bluuebunny/crossref_metadata_2025 huggingface dataset:
Supporting Cognition With Modern Technology: Distributed Cognition Today and in an AI-Enhanced Future
Authors: Grinschgl Sandra , Neubauer Aljoscha C.
Published: July 2022

In the present article, we explore prospects for using artificial intelligence (AI) to distribute cognition via cognitive offloading (i.e., to delegate thinking tasks to AI-technologies). Modern technologies for cognitive support are rapidly developing and increasingly popular. Today, many individuals heavily rely on their smartphones or other technical gadgets to support their daily life but also their learning and work. For instance, smartphones are used to track and analyze changes in the environment, and to store and continually update relevant information. Thus, individuals can offload (i.e., externalize) information to their smartphones and refresh their knowledge by accessing it. This implies that using modern technologies such as AI empowers users via offloading and enables them to function as always-updated knowledge professionals, so that they can deploy their insights strategically instead of relying on outdated and memorized facts. This AI-supported offloading of cognitive processes also saves individuals' internal cognitive resources by distributing the task demands into their environment. In this article, we provide (1) an overview of empirical findings on cognitive offloading and (2) an outlook on how individuals' offloading behavior might change in an AI-enhanced future. More specifically, we first discuss determinants of offloading such as the design of technical tools and links to metacognition. Furthermore, we discuss benefits and risks of cognitive offloading. While offloading improves immediate task performance, it might also be a threat for users' cognitive abilities. Following this, we provide a perspective on whether individuals will make heavier use of AI-technologies for offloading in the future and how this might affect their cognition. On one hand, individuals might heavily rely on easily accessible AI-technologies which in return might diminish their internal cognition/learning. On the other hand, individuals might aim at enhancing their cognition so that they can keep up with AI-technologies and will not be replaced by them. Finally, we present own data and findings from the literature on the assumption that individuals' personality is a predictor of trust in AI. Trust in modern AI-technologies might be a strong determinant for wider appropriation and dependence on these technologies to distribute cognition and should thus be considered in an AI-enhanced future.
One Size Does Not Fit All: Variability in Urinary Symptoms and Microbial Communities
Authors: Hochstedler-Kramer Baylie , Joyce Cara , Abdul-Rahim Omar , Barnes Hayley C. , Mueller Elizabeth R. , Wolfe Alan J. , Brubaker Linda , Burnett Lindsey A.
Published: July 2022

The discovery of the urinary microbiome prompted researchers to begin characterizing microbiota associated with various health and disease states; however, the etiology of bladder infections, the most common urinary tract infection (UTI), is still simplistically attributed to the invasion of a uropathogen, mainly Escherichia coli, without regard for the resident microbial community. In addition, the clinical variability of UTI symptoms remains poorly understood. Very little research has been done to investigate the role of baseline microbial communities in development and resolution of UTI symptoms. The goal of this study was to identify associations between urinary microbiota and lower urinary tract symptoms profiles in adult women with UTI symptoms. This is a secondary analysis of a previously published IRB-approved study that included 225 women who reported having acute UTI symptoms, submitted catheterized urine specimens for analysis by an enhanced urine culture method and were assessed for symptom resolution 7-10 days after receiving culture-directed antibiotic treatment. In this UTI population, we identified six distinct symptom profiles, termed symptotypes, that were characterized by varying severity and degree of bother of certain lower urinary tract symptoms. These symptotypes were not associated with urotype or the presence of specific microbes. In participants with pain on presentation, the presence of non-E. coli and non-uropathogens was associated with persistence of symptoms at follow up; however, this was not true for those with E. coli urotype. These data suggest that the presence of E. coli may not account for the underlying cause of typical UTI symptoms; instead, co-existence of a uropathogen in the context of the existing urinary microbiota and the host may be responsible for these symptom profiles.
Problemscapes and Hybrid Water Security Systems in Central Ethiopia
Authors: Polaine Xanthe K. , Nicol Alan , Amezaga Jaime , Berihun Meklit , Dessalegn Mengistu , Haile Alemseged Tamiru
Published: July 2022

Water management has followed a basin unit paradigm for several decades. This framing often inherits a pre-defined spatial and institutional boundary of analysis, one that largely fails to account for various externalities influencing water security beyond the hydrological unit. Moving away from this established basin-scale analysis, we present the concept of problemscapes, a systems approach for understanding how multiple physical and social drivers surrounding (and as part of) contextual water systems determine how they work and, ultimately, the outcomes in terms of the water security they provide. By first discussing the concept of boundaries for water paradigms, we argue that problemscapes can help us understand water security as a more dynamic and hybrid system by adapting these boundaries; enabling a clearer understanding of leverage points, interconnections and possible strategic solutions to longer-term water security challenges. We apply the method for establishing and utilizing a problemscape analysis across the Central Rift Valley, Upper Awash, and Abbay basins, as well as the capital city of Addis Ababa. The interactions in this part of Central Ethiopia are notoriously complex, with sets of critical water management issues at national and international scale, hybrid water security challenges across user communities, and contested management at different scales amidst multiple, and sometimes competing, ideologies. We show that problemscaping as an approach could support future planning decisions for long-term water security by enabling a systems perspective to emerge where complexity and connectivity between actors, institutions, and physical and social entities is considered.
Effects of Resistance Training Prior to Total Hip or Knee Replacement on Post-operative Recovery in Functional Performance: A Systematic Review and Meta-Analysis
Authors: Jørgensen Stian Langgård , Kierkegaard Signe , Bohn Marie Bagger , Aagaard Per , Mechlenburg Inger
Published: July 2022

Objective

To evaluate the effectiveness of pre-operative resistance training in patients allocated to TJR surgery on selected post-operative outcomes, via a meta-analysis of studies using exercise modalities and loading intensities objectively known to promote gains in muscle size and strength in adults of young-to-old age.

Design

A systematic review and meta-analysis.

Literature Search

Cochrane Central, MEDLINE, EMBASE, and PEDro were searched on August 4th 2021.

Study Selection

Randomized Controlled Trials (RCTs) were included if (i) they compared pre-operative lower-limb-exercises before elective TJR with standard care, (ii) explicitly reported the exercise intensity, and (iii) reported data on functional performance.

Data Synthesis

This systematic review and meta-analysis is reported in accordance with the PRISMA reporting guidelines. A random effects model with an adjustment to the confidence interval was performed for pooling the data.

Results

One thousand studies were identified. After applying exclusion criteria, five RCTs were located including 256 participants (mean age ranged from 61 to 72 years, 54% women). Moderate-to-large improvements in functional performance and maximal knee extensor strength were observed at 3 months after surgery along with small-to-moderate effects 12 months post-operatively. For patient-reported outcomes, small-to-moderate improvements were observed at 3 months post-operatively with no-to-small improvements at 12 months.

Conclusion

Prehabilitation efforts involving progressive resistance training provides an effective means to improve post-operative outcomes related to functional performance, knee extensor strength and patient-reported outcome in patients undergoing TJR. Due to large methodological diversity between studies, an optimal loading intensity remains unknown.

Systematic Review Registration

Prospero ID: CRD42021264796.
Natural language processing in low back pain and spine diseases: A systematic review
Authors: Bacco Luca , Russo Fabrizio , Ambrosio Luca , D’Antoni Federico , Vollero Luca , Vadalà Gianluca , Dell’Orletta Felice , Merone Mario , Papalia Rocco , Denaro Vincenzo
Published: July 2022

Natural Language Processing (NLP) is a discipline at the intersection between Computer Science (CS), Artificial Intelligence (AI), and Linguistics that leverages unstructured human-interpretable (natural) language text. In recent years, it gained momentum also in health-related applications and research. Although preliminary, studies concerning Low Back Pain (LBP) and other related spine disorders with relevant applications of NLP methodologies have been reported in the literature over the last few years. It motivated us to systematically review the literature comprised of two major public databases, PubMed and Scopus. To do so, we first formulated our research question following the PICO guidelines. Then, we followed a PRISMA-like protocol by performing a search query including terminologies of both technical (e.g., natural language and computational linguistics) and clinical (e.g., lumbar and spine surgery) domains. We collected 221 non-duplicated studies, 16 of which were eligible for our analysis. In this work, we present these studies divided into sub-categories, from both tasks and exploited models’ points of view. Furthermore, we report a detailed description of techniques used to extract and process textual features and the several evaluation metrics used to assess the performance of the NLP models. However, what is clear from our analysis is that additional studies on larger datasets are needed to better define the role of NLP in the care of patients with spinal disorders.
A Mathematical Model for On-Target Off-Tumor Effect of CAR-T Cells on Gliomas
Authors: Santurio Daniela Silva , Barros Luciana Rodrigues Carvalho
Published: July 2022

CAR-T cell immunotherapy involves genetically reprogrammed T-lymphocytes that interact with cancer cells and activate an anti-tumor immune response. This therapy has been approved for clinical use for hematological cancers, but new challenges have emerged in the treatment of solid tumors. Some of the challenges include the heterogeneity of antigen expression found in solid tumors, including antigen-positive non-tumoral cells, the immune inhibitory molecule expression, and CAR-T cell trafficking difficulty within the tumor microenvironment. We proposed a mathematical model to describe the “on-target” and “off-tumor” effects of CAR-T cell therapy on gliomas, and we investigated which parameters influenced the final outcome using a global sensitivity analysis. Our model highlights the dynamics of CAR-T cell therapy, tumor, and healthy populations (antigen-positive glia, antigen-negative glia, and neurons), and it provides novel insight into the consequences of “on-target” “off-tumor” effects, particularly in the neuronal loss.
APOBEC3 selects V179I in HIV-1 reverse transcriptase to provide selective advantage for non-nucleoside reverse transcriptase inhibitor-resistant mutants
Authors: Dwivedi Richa , Wang Youya , Kline Christopher , Fischer Douglas K. , Ambrose Zandrea
Published: July 2022

The V179I substitution in human immunodeficiency virus type 1 (HIV-1) reverse transcriptase (RT) is selected in humans or mouse models treated with certain nonnucleoside reverse transcriptase inhibitors (NNRTIs). While it is often observed together with other NNRTI resistance mutations, V179I does not confer drug resistance. To understand how V179I arises during NNRTI treatment, we characterized it in HIV-1 molecular clones with or without the NNRTI resistance mutations Y181C or Y181V. While V179I alone did not confer resistance to any NNRTIs tested, when present with Y181C/V it enhanced drug resistance to some NNRTIs by 3- to 8-fold. In replication competition experiments in the presence of the NNRTI rilpivirine (RPV), V179I modestly enhanced Y181C HIV-1 or Y181V HIV-1 replication compared to viruses without V179I. As V179I arises from a G to A mutation, we evaluated whether it could arise due to host APOBEC3 deaminase activity and be maintained in the presence of a NNRTI to provide a selective advantage for the virus. V179I was detected in some humanized mice treated with RPV and was associated with G to A mutations characteristic of APOBEC3 activity. In RPV selection experiments, the frequency of V179I in HIV-1 was accelerated in CD4+ T cells expressing higher APOBEC3F and APOBEC3G levels. Our results provide evidence that V179I in HIV-1 RT can arise due to APOBEC-mediated G to A hypermutation and can confer a selective advantage to drug-resistant HIV-1 isolates in the presence of some NNRTIs.
A Federated Generalized Linear Model for Privacy-Preserving Analysis
Authors: Cellamare Matteo , van Gestel Anna J. , Alradhi Hasan , Martin Frank , Moncada-Torres Arturo
Published: July 2022

In the last few years, federated learning (FL) has emerged as a novel alternative for analyzing data spread across different parties without needing to centralize them. In order to increase the adoption of FL, there is a need to develop more algorithms that can be deployed under this novel privacy-preserving paradigm. In this paper, we present our federated generalized linear model (GLM) for horizontally partitioned data. It allows generating models of different families (linear, Poisson, logistic) without disclosing privacy-sensitive individual records. We describe its algorithm (which can be implemented in the user’s platform of choice) and compare the obtained federated models against their centralized counterpart, which were mathematically equivalent. We also validated their execution time with increasing numbers of records and involved parties. We show that our federated GLM is accurate enough to be used for the privacy-preserving analysis of horizontally partitioned data in real-life scenarios. Further development of this type of algorithm has the potential to make FL a much more common practice among researchers.
Inference Acceleration with Adaptive Distributed DNN Partition over Dynamic Video Stream
Authors: Cao Jin , Li Bo , Fan Mengni , Liu Huiyu
Published: July 2022

Deep neural network-based computer vision applications have exploded and are widely used in intelligent services for IoT devices. Due to the computationally intensive nature of DNNs, the deployment and execution of intelligent applications in smart scenarios face the challenge of limited device resources. Existing job scheduling strategies are single-focused and have limited support for large-scale end-device scenarios. In this paper, we present ADDP, an adaptive distributed DNN partition method that supports video analysis on large-scale smart cameras. ADDP applies to the commonly used DNN models for computer vision and contains a feature-map layer partition module (FLP) supporting edge-to-end collaborative model partition and a feature-map size partition (FSP) module supporting multidevice parallel inference. Based on the inference delay minimization objective, FLP and FSP achieve a tradeoff between the arithmetic and communication resources of different devices. We validate ADDP on heterogeneous devices and show that both the FLP module and the FSP module outperform existing approaches and reduce single-frame response latency by 10–25% compared to the pure on-device processing.
Concurrent Trajectory Optimization and Aircraft Design for the Air Cargo Challenge Competition
Authors: Matos Nuno M. B. , Marta Andre C.
Published: July 2022

A coupled aerostructural aircraft design and trajectory optimization framework is developed for the Air Cargo Challenge competition to maximize the expected score based on cargo carried, altitude achieved and distance traveled. Its modular architecture makes it easily adaptable to any problem where the performance depends not only on the design of the aircraft but also on its flight trajectory. It is based on OpenAeroStruct, an aerostructural solver that uses analytic derivatives for efficient gradient-based optimization. A trajectory optimization module using a collocation method is coupled with the option of using b-splines to increase computational efficiency together with an experimentally-based power decay model that accurately determines the aircraft propulsive response to control input depending on the battery discharge level. The optimization problem totaled 206 variables and 283 constraints and was solved in less than 7 h on a standard computer with 12% reduction when using b-splines for trajectory control variables. The results revealed the need to consider the multi-objective total score to account for the different score components and highlighted the importance of the payload level and chosen trajectory. The wing area should be increased within allowable limits to maximize payload capacity, climb to maximum target height should be the focus of the first 60 s of flight and full throttle should be avoided in cruise to reduce losses and extend flight distance. The framework proved to be a valuable tool for students to easily obtain guidelines for both the model aircraft design and control to maximize the competition score.
Spectroscopic Investigation on the Effects of Biochar and Soluble Phosphorus on Grass Clipping Vermicomposting
Authors: Novotny Etelvino , Balieiro Fabiano , Auccaise Ruben , Benites Vinícius , Coutinho Heitor
Published: July 2022

Seeking to evaluate the hypothesis that biochar optimises the composting and vermicomposting processes as well as their product quality, we carried out field and greenhouse experiments. Four grass clipping composting treatments (only grass, grass + single superphosphate (SSP), grass + biochar and grass + SSP + biochar) were evaluated. At the end of the maturation period (150 days), the composts were submitted to vermicomposting (Eisenia fetida earthworm) for an additional 90 days. Ordinary fine charcoal was selected due to its low cost (a by-product of charcoal production) and great availability; this is important since the obtained product presents low commercial value. A greater maturity of the organic matter (humification) was observed in the vermicompost treatments compared with the compost-only treatments. The addition of phosphate significantly reduced the pH (from 6.7 to 4.8), doubled the electrical conductivity and inhibited biological activity, resulting in less than 2% of the number of earthworms found in the treatment without phosphate. The addition of soluble phosphate inhibited the humification process, resulting in a less-stable compound with the preservation of labile structures, primarily cellulose. The P species found corroborate these findings because the pyrophosphate conversion from SSP in the absence of biochar may explain the strong acidification and increased electric conductivity. Biochar appears to prevent this conversion, thus mitigating the deleterious effects of SSP and favouring the formation of organic P species from SSP (78.5% of P in organic form with biochar compared to only 12.8% in the treatments without biochar). In short, biochar decreases pyrophosphate formation from SSP, avoiding acidification and salinity; therefore, biochar improves the whole composting and vermicomposting process and product quality. Vermicompost with SSP and biochar should be tested as a soil conditioner on account of its greater proportion of stabilized C and organic P.
Key Region Extraction and Body Dimension Measurement of Beef Cattle Using 3D Point Clouds
Authors: Li Jiawei , Li Qifeng , Ma Weihong , Xue Xianglong , Zhao Chunjiang , Tulpan Dan , Yang Simon X.
Published: July 2022

Body dimensions are key indicators for the beef cattle fattening and breeding process. On-animal measurement is relatively inefficient, and can induce severe stress responses among beef cattle and pose a risk for operators, thereby impacting the cattle’s growth rate and wellbeing. To address the above issues, a highly efficient and automatic method was developed to measure beef cattle’s body dimensions, including the oblique length, height, width, abdominal girth, and chest girth, based on the reconstructed three-dimensional point cloud data. The horizontal continuous slice sequence of the complete point clouds was first extracted, and the central point of the beef cattle leg region was determined from the span distribution of the point cloud clusters in the targeted slices. Subsequently, the boundary of the beef cattle leg region was identified by the “five-point clustering gradient boundary recognition algorithm” and was then calibrated, followed by the accurate segmentation of the corresponding region. The key regions for body dimension data calculation were further determined by the proposed algorithm, which forms the basis of the scientific calculation of key body dimensions. The influence of different postures of beef cattle on the measurement results was also preliminarily discussed. The results showed that the errors of calculated body dimensions, i.e., the oblique length, height, width, abdominal girth, and chest girth, were 2.3%, 2.8%, 1.6%, 2.8%, and 2.6%, respectively. In the present work, the beef cattle body dimensions could be effectively measured based on the 3D regional features of the point cloud data. The proposed algorithm shows a degree of generalization and robustness that is not affected by different postures of beef cattle. This automatic method can be effectively used to collect reliable phenotype data during the fattening of beef cattle and can be directly integrated into the breeding process.
Composition and Diversity of LTR Retrotransposons in the Coffee Leaf Rust Genome (Hemileia vastatrix)
Authors: Orozco-Arias Simon , Candamil Mariana S. , Jaimes Paula A. , Cristancho Marco , Tabares-Soto Reinel , Guyot Romain
Published: July 2022

Coffee leaf rust is the most damaging disease for coffee cultivation around the world. It is caused by a fungal pathogen, Hemileia vastatrix (Hva), belonging to the phylum Basidiomycota. Coffee leaf rust causes significant yield losses and increases costs related to its control, with evaluated losses of USD 1–2 billion annually. It attacks both the cultivated coffee species Coffea canephora (Robusta coffee) and Coffea arabica (Arabica coffee). New races, or pathotypes, are constantly emerging with increased virulence, suggesting a rapid evolution of the pathogen. Previous genetic and genomic studies have indicated a limited nucleotide diversity of Hva despite a high genetic diversity and large genome size estimated to be ~800 Mb, with a high content of repeated sequences (>74%). Despite several genomic resources and the release of a recent partial genome sequence, the diversity of these repeated sequences and how they may impact the evolution of the leaf rust genome have not been investigated in detail. In an attempt to characterize the transposable elements within the Hva genomes, we report here new lineages of long terminal repeat (LTR) retrotransposons, called CO-HUI, Soroa, and Baco, which are classified into Gypsy, and and Labe and Mapi, which are classified as Copia. The CO-HUI and Soroa elements represent the main part of all Hva transposable elements, as well as approximately 37% of the available genome assemblies. Mapi and CO-HUI are the main expressed families in RNA-seq data. Although Soroa is the lineage showing more insertions into exons and genes, Mapi seems to be more frequently involved in co-expression with genes. All these new families are also present in the Pucciniales, suggesting that they dynamically participate in their genome evolution.
Water Demand Pattern and Irrigation Decision-Making Support Model for Drip-Irrigated Tomato Crop in a Solar Greenhouse
Authors: An Shunwei , Yang Fuxin , Yang Yingru , Huang Yuan , Zhangzhong Lili , Wei Xiaoming , Yu Jingxin
Published: July 2022

The knowledge of crop water requirements is critical for agricultural water conservation, especially for accurate irrigation decision making in the greenhouse. Investigating the water demand pattern of the tomato in the solar greenhouse environment and constructing an appropriate irrigation decision-making model are urgently needed to improve irrigation water use efficiency. We designed four irrigation-level treatments: 100% ET0 (T1), 85% ET0 (T2), 70% ET0 (T3), and 55% ET0 (T4), and conducted a two-vegetation-season tomato planting trial under drip irrigation conditions in a solar greenhouse. The Pearson’s correlation coefficient method analyzed the intrinsic linkage and influence between soil–crop–environment and tomatoes’ water demand patterns. Indicators suitable for irrigation decision making in greenhouse tomatoes were selected, and regression functions were constructed for environmental and crop physiological parameters by combining path analysis and multiple regression methods. Finally, a fusion irrigation decision-making model was constructed by introducing a distance function in the Dempster–Shafer (D–S) theory primary probability assignment (BPA) synthesis algorithm and combining it with a triangular affiliation function. The results showed that: (1) the soil coefficient of variation was shallow > middle > deep, and tomatoes absorbed water mainly in the 0–60 cm soil layer; (2) the crop stem flow rate, net photosynthetic rate, and transpiration rate were positively correlated with irrigation water and had the highest correlation with net radiation, relative humidity, and relative humidity, with correlation coefficients of 0.9441, 0.9441, and 0.7679, respectively; (3) the constructed decision model had a significantly lower value of uncertainty than other methods, while the highest decision value could reach over 0.99, which achieved the best decision accuracy compared to other algorithms.
Evaluation of Alfalfa and Grass Species in Binary and Complex Mixtures on Performance under Soil Salinity Conditions
Authors: Darambazar Enkhjargal , Larson Kathy , Schoenau Jeff , Wang Gravel , Biligetu Bill , Damiran Daalkhaijav , Lardner Herbert A.
Published: July 2022

The effect of synergies between saline-tolerant grass and legume species grown in saline soil, on yield, quality, composition, persistence, and weed suppression was studied in 2019–2021 in a moderately saline soil located in the dark brown soil zone near Saskatoon, Saskatchewan, Canada. ‘Halo’ alfalfa (ALF), a salt-tolerant cultivar of alfalfa, was seeded in binary mixtures with ‘Revenue’ slender wheatgrass (ALF-SWG), ‘Garrison’ creeping meadow foxtail (ALF-CMF), and ‘Radisson’ smooth bromegrass (ALF-SBG). A complex mixture (quaternary) with all three grasses was also included. Four replicated treatments (n = 4) were randomly allocated to 6.2 × 1.2 m plots in spring 2019. The binary mixtures had similar or slightly better stand establishment compared to the quaternary mixture over the two years (83.3 vs. 76.9%), the quaternary stand showed greater (p = 0.01) establishment in Yr 2 than in Yr 1 (85 vs. 68.8%). There was high weed infestation in all the stands, but ALF-SWG had less weed infestation (23.8 vs. 44.1%) than ALF-CMF, especially in Yr 2 (p = 0.05). There were no significant differences among mixtures in yield, nutritional composition, and nutrient uptake. The ALF-CMF and ALF-SWG binary mixtures had 9 to 23% greater mean total DMY than the other mixtures in the moderately saline soil. The cost of establishing forage mixtures on unproductive saline land can be up to 89% recovered after only two years. The results suggested that binary mixtures of ‘Halo’ alfalfa with ‘Revenue’ slender wheatgrass or ‘Garrison’ creeping meadow foxtail could be reasonable alternatives for adequate forage production and quality, high N-use efficiency, and ultimately livestock gain per hectare, as well as for controlling soil salinity and improving soil fertility in this saline area in the dark brown soil zone.
Cetaceans Humerus Radiodensity by CT: A Useful Technique Differentiating between Species, Ecophysiology, and Age
Authors: Consoli Francesco Maria Achille , Bernaldo de Quirós Yara , Arbelo Manuel , Fulle Stefania , Marchisio Marco , Encinoso Mario , Fernandez Antonio , Rivero Miguel A.
Published: July 2022

Cetaceans are mammals that underwent a series of evolutionary adaptations to live in the aquatic environment, including morphological modifications of various anatomical structures of the skeleton and their bone mineral density (BMD); there are few studies on the latter. BMD is related to the radiodensity measured through computed tomography (CT) in Hounsfield units (HU). This work aimed to test and validate the usefulness of studying humeral bone radiodensity by CT of two cetacean species (the Atlantic spotted dolphin and the pygmy sperm whale) with different swimming and diving habits. The radiodensity was analysed at certain levels following a new protocol based on a review of previous studies. Humeral radiodensity values were related to four aspects: species, diving behaviour, swimming activity level, and age. We observed that the consistent differences in the radiodensity of the cortical bone of the distal epiphysis between animals of different life-history categories suggest that this bone portion could be particularly useful for future ontogenetic studies. Hence, this technique may be helpful in studying and comparing species with different ecophysiologies, particularly distinguishing between swimming and diving habits.
Defining the Effect of Oxytocin Use in Farrowing Sows on Stillbirth Rate: A Systematic Review with a Meta-Analysis
Authors: Hill Sarah V. , del Rocio Amezcua Maria , Ribeiro Eduardo S. , O’Sullivan Terri L. , Friendship Robert M.
Published: July 2022

The objective of this systematic review and meta-analysis was to identify the benefits and possible adverse side effects of oxytocin use during farrowing. Randomized controlled trials that were published in English within the last 50 years were eligible for inclusion. Eligible research needed to contain the PICO elements: population (P)—sows at farrowing; intervention (I):—oxytocin given to sows—comparator (C): sows at farrowing not given oxytocin, as well as sows given different dosages and/or different timing of administration; and outcomes (O):—stillbirths, sow mortality, and piglet viability. Four bibliographic databases were used: PubMed, CAB Direct, Web of Science Core Collection, and ProQuest Dissertations, and Theses Global. In addition, we performed a manual search of the table of contents in the American Association of Swine Veterinarians database for relevant conference proceedings and reports. To assess the risk of bias at the study level, a modified version of the Cochrane 2.0 ROB was used. Meta-analyses were performed to examine the average stillbirth rate, farrowing duration, and birth interval between piglets using random-effect standardized mean difference (SMD) models. To explore heterogeneity, a sub-group analysis was performed on the objectives of the study, dose, time, and route of administration. Of the 46 studies eligible for meta-analyses, only 25 had sufficient information. The pooled analyses of the random effect model demonstrated that the average number of stillborn pigs was lower in the comparator group (SMD = 0.23; CI95% = 0.1, 0.36), and both the farrowing duration (SMD = −8.4; CI95% = −1.1, −0.60) and the birth interval between piglets (SMD = −1.41; CI95% = −1.86, −0.97) were shorter in the oxytocin group. The majority of the studies had an overall risk of bias of ‘some concerns’. It was concluded that the use of oxytocin increases the overall number of stillborn piglets, but decreases the farrowing duration and time interval between piglets. However, future studies should focus on the effect of oxytocin on the experience of dystocia among sows.
Inter-Observer Repeatability of Indicators of Consciousness after Waterbath Stunning in Broiler Chickens
Authors: Contreras-Jodar Alexandra , Varvaró-Porter Aranzazu , Michel Virginie , Velarde Antonio
Published: July 2022

This study evaluated the prevalence and tested the inter-observer repeatability of the most valid and feasible animal-based indicators of the state of consciousness after waterbath stunning in broilers before bleeding (tonic seizure, breathing, spontaneous blinking and vocalization) and during bleeding (wing flapping, breathing, spontaneous swallowing and head shaking). In addition, correlations among them were computed to better understand their relationship and offer insights into the reliability of such indicators. This was aimed at proposing a refined list of indicators that could be used in commercial slaughterhouses to ensure consistent assessments. This study compared the assessments of three observers of 5241 broilers from 19 batches in six different slaughterhouses. Inter-observer repeatability was assessed through the combination of the crude percentage of agreement and the Fleiss’ kappa coefficient and interpretation. Before bleeding, the results led us to recommend assessing breathing over spontaneous blinking and vocalizations and to neglect tonic seizure in commercial conditions. During bleeding, the recommended indicators are breathing, wing flapping and head shaking while spontaneous swallowing can be neglected.
Characterization of Pathway-Specific Regulator NigR for High Yield Production of Nigericin in Streptomyces malaysiensis F913
Authors: Wei Junhong , Ma Mengting , Guo Senwen , Xu Yaobo , Xie Jie , Pan Guoqing , Zhou Zeyang
Published: July 2022

Nigericin is a polyether antibiotic with potent antibacterial, antifungal, antimalarial and anticancer activity. NigR, the only regulator in the nigericin biosynthetic gene cluster in Streptomyces malaysiensis F913, was identified as a SARP family regulator. Disruption of nigR abolished nigericin biosynthesis, while complementation of nigR restored nigericin production, suggesting that NigR is an essential positive regulator for nigericin biosynthesis. Overexpression of nigR in Streptomyces malaysiensis led to significant increase in nigericin production compared to the wild-type strain. Nigericin production in the overexpression strain was found to reach 0.56 g/L, which may be the highest nigericin titer reported to date. Transcriptional analysis suggested that nigR is required for the transcription of structural genes in the nig gene cluster; quantitative RT-PCR analysis revealed that the expression of structural genes was upregulated in the nigR overexpression strain. Our study suggested that NigR acts in a positive manner to modulate nigericin production by activating transcription of structural genes and provides an effective strategy for scaling up nigericin production.
Effects of Coenzyme Q10 Supplementation on Biomarkers of Oxidative Stress in Adults: A GRADE-Assessed Systematic Review and Updated Meta-Analysis of Randomized Controlled Trials
Authors: Dai Suming , Tian Zezhong , Zhao Dan , Liang Ying , Liu Meitong , Liu Zhihao , Hou Shanshan , Yang Yan
Published: July 2022

Evidence shows that exogenous CoQ10 supplementation may potentially attenuate oxidative stress status. However, its effective dose and evidence certainty require further evaluation in the general population via more updated randomized controlled trials (RCTs). Databases (PubMed, Embase and Cochrane Library) were searched up to 30 March 2022. Evidence certainty was assessed using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach. Thirty-four RCTs containing 2012 participants were included in this review. Pooled effects of significant increase in total antioxidant capacity (TAC) (standardized mean difference: 1.83, 95%CI: [1.07, 2.59], p < 0.001) and significant reduction in malondialdehyde (MDA) concentrations (−0.77, [−1.06, −0.47], p < 0.001) were shown after CoQ10 supplementation compared to placebo. However, we could not determine that there was a significant increase in circulating superoxide dismutase (SOD) levels yet (0.47, [0.00, 0.94], p = 0.05). Subgroup analyses implied that CoQ10 supplementation was more beneficial to people with coronary artery disease or type 2 diabetes. Additionally, taking 100–150 mg/day CoQ10 supplement had better benefits for the levels of TAC, MDA and SOD (all p < 0.01). These results to a statistically significant extent lent support to the efficacy and optimal dose of CoQ10 supplementation on attenuating oxidative stress status in adults.
Thermal Layer Design in Fused Filament Fabrication
Authors: Bjørken Olav U. , Andresen Benjamin , Eikevåg Sindre W. , Steinert Martin , Elverum Christer W.
Published: July 2022

The current limitations of design for additive manufacturing (DfAM) are the state of knowledge on materials and the effects of production parameters. As more engineering-grade polymers become available for fused filament fabrication (FFF), the designs and processes must be adapted to fully utilize the structural properties of such materials. By studying and comparing the production parameters of a material test specimen and a component, the effects of layer temperature on the strength, surface roughness, and dimensional accuracy of PA6-CF were found. As the cross-section increases in component manufacturing, maintaining the layer temperature becomes a major challenge. From the findings, the concept of thermal layer design (TLD) was introduced as a way of increasing strength via temperature in selected regions after presenting the effect of layer temperature. TLD proved to have a major effect on layer temperature and heat distribution. Depending on the investigated layer temperature, from 147 °C to 193 °C the UTS of PA6-CF increased from 42 MPa to 73 MPa. Implementing TLD in DfAM represents a big leap for designing high-performance polymer components.
Tunable Electromagnetically Induced Transparent Window of Terahertz Metamaterials and Its Sensing Performance
Authors: Wu Zhenlin , An Peiyao , Ding Menghan , Qi Yanan , Zhang Lin , Han Shaoshuai , Lian Di , Chen Changming , Yang Xin
Published: July 2022

The electromagnetically induced transparency effect of terahertz metamaterials exhibits excellent modulation and sensing properties, and it is critical to investigate the modulation effect of the transparent window by optimizing structural parameters. In this work, a unilateral symmetrical metamaterial structure based on the cut-wire resonator and the U-shaped split ring resonator is demonstrated to achieve electromagnetically induced transparency-like (EIT-like) effect. Based on the symmetrical structure, by changing the structural parameters of the split ring, an asymmetric structure metamaterial is also studied to obtain better tuning and sensing characteristics. The parameters for controlling the transparent window of the metamaterial are investigated in both passive and active modulation modes. In addition, the metamaterial structure based on the cut-wire resonator, unilateral symmetric and asymmetric configurations are investigated for high performance refractive index sensing purposes, and it is found that the first two metamaterial structures can achieve sensitivity responses of 63.6 GHz/RIU and 84.4 GHz/RIU, respectively, while the asymmetric metamaterial is up to 102.3 GHz/RIU. The high sensitivity frequency response of the proposed metamaterial structures makes them good candidates for various chemical and biomedical sensing applications.
Linear Dimensional Change in Acrylic Denture Teeth Positions Factored by Different Processing Techniques and Occlusal Forms: An In Vitro Study
Authors: Sayed Mohammed E. , Porwal Amit , Jain Saurabh , Alshehri Abdulkarim Hussain , Alqahtani Nasser M. , Hadadi Ashwaq Hadi Ali , Zakri Rawan Abdulwadoud , Zeed Sahar Mahdi Musa , Nahari Saswan Ibrahim , Alsurayyie Fatimah H. , Alqarni Hatem , Alqahtani Saeed M. , AlResayes Saad Saleh
Published: July 2022

The current literature lacks substantial evidence for the effect of denture base processing techniques and posterior denture tooth forms on denture tooth shifts due to denture base resin polymerization. The aim of this study was to evaluate the combined effect of PMMA-based denture processing techniques (compression packing and injection molding) and posterior tooth forms (semi-anatomic and non-anatomic) on the linear dimensional shift of denture teeth following denture processing in both horizontal and vertical dimensions. Two different complete denture fabrication techniques were used to prepare forty ideal maxillary complete dentures using two different types of posterior tooth forms. The used fabrication techniques were conventional heat polymerized compression packing and injection molding. The posterior tooth forms used in the current study were non-anatomic tooth (0 degrees) and semi-anatomic tooth forms (approximately 20 degrees). Initial linear measurements (vertical and horizontal) were taken from pre-specified points for the central incisor and first molar. Specimens were randomly divided into four groups (n = 10), and denture processing was performed using the two techniques. Final linear measurements were recorded. The linear change in dimension for all six parameters was calculated by deducting the after values from the before values. Since the discrepancies were both positive and negative in magnitude, the absolute value of the difference was taken for further analysis. This value represents the dimensional change. T-tests were used to compare the mean dimensional changes. Furthermore, the mean dimensional changes for all the six parameters were compared using a two-way analysis of variance. The alpha error was set at 5%, and a p-value of less than 0.05 was considered statistically significant. The injection molding technique showed significantly fewer tooth movements in both the vertical and horizontal measurements as compared to the conventional compression packing technique. The non-anatomic tooth showed significantly fewer changes in tooth movement as compared to semi-anatomic teeth in both the compression and injection techniques. This study can guide the selection of a proper processing technique for a particular posterior tooth form, thus minimizing occlusal discrepancies and reducing occlusal corrections during laboratory and clinical remount procedures.
A Small UAV Optimized for Efficient Long-Range and VTOL Missions: An Experimental Tandem-Wing Quadplane Drone
Authors: Okulski Michał , Ławryńczuk Maciej
Published: July 2022

Most types of Unmanned Aerial Vehicle (UAV, drone) missions requiring Vertical-Take-Off-and-Landing (VTOL) capability could benefit if a drone’s effective range could be extended. Example missions include Search-And-Rescue (SAR) operations, a remote inspection of distant objects, or parcel delivery. There are numerous research works on multi-rotor drones (e.g., quadcopters), fixed-wing drones, VTOL quadplanes, or tilt-motor/tilt-wing VTOLs. We propose a unique compact VTOL UAV optimized for long hover and long-range missions with great lifting capacity and manoeuvrability: a tandem-wing quadplane with fixed motors only. To the best of our knowledge, such a drone has not yet been researched. The drone was designed, built, and tested in flight. Construction details, its advantages, and issues are discussed in this research.
Hybrid Shielding for Hypervelocity Impact of Orbital Debris on Unmanned Spacecraft
Authors: Fowler Kayleigh , Teixeira-Dias Filipe
Published: July 2022

The passive shielding of space craft structures is critical due to the increase in demand for lightweight protection, which is required to counter the damaging effects of micro-meteoroid orbital debris (MMOD) on unmanned spacecraft, which have steeply increased in recent years. Research on hypervelocity impact (HVI) led to the development of shield configurations such as the conventional Whipple shield, which consists of two plates separated by a stand-off distance to allow for the fragmentation and dispersion of the debris from the impact. Variations in the Whipple shield have been proposed, where additional layers are included for increased energy dissipation efficiency. In this work, the authors develop, validate and test a numerical model of an orthogonally loaded hybrid Whipple shield, incorporating an aluminium honeycomb core, orientated with hexagonal tubes perpendicular to the direction of proposed debris travel, to mitigate the well-known channelling effect. The debris threat is an A2024-T3 projectile, impacting the structure at a velocity of 6.5 km/s. The proposed model is validated with experimental observations of the debris spread at half-angle and the efficiency of the proposed topology is assessed against a conventional two-plate A2024-T3 shield. The honeycomb core cell density, its position relative to the point of impact, the thickness of the honeycomb shell, and the material of the honeycomb are thoroughly analysed. A hybrid honeycomb structure concept is proposed, which provides a highly efficient alternative to a standard Whipple shield design, without significantly compromising the weight of the structure. The obtained results clearly show that the hybrid Whipple shield exhibits significantly increased the kinetic energy dissipation of the debris from the impactor and shield front plate, with an increase in the dissipated kinetic energy that can reach 86.8% relative to the conventional shield.
Positioning Information Based High-Speed Communications with Multiple RISs: Doppler Mitigation and Hardware Impairments
Authors: Wang Ke , Lam Chan-Tong , Ng Benjamin K.
Published: July 2022

In this paper, we consider a multiple reconfigurable intelligent surface (RIS)-assisted system using positioning information (PI) to explore the potential of Doppler effect mitigation and spectral efficiency (SE) enhancement in high-speed communications (HSC) in the presence of hardware impairments (HWI). In particular, we first present a general multi-RIS-assisted system model for HSC with HWI. Then, based on PI, different phase shift optimization strategies are designed and compared for maximizing SE, eliminating Doppler spread, and maintaining a very low delay spread. Moreover, we compare the performance of different numbers of RISs with HWI in terms of SE and delay spread. Finally, we extend our channel model from line-of-sight to the Rician channel to demonstrate the effectiveness and robustness of our proposed scheme. Numerical results reveal that the HWI of RISs increases the delay spread, but has no impact on Doppler shift and spread. Additionally, the multiple RIS system not only suffers a more severe delay spread, but is limited in SE due to the HWI. When the number of RISs increases from 2 to 16, the range of average spectral efficiency and delay spread are from 4 to 4.6 Bit/s/Hz and from 0.7 μs to 2.5 μs, respectively. In contrast to conventional RIS-assisted systems that require channel estimation, the proposed PI-based RIS system offers simplicity without compromising effectiveness and robustness in both SE enhancement and Doppler mitigation.