, non-Hispanic – 25%, Hispanic – 27%, Another race – 14%). Women were more likely to have heard of LA-PrEP if they had reported injection drug use in the past year (71%), had an STI diagnosis (70%) or HIV test (66%) in the past two years, and were currently using contraception (65%). Interest in using LA-PrEP was consistently high; the difference between LA-PrEP awareness and interest was greatest among women with non-private health insurance and those with perceived likelihood of future HIV acquisition. Conclusion Although interest in using LA-PrEP is high among US women, these results demonstrate the large gap between LA-PrEP awareness and interest in using it. Disclosures Tonia Poteat, PhD, MPH, PAC, Viiv Healthcare: Advisor/Consultant Supriya Sarkar, PhD, MPH, GlaxoSmithKline: Stocks/Bonds|Viiv Healthcare: Employee Leigh Ragone, MS, GlaxoSmithKline: Stocks/Bonds|ViiV Healthcare: Employee Danielle Bogan, BSN, MPH,DrPH, ViiV Healthcare: Contract worker Keith Rawlings, MD, GlaxoSmithKline: Stocks/Bonds|ViiV Healthcare: Employee Alex R. Rinehart, PhD, ViiV Healthcare: Employee Vani Vannappagari, MBBS, MPH, PhD, GlaxoSmithKline: Stocks/Bonds|ViiV Healthcare: Employee

Relevant input data for crack feature segmentation with deep learning on SEM imagery and topography data

Fractography plays a critical role in failure analysis of engineering components and has a considerable importance for safety investigations. Usually, the interpretation of fracture surfaces is done by experts with the help of literature and experimental data, that requires a lot of experience. The use of deep learning (DL) with neural networks in failure analysis becomes more and more relevant with the rapidly developing possibilities. Especially, the modern network architectures can assist fractographers in determining various fracture features on SEM images of the fracture surfaces. The basis for the best possible evaluation is the understanding of the influence of the input data used for training deep neural networks (DNN). Therefore, this study discusses the influence of the selection of the input data used for the prediction quality of these networks in order to take this into account for future data acquisition. Specimens of various metallic materials were subjected to fatigue cracking experiment under laboratory conditions. The fractured surfaces were then imaged using various modes or detectors (such as SE, BSE and topography) in SEM, and those captured images were used to create a training data set. The relevance of the individual data for the quality of the prediction is determined by a specific combination of the different detector data. For the training, the well-established architecture of a UNet-ResNet34 with a fixed set of hyperparameters is used. It has been found in this present study that the combination of all input data significantly increases the prediction accuracy, whereby even the combination of SE and BSE data provides considerable advantages over the exclusive use of SE images.

An electropenetrography waveform library for the probing and ingestion behaviors of Culex tarsalis on human hands.

Culex tarsalis Coquillett (Diptera: Culicidae) mosquitoes are capable of vectoring numerous pathogens affecting public and animal health. Unfortunately, the probing behaviors of mosquitoes are poorly understood because they occur in opaque tissues. Electropenetrography (EPG) has the potential to elucidate these behaviors by recording the electrical signals generated during probing. We used an AC-DC EPG with variable input resistors (Ri levels) to construct a waveform library for Cx. tarsalis feeding on human hands. Biological events associated with mosquito probing were used to characterize waveforms at four Ri levels and with two electrical current types. The optimal settings for EPG recordings of Cx. tarsalis probing on human hands was an Ri level of 107 Ohms using an applied signal of 150 millivolts alternating current. Waveforms for Cx. tarsalis included those previously observed and associated with probing behaviors in Aedes aegypti L. (Diptera: Culicidae): waveform families J (surface salivation), K (stylet penetration through the skin), L (types 1 and 2, search for a blood vessel/ingestion site), M (types 1 and 2, ingestion), N (type 1, an unknown behavior which may be a resting and digestion phase), and W (withdrawal). However, we also observed variations in the waveforms not described in Ae. aegypti, which we named types L3, M3, M4, and N2. This investigation enhances our understanding of mosquito probing behaviors. It also provides a new tool for the automated calculation of peak frequency. This work will facilitate future pathogen acquisition and transmission studies and help identify new pest and disease management targets.

Analysis of JD.com's Acquisition of Deppon

Nowadays, logistics industry is a valid role in the economic growth. In the dissertation, JD.com’s and Deppon acquisition will be the typical example in the company acquisition. The aim of this dissertation is to analyse whether the acquisition is successful through the comparison of financial data and historical data before and after the acquisition. This will help the acquisition of companies in the future. This dissertation will provide the background of two of the companies. That will make a better understanding of the two companies and the acquisition process. Then, according to the financial data and historical data to analyse the acquisition of JD.com’s and Deppon. Some following suggestions will be given which focus on the future acquisitions, the aim of the dissertation is to help the future similar acquisitions, give them some relative suggestions.

IndiGrid: Transitioning into India's First Independent Power Transmission InvIT (B)1

This case is a sequel to the “IndiGrid: Creating India's First Power Transmission InvIT (A)” case. It describes the deal that would replace the trust's original sponsor, Sterlite Power, with a new set of KKR-led financial investors. It provides an opportunity to discuss the consequences of this change on the new investment manager's outlook for management and future acquisitions. The new investment manager, freed from the limiting interest of the original sponsor, had to search for investment opportunities from the perspective of incoming financial investors, which included the new sponsor. It also provides an opportunity to evaluate the trade-offs in investing in operational utility-scale renewable energy assets by the IndiGrid, which had so far only acquired operational transmission assets in its portfolio.

Design of a 5.94 FO4 absolute-value detector based on hybrid logic technique

With the development of neural signal acquisition systems, spike sorting algorithms have become a hot topic in related fields. The delay of the spike detection system largely determines the speed of the overall signal acquisition system. This paper designs a low-delay Absolute-value Detector based on the GDI technique to improve the timeliness of the neural signal acquisition system. The final circuit has only 20 logic gates-56 transistors. According to the logical effort methodology, the final path delay is 5.94 FO4. This research can provide a reference for the design of future portable ultra-low delay neural signal acquisition systems.

Factors in cognitive processing of Japanese loanwords by advanced Chinese Japanese-as-a-foreign-language learners.

Previous studies have highlighted the challenges faced by Chinese Japanese-as-a-foreign-language (JFL) learners (whose L2 is English) in acquiring L3 Japanese loanwords. These challenges arise from the linguistic characteristics of loanwords and the limited emphasis on teaching and learning them. However, there is a lack of research on the specific factors that influence the processing of Japanese loanwords among Chinese JFL learners. Significant motivation exists, therefore, to investigate these influencing factors as they provide valuable insight into the integration of phonographic and ideographic language systems, ultimately facilitating future lexical acquisition. In this study, an experiment was conducted on 31 Chinese JFL learners to investigate the effects of loanword familiarity, English vocabulary proficiency, English-Japanese phonological similarity, and context on the processing of Japanese loanwords. Data analysis, using a (generalized) linear mixed-effect model, provided the following insights: (1) the processing of Japanese loanwords is influenced by English-Japanese phonological similarity, loanword familiarity, context, and learner English proficiency. Among these four factors, familiarity has the most significant impact on Japanese loanword processing; (2) the effects of context and phonological similarity on the processing of Japanese loanwords are not consistently positive. As learners improve their proficiency in L3 Japanese, they tend to decrease their reliance on English knowledge and instead access loanword representations directly to conceptual representations. Based on the findings of this study, a processing model for Japanese loanwords among advanced Chinese JFL learners is proposed. The model emphasizes the critical importance of the characteristics of loanwords, including phonological similarity and familiarity. It is necessary to determine the specific circumstances in which context considerably enhances learner processing ability.

Comparison of Acquisition of Tense Markers in Oral and Written Language in Bilingual Children

Abstract: Tense acquisition plays a crucial role in the language development of children. Tense refers to the grammatical expression of time in a sentence, which can be in the past, present, or future. Children begin to learn about tenses from a very young age and gradually acquire the ability to use them accurately as they develop their language skills. The present study aims to describe the comparison of the acquisition of tense markers in the oral and written language of 8 to 12-year-old MalayalamEnglish bilingual children. The study involves 20 typically developing children, studying in regular schools with English as the medium of instruction. Two tasks were selected, which included oral and written picture descriptions and narration. The results revealed that, in 8 to 10-year-old children, the acquisition of the simple present tense for both oral and written tasks in Malayalam and English was non significant and the acquisition of the simple past tense for both tasks in Malayalam and English was significant. However, the acquisition of the simple future tense in oral tasks for both languages was significant, while the written performance for future tense acquisition in both languages was non significant. For children aged 11 to 13 years, the acquisition of the simple present tense for oral and written tasks in Malayalam and English was inconclusive and the acquisition of the simple past tense for oral and written tasks in both Malayalam and English was non significant. The acquisition of the future tense for oral tasks was significant whereas for written tasks, it was inconclusive in both languages.

Third language phonological acquisition: Understanding sound structure in a multilingual world

AbstractThe field of third language acquisition has gathered increased attention over the last three decades. However, phonological acquisition in an L3 is still relatively understudied within the field, despite there likely being over a billion people regularly using an L3 worldwide. In this paper, we review experimental and theoretical studies of sequential L3 acquisition to date and aim to give implications for future L3 phonological acquisition research, laying the groundwork for advances in this area. According to the reviewed studies, it is necessary to adapt previous second language phonology models (i.e. SLM/SLM‐r, PAM/PAM‐L2, L2LP) into future L3 phonological research. Additionally, it is essential to expand the research scope and time scale to reflect linguistic diversity, age and education background of participants, and the processes of learning.

Data space inversion for efficient uncertainty quantification using an integrated surface and sub-surface hydrologic model

Abstract. It is incumbent on decision-support hydrological modelling to make predictions of uncertain quantities in a decision-support context. In implementing decision-support modelling, data assimilation and uncertainty quantification are often the most difficult and time-consuming tasks. This is because the imposition of history-matching constraints on model parameters usually requires a large number of model runs. Data space inversion (DSI) provides a highly model-run-efficient method for predictive uncertainty quantification. It does this by evaluating covariances between model outputs used for history matching (e.g. hydraulic heads) and model predictions based on model runs that sample the prior parameter probability distribution. By directly focusing on the relationship between model outputs under historical conditions and predictions of system behaviour under future conditions, DSI avoids the need to estimate or adjust model parameters. This is advantageous when using integrated surface and sub-surface hydrologic models (ISSHMs) because these models are associated with long run times, numerical instability and ideally complex parameterization schemes that are designed to respect geological realism. This paper demonstrates that DSI provides a robust and efficient means of quantifying the uncertainties of complex model predictions. At the same time, DSI provides a basis for complementary linear analysis that allows the worth of available observations to be explored, as well as of observations which are yet to be acquired. This allows for the design of highly efficient, future data acquisition campaigns. DSI is applied in conjunction with an ISSHM representing a synthetic but realistic river–aquifer system. Predictions of interest are fast travel times and surface water infiltration. Linear and non-linear estimates of predictive uncertainty based on DSI are validated against a more traditional uncertainty quantification which requires the adjustment of a large number of parameters. A DSI-generated surrogate model is then used to investigate the effectiveness and efficiency of existing and possible future monitoring networks. The example demonstrates the benefits of using DSI in conjunction with a complex numerical model to quantify predictive uncertainty and support data worth analysis in complex hydrogeological environments.

T1ρ and T2* measurements in small and knee-sized magnetic resonance imaging phantoms: Effect of phantom size and position relative to isocenter

ObjectiveQuantitative magnetic resonance imaging (qMRI) parameters such as T1ρ and T2* characterize changes in cartilage matrix composition prior to cartilage loss. However, T1ρ and T2* measurement reliability in phantoms that mimic in vivo knee size and position within the scanner bore (left or right side of isocenter) is unknown. This study aimed to quantify sources of variance, and the systematic differences between left and right positions in T1ρ and T2* in small vials of a commercially available phantom and a knee-sized phantom. MethodsPhantoms were imaged 100 mm to the left and right of isocenter on five days using 3D MAPSS (T1ρ) and 3D gradient echo (T2*) sequences at 3T. Variance component analysis estimated the variability attributable to slice, side, vial, and day. Measurement error was quantified with 95% confidence intervals (CI). Paired t-tests evaluated systematic differences between the left and right imaging locations (p<.05). ResultsAveraged across days the left-to-right phantom positions produced differences of 0.1 ms (p<.0001) for T1ρ and -0.8 ms (p<.0001) for T2* in the knee-sized phantoms, and differences ranged from -1.5 ± 0.3 ms (p=.0004) to -0.4 ± 0.4 ms (p=.045) for T1ρ and -3.3 ± 2.5 ms (p<.0001) to 2.3 ± 1.5 ms (p<.0001) for T2* in the small vial phantoms. The total variance for T2* was much less for the knee-sized phantom (0.9) than the small-vial pairs with the same concentration (7.0). ConclusionsThis study revealed a position and phantom size dependence on qMRI parameters not reported previously. Future studies and quality control acquisitions should consider position within the MR scanner and phantom size in their design.

Faster and lower dose imaging: evaluating adaptive, constant gantry velocity and angular separation in fast low-dose 4D cone beam CT imaging.

The adoption of four-dimensional cone beam computed tomography (4DCBCT) for image-guided lung cancer radiotherapy is increasing, especially for hypofractionated treatments. However, the drawbacks of 4DCBCT include long scan times (∼240s), inconsistent image quality, higher imaging dose than necessary, and streaking artifacts. With the emergence of linear accelerators that can acquire 4DCBCT scans in a short period of time (9.2s) there is a need to examine the impact that these very fast gantry rotations have on 4DCBCT image quality. This study investigates the impact of gantry velocity and angular separation between x-ray projections on image quality and its implication for fast low-dose 4DCBCT with emerging systems, such as the Varian Halcyon that provide fast gantry rotation and imaging. Large and uneven angular separation between x-ray projections is known to reduce 4DCBCT image quality through increased streaking artifacts. However, it is not known when angular separation starts degrading image quality. The study assesses the impact of constant and adaptive gantry velocity and determines the level when angular gaps impair image quality using state-of-the-art reconstruction methods. This study considers fast low-dose 4DCBCT acquisitions (60-80s, 200-projection scans). To assess the impact of adaptive gantry rotations, the angular position of x-ray projections from adaptive 4DCBCT acquisitions from a 30-patient clinical trial were analyzed (referred to as patient angular gaps). To assess the impact of angular gaps, variable and static angular gaps (20°, 30°, 40°) were introduced into evenly separated 200 projections (ideal angular separation). To simulate fast gantry rotations, which are on emerging linacs, constant gantry velocity acquisitions (9.2s, 60s, 120s, 240s) were simulated by sampling x-ray projections at constant intervals using the patient breathing traces from the ADAPT clinical trial (ACTRN12618001440213). The 4D Extended Cardiac-Torso (XCAT) digital phantom was used to simulate projections to remove patient-specific image quality variables. Image reconstruction was performed using Feldkamp-Davis-Kress (FDK), McKinnon-Bates (MKB), and Motion-Compensated-MKB (MCMKB) algorithms. Image quality was assessed using Structural Similarity-Index-Measure (SSIM), Contrast-to-Noise-Ratio (CNR), Signal-to-Noise-Ratio (SNR), Tissue-Interface-Width-Diaphragm (TIW-D), and Tissue-Interface-Width-Tumor (TIW-T). Patient angular gaps and variable angular gap reconstructions produced similar results to ideal angular separation reconstructions, while static angular gap reconstructions produced lower image quality metrics. For MCMKB-reconstructions, average patient angular gaps produced SSIM-0.98, CNR-13.6, SNR-34.8, TIW-D-1.5mm, and TIW-T-2.0mm, static angular gap 40° produced SSIM-0.92, CNR-6.8, SNR-6.7, TIW-D-5.7mm, and TIW-T-5.9mm and ideal produced SSIM-1.00, CNR-13.6, SNR-34.8, TIW-D-1.5mm, and TIW-T-2.0mm. All constant gantry velocity reconstructions produced lower image quality metrics than ideal angular separation reconstructions regardless of the acquisition time. Motion compensated reconstruction (MCMKB) produced the highest contrast images with low streaking artifacts. Very fast 4DCBCT scans can be acquired provided that the entire scan range is adaptively sampled, and motion-compensated reconstruction is performed. Importantly, the angular separation between x-ray projections within each individual respiratory bin had minimal effect on the image quality of fast low-dose 4DCBCT imaging. The results will assist the development of future 4DCBCT acquisition protocols that can now be achieved in very short time frames with emerging linear accelerators.

The cost of buying land for protected areas in the United States

Buying land to establish protected areas is a common conservation strategy, particularly in countries with strong private property rights. Accurately accounting for spatial heterogeneity in land cost could lead to large efficiency savings when planning future acquisitions. However, lack of data regarding actual acquisition costs faced by conservation organizations has led planners to rely on more readily available proxies, such as agricultural land value. Using data on nearly 36,000 parcels acquired for conservation by public agencies and land trusts in the continental U.S., we built a model predicting protected area acquisition costs. While costs of land for agriculture or development are useful predictors of variation in protected area acquisition costs, they are not, by themselves, good approximations of those costs. For example, using a more comprehensive combination of variables, our model explained almost four times as much variation in actual acquisition costs as those. We found that agricultural land value loses most of its explanatory power once other predictors are used, confirming that it acts as a partial proxy for actual acquisition costs. We then used an optimization model to compare prioritization recommendations with our new cost estimates to those suggested when relying on agricultural land values alone. Locations of highest conservation return on investment shifted from coastal regions toward the country's center, when using actual cost data. Cost estimates used in conservation planning should be based on actual protected area acquisitions, because the type of properties and motivations of buyers and sellers differ from those of other land transactions.

Time series analysis-based models for predicting utilization of electronic resources

This case study examines the use of electronic resources in academic institutions and the difficulties in forecasting their usage. By employing time series analysis-based models, the study forecasts the utilization of e-resources from 2012 to 2021. It concludes that both Autoregressive Integrated Moving Average (ARIMA) and Error, Trend, Seasonal (ETS) models successfully predict electronic resource usage. The study emphasizes the significance of precise predictions for academic institution libraries to manage their collections, allocate resources efficiently, and make informed decisions regarding future acquisitions. The research seeks to forecast the trends of e-resource usage for the next decade based on the decade’s data (2012 to 2021).

Analysis of Dairy M&amp;A: Evidence from Acquisition of Ausnutria by Yili Diary

Nowadays, dairy industry has shown a diversified development trend, all kinds of dairy enterprises not only produce room temperature milk, yogurt, infant formula, goat milk powder track also gradually become the goal of dairy enterprises development. A number of dairy companies have previously implemented acquisitions aimed at developing the goat milk powder, such as Mead Johnson's acquisition of Mercurial. Yili Corporation ("Yili"), as a leading company in China's dairy industry, aims to complete its industrial structure and expand the development of goat milk powder. From 2020 to 2022, Yili, through its wholly-owned subsidiary, Hong Kong Jingang Trade Holding Co ("Jingang"). After the acquisition, Yili became the sole major shareholder. With this acquisition, both parties aim to reap synergies and seek the operational benefits of 1+1&gt;2. The purpose of this paper is to examine the financial impact of this merger on both companies and to make recommendations for future mergers and acquisitions of related dairy companies. According to the analysis, this paper figure out that M&amp;A plays a strategic role for both companies, facilitating the integration and utilization of resources of both companies, bringing a win-win situation for both parties. However, the long-term impact of the M&amp;A will require ongoing attention. These results shed light on guiding further exploration of the M&amp;A of dairy products enterprise.

Spatio-temporal sensitivity analysis of the wetland modules of a semi-distributed hydrological model

Hydrological models offer the opportunity to evaluate wetland conservation networks as nature-based solutions to mitigate hydrological extremes. To optimize the replication of a hydrological model response (i.e., stream flows), the models rely on input data (land cover, hydrographic network, soil types, topography, meteorological data) and parameters. However, the effect of parametric uncertainty on the simulated variables and the spatio-temporal variability of this sensitivity are insufficiently documented. This study presents an application of the novel global sensitivity analysis method, the Variogram Analysis of Response Surface, to the isolated and riparian wetland modules of HYDROTEL, a semi-distributed, process-based, deterministic model, on two watersheds located in the province of Quebec, Canada. The analysis accounted for: (i) the spatial variability by assessing the sensitivity at various locations in the watersheds and by compiling sensitivity indices for wetland networks discretized following the Strahler order classification which quantifies the structure of hydrographic networks and (ii) the temporal variability of the sensitivity using the Generalized Global Sensitivity Matrix. The results indicate that the parameters defining the geometry of wetlands (area, depth) are the most sensitive for both isolated and riparian wetlands, and for all Strahler orders. The temporal assessment of sensitivity highlights the seasonal controlling processes, including a peaking sensitivity of the maximum water depth in wetlands during spring snowmelt, whereas the sensitivity of the evapotranspiration parameter increases during summer, but is null during winter. Results also indicate that the parameters of the isolated modules are more sensitive for wetlands located on lower stream order (upstream/headwaters) while those of the riparian modules display a greater sensitivity when wetlands are located on higher Strahler orders (downstream/main channel). These findings deepen our understanding of the impact of wetland features on stream flows and provide guidelines to plan future data acquisition campaigns in wetlandscapes.

Joint Retrieval of Sea Surface Rainfall Intensity, Wind Speed, and Wave Height Based on Spaceborne GNSS-R: A Case Study of the Oceans near China

In this paper, a method for joint sea surface rainfall intensity (RI), wind speed, and wave height retrieval based on spaceborne global navigation satellite system reflectometry (GNSS-R) data is proposed, which especially considers the effects between these two parameters. A method of rainfall detection (RD) according to different wind speed ranges is also proposed by mitigating the impact of swell and wind speed. The results, with data collected over the oceans near Southeast Asia, show that the RD method has a detection accuracy of up to 81.74%. The RI retrieval accuracy can reach about 2 mm/h by simultaneously correcting the effects of wind speed and swell. The accuracy of wind speed retrieval is improved by about 5% after removing rainfall interference through RD in advance. After considering the influence of wind speed and eliminating rainfall interference, the retrieval accuracy of significant wave height (SWH) is improved by about 18%. Finally, the deep convolutional neural network (DCNN) model is built to estimate the SWH of the swell. The results show that the retrieval accuracy of the swell height is better than 0.20 m after excluding rainfall interference. The proposed joint retrieval method provides an important reference for the future acquisition of multiple high-precision marine geophysical parameters by spaceborne GNSS-R technology.

Usefulness of the lupus low disease activity state as a treatment target in childhood-onset SLE

ObjectiveTreat-to-target (T2T) strategies are advocated to improve prognosis in childhood-onset SLE (cSLE). Proposed T2T states include SLEDAI score of <4 (SLEDAI-LD), limited corticosteroid use (low-CS), and lupus low disease activity...

Future Proofing Streaming Video Acquisitions: A Medium Sized Academic Library Adapts

ABSTRACT The pedagogical appeal of using film in higher education, while not new, has undeniably grown since the COVID-19 pandemic necessitated remote teaching for health and safety reasons. This dramatic rise in streaming video requests is challenging for academic libraries of all sizes. Yet, smaller- and medium-sized institutions have personnel who already juggle multiple roles and responsibilities, resulting in chaos and the need for new workflows. This article will reflect on the past 24 months of managing streaming video at the University of San Diego’s Copley Library, comparing the remote instruction period to the hybrid teaching that followed.