Miracle-dz/UniFAR-FTUs huggingface dataset:
A bibliometric analysis of non-coding RNA studies in acute pancreatitis

Background: Non-coding RNA (ncRNA) is a type of RNA that does not code for proteins and plays a crucial role in the onset, progression, diagnosis, and therapy of acute pancreatitis. However, bibliometric, and visual analyses of studies on acute pancreatitis and ncRNA are lacking. This study seeks to provide a bibliometric overview of the knowledge structure and research hotspots of ncRNA in the field of acute pancreatitis research. Materials and methods: Literature search and collection of information in the field of ncRNA-related research in acute pancreatitis from 2000-2023 through the Web of Science Core Collection. Use CiteSpace and VOSviewer to visually analyze countries, institutions, authors, and keywords. Results: A total of 563 articles have been published in the field of ncRNA-related research in acute pancreatitis, and the number of publications in this field is gradually increasing. The largest number of publications was from China. Four clusters were produced by the co-occurrence cluster analysis of the top 89 keywords: studies of ncRNA in inflammation, autophagy, and apoptosis in acute pancreatitis; studies related to microRNA expression in pancreatic cancer among ncRNA; studies related to microRNAs as diagnostic and therapeutic markers in acute pancreatitis; and studies related to ncRNA in acute pancreatitis; The key words “injury,” “pathway” and “extracellular vesicles” are the key words of emerging research hotspots. Conclusion: In conclusion, ncRNA research in acute pancreatitis is an established discipline. Researchers can use the research hotspots and frontiers in this field as a guide for choosing their research direction.
Mice with Deficient BK Channel Function Show Impaired Prepulse Inhibition and Spatial Learning, but Normal Working and Spatial Reference Memory

Genetic variations in the large-conductance, voltage- and calcium activated potassium channels (BK channels) have been recently implicated in mental retardation, autism and schizophrenia which all come along with severe cognitive impairments. In the present study we investigate the effects of functional BK channel deletion on cognition using a genetic mouse model with a knock-out of the gene for the pore forming α-subunit of the channel. We tested the F1 generation of a hybrid SV129/C57BL6 mouse line in which the slo1 gene was deleted in both parent strains. We first evaluated hearing and motor function to establish the suitability of this model for cognitive testing. Auditory brain stem responses to click stimuli showed no threshold differences between knockout mice and their wild-type littermates. Despite of muscular tremor, reduced grip force, and impaired gait, knockout mice exhibited normal locomotion. These findings allowed for testing of sensorimotor gating using the acoustic startle reflex, as well as of working memory, spatial learning and memory in the Y-maze and the Morris water maze, respectively. Prepulse inhibition on the first day of testing was normal, but the knockout mice did not improve over the days of testing as their wild-type littermates did. Spontaneous alternation in the y-maze was normal as well, suggesting that the BK channel knock-out does not impair working memory. In the Morris water maze knock-out mice showed significantly slower acquisition of the task, but normal memory once the task was learned. Thus, we propose a crucial role of the BK channels in learning, but not in memory storage or recollection.
Performance of Dynamically Resizing Message Fields for Differential Serialization of SOAP Messages

SOAP is an XML-based protocol that is widely used in Web services and that provides extensibility, portability, flexibility, and descriptiveness. Unfortunately, these attractive characteristics come at the expense of performance, threatening to preclude the use of SOAP for high performance computing. In particular, we have shown in previous work that serialization and deserialization of scientific data are by far the most expensive operations that limit SOAP’s performance. One technique for eliminating this performance bottleneck is differential serialization—saving copies of messages in the sender, and reserializing only the differences between the most recent message and the next one. In this paper, we build on our earlier introduction and investigation of differential serialization by describing improved algorithms for dynamically resizing message fields, which is necessary when newly serialized data requires a different amount of space than the old data occupied. In particular, we describe our implementation of stealing space from neighboring fields, and present a performance study that compares this new technique with others from previous work. Results show that stealing (1) performs better than other techniques for increasing message field size when extra space is limited, and (2) is effective at keeping message sizes from expanding over time, but results in a tradeoff with performance when compared against other approaches that allow message sizes to grow.1
Document Retrieval using a Probabilistic Knowledge Model

We are interested in enhancing information retrieval methods by incorporating domain knowledge. In this paper, we present a new document retrieval framework that learns a probabilistic knowledge model and exploits this model to improve document retrieval. The knowledge model is represented by a network of associations among concepts defining key domain entities and is extracted from a corpus of documents or from a curated domain knowledge base. This knowledge model is then used to perform concept-related probabilistic inferences using link analysis methods and applied to the task of document retrieval. We evaluate this new framework on two biomedical datasets and show that this novel knowledge-based approach outperforms the state-of-art Lemur/Indri document retrieval method.
Integration of Action and Language Knowledge: A Roadmap for Developmental Robotics

This position paper proposes that the study of embodied cognitive agents, such as humanoid robots, can advance our understanding of the cognitive development of complex sensorimotor, linguistic, and social learning skills. This in turn will benefit the design of cognitive robots capable of learning to handle and manipulate objects and tools autonomously, to cooperate and communicate with other robots and humans, and to adapt their abilities to changing internal, environmental, and social conditions. Four key areas of research challenges are discussed, specifically for the issues related to the understanding of: 1) how agents learn and represent compositional actions; 2) how agents learn and represent compositional lexica; 3) the dynamics of social interaction and learning; and 4) how compositional action and language representations are integrated to bootstrap the cognitive system. The review of specific issues and progress in these areas is then translated into a practical roadmap based on a series of milestones. These milestones provide a possible set of cognitive robotics goals and test scenarios, thus acting as a research roadmap for future work on cognitive developmental robotics.
Role of a Bacillus subtilis Direct-Fed Microbial on Digesta Viscosity, Bacterial Translocation, and Bone Mineralization in Turkey Poults Fed with a Rye-Based Diet

Rye contains high concentrations of non-starch polysaccharides (NSPs), leading to reduced digestibility. Since poultry have little or no endogenous enzymes capable of hydrolyzing these NSP, exogenous carbohydrases as feed additives are used in an attempt to reduce the anti-nutritional effects of these polysaccharides. Previously, an in vitro study conducted in our laboratory showed that inclusion of certain Bacillus direct-fed microbial (DFM) candidates that produce exogenous phytase, lipase, protease, cellulase, and xylanase in high-NSP diets significantly reduced both digesta viscosity and Clostridium perfringens proliferation. In the present study, rye-based turkey starter diets with or without Bacillus-DFM were administered ad libitum to day-of-hatch turkey poults in two independent experiments. In both experiments, day-of-hatch turkey poults were randomly assigned to either a control diet (CON) or a DFM treated diet (n = 25 birds/group). At 10 days-of-age, all turkey poults from experiments 1 and 2 were weighted and 12 turkey poults/group were randomly selected and humanely killed. Liver samples were aseptically collected to evaluate bacterial translocation, and intestinal digesta samples were individually collected to evaluate viscosity. Additionally, in experiment 2 both tibias were removed for assessment of bone parameters. In both experiments, the treated group showed a reduction in the total number of coliforms in the liver and a reduced digesta viscosity when compared to the CON group (P < 0.05). Turkey poults fed the Bacillus-DFM candidate had increased tibia diameter, breaking strength, ash content, calcium content, and phosphorus content when compared with CON turkey poults. In summary, turkey poults fed with a rye-based diet without DFM showed an increase in bacterial translocation and digesta viscosity, accompanied by a reduction in bone mineralization; however, these adverse effects can be prevented by the inclusion of selected a Bacillus-DFM candidate in high-NSP diets.
A Blind-Zone Detection Method Using a Rear-Mounted Fisheye Camera With Combination of Vehicle Detection Methods

This paper proposes a novel approach for detecting and tracking vehicles to the rear and in the blind zone of a vehicle, using a single rear-mounted fisheye camera and multiple detection algorithms. A maneuver that is a significant cause of accidents involves a target vehicle approaching the host vehicle from the rear and overtaking into the adjacent lane. As the overtaking vehicle moves toward the edge of the image and into the blind zone, the view of the vehicle gradually changes from a front view to a side view. Furthermore, the effects of fisheye distortion are at their most pronounced toward the extremities of the image, rendering detection of a target vehicle entering the blind zone even more difficult. The proposed system employs an AdaBoost classifier at distances of 10-40 m between the host and target vehicles. For detection at short distances where the view of a target vehicle has changed to a side view and the AdaBoost classifier is less effective, identification of vehicle wheels is proposed. Two methods of wheel detection are employed: at distances between 5 and 15 m, a novel algorithm entitled wheel arch contour detection (WACD) is presented, and for distances less than 5 m, Hough circle detection provides reliable wheel detection. A testing framework is also presented, which categorizes detection performance as a function of distance between host and target vehicles. Experimental results indicate that the proposed method results in a detection rate of greater than 93% in the critical range (blind zone) of the host.
Modified HHT analysis of micro-Doppler signatures scattered from rotating flat blades

This paper has presented the time-frequency analysis (TFA) of the micro-Doppler signatures scattered from rotating flat blades using the modified Hilbert-Huang transform (HHT). After the modified HHT examined the scattered field data, the analysis results showed good agreement with real blade numbers in the propeller. It can be concluded that the TFA via the modified HHT provides the discriminative characteristic for recognizing a small aircraft target that generally has small radar cross section (RCS).
Towards industrial robots with human-like moral responsibilities

Robots do not have any capability of taking moral responsibility. At the same time industrial robotics is entering a new era with ¿intelligent¿ robots sharing workbench with humans. Teams consisting of humans and industrial robots are no longer science fiction. The biggest worry in this scenario is the fear of humans losing control and robots running amok. We believe that the current way of implementing safety measures have shortcomings, and cannot address challenges related to close collaboration between humans and robots. We propose that ¿intelligent¿ industrial robots of the future should have moral responsibilities towards their human colleagues. We also propose that implementation of moral responsibility is radically different from standard safety measures.
The Bacterial Isolates and Plasmid Profile of Extended Spectrum Beta-Lactamases Producers Causing Urinary Tract Infection among Pregnant Women in Uyo, Nigeria

Background: Extended spectrum beta-lactamases (ESBLs) are enzymes that compromise the efficacy of all beta-lactams and are spread by plasmids. They are of public health importance the world over; however, in Nigeria in general and Uyo in particular, tests for their detection are not routinely done in hospital laboratories despite increase in treatment failures observed for common clinical conditions like urinary tract infection. Objective: To isolate ESBLs producing uropathogens and the plasmid underlying their resistance to antibiotics. Materials and Methods: Three hundred urine specimens (n = 300) were collected from pregnant women attending antenatal clinics at St. Lukes Hospital, Anua, cultured and incubated according to accepted standard. Identification of isolates was done using Microbact 24E (Oxoid, UK) system. The predominant bacterial pathogens were Escherichia coli (42%) followed by Klebsiella pneumonia (21%), Klebsiella oxytoca (12%), Citrobacter spp. (5%), Proteus mirabilis (7%), Enterobacter spp. (12%) and Acinetobacter baumanii (1%). The isolated bacteria were tested for their antibiotic susceptibility using Clinical Laboratory Standard Institute (CLSI) recommended disc diffusion method. A Double Disk Synergy Test (DDST) and Phenotypic Disk Confirmatory Test (PDCT) were performed to determine ESBL production. Chromagar ESBL was also used to test for the presence of ESBL producing isolates. The plasmid content of ESBL producing isolates and their participation in drug resistance were investigated. Results: Of the 80 bacterial isolates causing urinary tract infection in these women, the ESBL producers were found to be 16 (20%). Out of these 16 ESBL producing urogenital isolates Klebsiella pneumonia (8, 50%) was the most prevalent. Others include Escherichia coli (38%), Klebsiella oxytoca (6%) and Enterobacter cloacae (6). Plasmid content of ESBL producing isolates was found to be 87.5%. Conclusion: The Extended Spectrum Beta-lactamase producing uropathogens mainly of plasmid origin are increasingly responsible for the cause of community acquired urinary tract infections in pregnant women in Uyo.
Benefits and risks of weight-loss treatment for older, obese women

Background: A key issue in the treatment of obesity in older adults is whether the health benefits of weight loss outweigh the potential risks with respect to musculoskeletal injury. Objective: To compare change in weight, improvements in metabolic risk factors, and reported musculoskeletal adverse events in middle-aged (50–59 years) and older (65–74 years), obese women. Materials and methods: Participants completed an initial 6-month lifestyle intervention for weight loss, comprised of weekly group sessions, followed by 12 months of extended care with biweekly contacts. Weight and fasting blood samples were assessed at baseline, month 6, and month 18; data regarding adverse events were collected throughout the duration of the study. Results: Both middle-aged (n = 162) and older (n = 56) women achieved significant weight reductions from baseline to month 6 (10.1 ± 0.68 kg and 9.3 ± 0.76 kg, respectively) and maintained a large proportion of their losses at month 18 (7.6 ± 0.87 kg and 7.6 ± 1.3 kg, respectively); there were no significant differences between the two groups with respect to weight change. Older women further experienced significant reductions in systolic blood pressure, HbA 1c , and C-reactive protein from baseline to month 6 and maintained these improvements at month 18. Despite potential safety concerns, we found that older women were no more likely to experience musculoskeletal adverse events during the intervention as compared with their middle-aged counterparts. Conclusion: These results suggest that older, obese women can experience significant health benefits from lifestyle treatment for obesity, including weight loss and improvements in disease risk factors. Further investigation of the impact of weight loss on additional health-related parameters and risks (eg, body composition, muscular strength, physical functioning, and injuries) in older adults is needed.
Building Immersive Data Visualizations for the Web

We present our early work on building prototype applications for Immersive Analytics using emerging standards-based web technologies for VR. For our preliminary investigations we visualize 3D bar charts that attempt to resemble recent physical visualizations built in the visualization community. We explore some of the challenges faced by developers in working with emerging VR tools for the web, and in building effective and informative immersive 3D visualizations.
Innovation and Productivity in Smes. Empirical Evidence for Italy 1. Introduction 3. Data and Methodology

Innovation in SMEs exhibits some peculiar features that most traditional indicators of innovation activity do not capture. Therefore, in this paper, we develop a structural model of innovation which incorporates information on innovation success from firm surveys along with the usual R&D expenditures and productivity measures. We then apply the model to data on Italian SMEs from the " Survey on Manufacturing Firms " conducted by Mediocredito-Capitalia covering the period 1995-2003. The model is estimated in steps, following the logic of firms' decisions and outcomes: in the first, R&D intensity is linked to a set of firm and market characteristics. We find that international competition fosters R&D intensity, especially for high-tech firms. Firm size, R&D intensity, along with investment in equipment enhances the likelihood of having both process and product innovation. Both these kinds of innovation have a positive impact on firm's productivity, especially process innovation. Among SMEs, larger and older firms seem to be less productive. * We would like to thank the Mediocredito-Capitalia research department for having kindly supplied firm level data for this project. We thank also and participants at the NBER Productivity Seminars (Cambridge, MA), at the workshop " Drivers and Impacts of Corporate R&D in SMEs " at the IPTS (Seville). The views expressed by the authors do not necessarily reflect those of the Bank of Italy. In the past decade, labor productivity growth in Italy has been one of the lowest in the EU; the low level has been particularly strong in manufacturing, where the growth rate even turned negative in the period from 2000 to 2005 (see Figure 1). Such a poor performance raises unavoidable policy concerns about the possible underlying reasons. Is the labor productivity slowdown due to the decline in total factor productivity (see Daveri and Jona-Lasinio 2005)? Or, more precisely, is it a consequence of the exhaustion of the so-called " capital deepening " phase that supported labor productivity growth during the Eighties (as documented by Pianta and Vaona. 2007)? Alternatively, is it simply due to the input reallocation following a change in the relative price of labor with respect to capital after the labor market reforms (Brandolini et al., 2007)? Or does the explanation lie in the evergreen motto that Italian firms exhibit insufficient R&D investment (European Commission, 2006)? The latter aspect has been largely explained by the unquestionable fragmentation of the Italian production system. According to the latest …
Assessment of Ontology-based Tools : A Step Towards Systemizing the Scenario Approach

Scenarios have been already used for designing and evaluating ontology-based tools. For example, the so-called “motivating scenarios” are a core component of the TOVE ontological engineering method elaborated by Grüninger and Fox (1995; Uschold and Grüninger, 1996). We ourselves used a “scenario approach” for designing and evaluating CoMMA, a corporate memory computer platform based on ontologies and agents; the approach was inspired by the scenario approaches proposed in the HCI and CSCW communities, which we consider more user-oriented than the “motivating scenarios” approach. In this paper, we account for our CoMMA experience and its major lesson: the necessity to apply the scenario approach more systematically for assessing the usability and utility of ontology-based tools.
Analysis of nuclear transport signals in the human apurinic/apyrimidinic endonuclease (APE1/Ref1)

The mammalian abasic-endonuclease1/redox-factor1 (APE1/Ref1) is an essential protein whose subcellular distribution depends on the cellular physiological status. However, its nuclear localization signals have not been studied in detail. We examined nuclear translocation of APE1, by monitoring enhanced green fluorescent protein (EGFP) fused to APE1. APE1's nuclear localization was significantly decreased by deleting 20 amino acid residues from its N-terminus. Fusion of APE1's N-terminal 20 residues directed nuclear localization of EGFP. An APE1 mutant lacking the seven N-terminal residues (ND7 APE1) showed nearly normal nuclear localization, which was drastically reduced when the deletion was combined with the E12A/D13A double mutation. On the other hand, nearly normal nuclear localization of the full-length E12A/D13A mutant suggests that the first 7 residues and residues 8–13 can independently promote nuclear import. Both far-western analyses and immuno-pull-down assays indicate interaction of APE1 with karyopherin alpha 1 and 2, which requires the 20 N-terminal residues and implicates nuclear importins in APE1's nuclear translocation. Nuclear accumulation of the ND7 APE1(E12A/D13A) mutant after treatment with the nuclear export inhibitor leptomycin B suggests the presence of a previously unidentified nuclear export signal, and the subcellular distribution of APE1 may be regulated by both nuclear import and export.
An improved proportionate NLMS algorithm based on the l0 norm

The proportionate normalized least-mean-square (PNLMS) algorithm was developed in the context of network echo cancellation. It has been proven to be efficient when the echo path is sparse, which is not always the case in real-world echo cancellation. The improved PNLMS (IPNLMS) algorithm is less sensitive to the sparseness character of the echo path. This algorithm uses the l1 norm to exploit sparseness of the impulse response that needs to be identified. In this paper, we propose an IPNLMS algorithm based on the l0 norm, which represents a better measure of sparseness than the l1 norm. Simulation results prove that the proposed algorithm outperforms the original IPNLMS algorithm.