Miracle-dz/UniFAR-FTUs huggingface dataset:
UML-Based Cyber-Physical Production Systems on Low-Cost Devices under IEC-61499

Current industry must improve the day-to-day control and industrial communications of its processes in order to bring itself closer to the Industry 4.0 paradigm. To attain these improvements, which aim towards obtaining agile and intelligent manufacturing systems, the IEC-61499 standard is considered to be the main option by many researchers. Despite its benefits, its biggest drawback is the lack of software tools required for an effective design process for distributed control systems. The following work details the implementation of the IEC-61499 standard in low-cost devices using 4DIAC-FORTE for distributed control of a FESTO MPS 200 educational system, by using Unified Modeling Language (UML) diagrams as a software tool for modeling the function blocks (FBs) of the IEC-61499 standard. This work demonstrates a simple and easy way to create distributed systems.
An Automatic Approach for Building Place-Name Datasets from the Web

A large amount of valuable geographic information about places, including place names, addresses, and telephone numbers exists on the Web but only a small portion of the data is accessible through structured sources (e.g., Google Maps API, GeoNames, and OpenStreetMaps). Moreover, these structured sources only provide static information and do not incorporate changes in a timely manner. This paper presents an approach to automatically build place-name datasets from the results of a Web search engine. In this work, our approach uses the Google search engine API to retrieve webpages associated with specific location names and place types and then parses the returned webpages to extract place names and addresses. The result is a place-name dataset built completely from information on the Web. To evaluate our approach, we collected ground truth data using Google Street View by reading business signs in the image. We tested our approach on 10 city blocks in a U.S. city. The results showed that the proposed approach effectively generated place datasets on a par with Google Maps and outperformed the data available in OpenStreetMap.
Light detection and ranging-based measures of mixed hardwood forest structure.

Light detection and ranging (LiDAR) is increasingly used to map terrain and vegetation. Data collection is expensive, but costs are reduced when multiple products are derived from each mission. We examined how well low-density leaf-off LiDAR, originally flown for terrain mapping, quantified hardwood forest structure. We measured tree density, dbh, basal area, mean tree height, Lorey's mean tree height, and sawtimber and pulpwood volume at 114 field plots. Using univariate and multivariate linear regression models, we related field data to LiDAR return heights. We compared models using all LiDAR returns and only first returns. First-return univariate models explained more variability than all-return models; however, the differ- ences were small for multivariate models. Multiple regression models had R 2 values of 65% for sawtimber and pulpwood volume, 63% for Lorey's mean tree height, 55% for mean tree height, 48% for mean dbh, 46% for basal area, and 13% for tree density. However, the standard error of the mean for predictions ranged between 1 and 4%, and this level of error is well within levels needed for broad-scale forest assessments. Our results suggest that low-density LiDAR intended for terrain mapping is valuable for broad-scale hardwood forest inventories. FOR . S CI. 56(3):313-326.
Landslide in Dossena (BG): comparison between interferometric techniques

In this work the landslide of Dossena (BG, Italy), located in a mountainous area north of Milan, is taken as case study to compare different spaceborne SAR interferometric techniques and find the best answer to the requests of the local geologists. The landslide of Dossena, in fact, is known since almost 20 years and it has been monitored with levelling instruments for some periods. But, due to economical and technical problems, the precise delimitation of the sliding area was not yet known. Spaceborne SAR interferometric techniques are able to detect terrain movements within wide areas and thus represent the ideal instrument to find the borders of such deformations. The most accurate interferometric algorithm at the moment is the Permanent Scatterers (PS) technique, developed by POLIMI. But the PS technique requires that a target, in order to be detected as coherent, shows an electromagnetic stability for the whole time-span of the acquisitions. This is usually the case of targets in urban sites, but not in mountainous areas. In this work we present new hints for multi-temporal analysis of SAR images to extract information also by partially coherent targets and thus provide more spatially dense deformation maps in extra-urban areas. A novel processing chain has been implemented and applied to the Dossena case study, allowing to increase the number of measure points and thus to better identify the borders of the landslide.
ICE-BA: Incremental, Consistent and Efficient Bundle Adjustment for Visual-Inertial SLAM

Modern visual-inertial SLAM (VI-SLAM) achieves higher accuracy and robustness than pure visual SLAM, thanks to the complementariness of visual features and inertial measurements. However, jointly using visual and inertial measurements to optimize SLAM objective functions is a problem of high computational complexity. In many VI-SLAM applications, the conventional optimization solvers can only use a very limited number of recent measurements for real time pose estimation, at the cost of suboptimal localization accuracy. In this work, we renovate the numerical solver for VI-SLAM. Compared to conventional solvers, our proposal provides an exact solution with significantly higher computational efficiency. Our solver allows us to use remarkably larger number of measurements to achieve higher accuracy and robustness. Furthermore, our method resolves the global consistency problem that is unaddressed by many state-of-the-art SLAM systems: to guarantee the minimization of re-projection function and inertial constraint function during loop closure. Experiments demonstrate our novel formulation renders lower localization error and more than 10x speedup compared to alternatives. We release the source code of our implementation to benefit the community1.
Colour Correction for Stereoscopic Omnidirectional Images

Stereoscopic omnidirectional images (ODI) when viewed with a head-mounted display are a way to generate an immersive experience. Unfortunately, their creation is not an easy process, and different problems can be present in the ODI that can reduce the quality of experience. A common problem is colour mismatch, which occurs when the colours of the objects in the scene are different between the two stereoscopic views. In this paper we propose a novel method for the correction of colour mismatch based on the subdivision of ODIs into patches, where local colour correction transformations are fitted and then globally combined. The results presented in the paper show that the proposed method is able to reduce the colour mismatch in stereoscopic ODIs.
Relationship between the endothelium biomarkers endocan and thrombomodulin and slow coronary flow

Background: Growing evidence suggests that endothelial dysfunction plays a key role in the pathophysiology of Slow Coronary Flow (SCF). This study investigated the association between endothelial biomarkers endocan and soluble Thrombomodulin (sTM) and SCF. Methods: The study population consisted of 89 subjects (54 patients with SCF and 35 controls). Coronary flow rate was assessed using the Thrombolysis in Myocardial Infarction (TIMI) Frame Count (TFC) method. The serum endocan and sTM levels of all subjects were analysed. Results: Significantly higher endocan levels (1.14 ± 0.22 vs. 0.96 ± 0.32 ng/ml; p=0.009) and sTM levels (657.06 ± 198.18 vs. 592.76 ± 128.45 pg/ml; p=0.119) were observed in the SCF group relative to the control group. A positive correlation was detected between endocan and TFC (r=0.563; p=0.016). Multivariate logistic regression analysis revealed endocan as a predictor of SCF. Conclusions: The endocan level in SCF patients was significantly higher than in controls and the sTM level was also increased, although the difference was not significant. These results suggest that endocan may serve as a biomarker to predict SCF.
Endoscopic, Ultrasonographic, and Histologic Descriptions of Dextranomer/Hyaluronic Acid in a Case of Fecal Incontinence

Objective To present a case of fecal incontinence treated with dextranomer/hyaluronic acid (Solesta®) injections, which later caused clinical confusion and avoidable interventions. The endoscopic, ultrasonographic, and histologic appearances of dextranomer/hyaluronic acid will also be reported. Case Presentation A middle-aged Hispanic male who failed conservative management of his fecal incontinence was injected with dextranomer/hyaluronic acid in an attempt to alleviate symptoms. An unrelated screening colonoscopy was performed soon after, revealing a submucosal rectal lesion. Flexible sigmoidoscopy and endoscopic rectal ultrasound with FNA were scheduled for patient for further evaluation. An unknown foreign material was noted under microscopy and, upon attaining additional history, the gastroenterologist uncovered the patient's recent injections of dextranomer/hyaluronic acid. Conclusion Dextranomer/hyaluronic acid for the treatment of fecal incontinence has become more common in recent years. Though the imaging and histologic appearance of this gel-like material is seen in other areas of medicine, equivalent descriptions are limited in the anorectal region. To curb misdiagnoses and prevent unnecessary interventions, it is important to expound on the endoscopic, imaging, and histopathologic features of this tissue-bulking agent in the setting of fecal incontinence and to encourage communication, proper documentation, and easy accessibility to patient health information by all medical staff.
Reorganization of the Action Observation Network and Sensory-Motor System in Children with Unilateral Cerebral Palsy: An fMRI Study

Little is known about the action observation network (AON) in children with unilateral cerebral palsy (UCP). Using fMRI, we aimed to explore AON and sensory-motor network (SMN) in UCP children and compare them to typically developed (TD) children and analyse the relationship between AON (re-)organization and several neurophysiological and clinical measures. Twelve UCP children were assessed with clinical scales and transcranial magnetic stimulation (TMS). For the fMRI study, they underwent a paradigm based on observation of complex and simple object-manipulation tasks executed by dominant and nondominant hand. Moreover, UCP and TD children carried out a further fMRI session to explore SMN in both an active motor and passive sensory task. AON in the UCP group showed higher lateralization, negatively related to performances on clinical scales, and had greater activation of unaffected hemisphere as compared to the bilateral representation in the TD group. In addition, a good congruence was found between bilateral or contralateral activation of AON and activation of SMN and TMS data. These findings indicate that our paradigm might be useful in exploring AON and the response to therapy in UCP subjects.
DIGITAL TWINS AS A MODERN APPROACH TO DESIGN OF INDUSTRIAL PROCESSES

The objective of the paper was to describe the concept of a virtual, digital equivalent to a physical process. The basic idea of the virtual counterpart for the process called a digital twin is described first. Following this the hybrid computer system dedicated to the design of the optimal manufacturing technology for thin steel strips is presented. The models used in the system and the database are described. Numerical tests showing capabilities of the system recapitulate the work. 1.
The Associations between Toll-Like Receptor 9 Gene Polymorphisms and Cervical Cancer Susceptibility

This meta-analysis systematically reviews the association between Toll-like receptor 9 polymorphisms and the risk of cervical cancer. Case-control studies focused on the association were collected from the PubMed, Web of Science, Cochrane Library, Embase, MEDLINE, CNKI, VIP, and Wanfang databases from inception to July 2017. We screened the studies and assessed the methodological quality of the included studies and extracted data. A meta-analysis was performed using RevMan 5.3 and Stata 12.0 software. Pooled odds ratios and 95% confidence intervals were employed to evaluate the strength of the associations between Toll-like receptor 9 polymorphisms and cervical cancer risk. A total of 9 studies comprising 3331 cervical cancer patients and 4109 healthy controls met the inclusion criteria. Of these, 8 studies contained information about G2848A (rs352140) and 4 studies contained information about −1486T/C (rs187084). Our results revealed that the associations between rs187084 and cervical cancer risk in the dominant model (p = 0.002) and heterozygous model (p = 0.002) were significant, with 1.30- and 1.32-fold increases in susceptibility, respectively, compared to that in the wild-type model. However, rs352140 was not related to cervical cancer regardless of whether the subgroup analysis was conducted (p > 0.05). In conclusion, there is a significant correlation between rs187084 and cervical cancer risk with the minor C allele increasing the risk of occurrence of cervical cancer. However, rs352140 is not associated with the occurrence of cervical cancer.
Preschool predictors of reading ability in the first year of schooling in children with ASD

A high percentage of children with Autism Spectrum Disorder (ASD) show elevated challenges in learning to read. We investigated longitudinal predictors of reading skills in 41 children diagnosed with ASD. All children completed measures of precursor literacy skills at the age of 4–5 years, including phonological awareness, letter sound knowledge, rapid automatic naming, name writing, and phonological memory (digit span), along with measures of word‐ and passage‐level reading skills in their first year of formal schooling. Nonverbal cognition and letter sound knowledge accounted for 53.4% of the variance in regular single word reading at school age, with letter sound knowledge a significant individual predictor. Overall, 18 children showed reading ability scores in the average range on a standardized test of passage‐level reading ability, whereas 23 children performed below expectations. These groups differed significantly on all precursor literacy measures (at ages 4–5), except autism symptoms based on parent report. Group membership was significantly predicted by preschool receptive vocabulary, name writing, and rapid automatic naming, with high sensitivity and specificity. These results are discussed in reference to the literature describing early literacy predictors for typically developing children, highlighting key areas for future intervention and support. Autism Res 2018, 11: 1332–1344. © 2018 International Society for Autism Research, Wiley Periodicals, Inc.
Effect of dietary cotton stalk on nitrogen and free gossypol metabolism in sheep

Objective This study was to investigate the effects of dietary cotton stalk on nitrogen and free gossypol in sheep. Methods Treatments included 25% cotton stalk (Treat 1), 50% cotton stalk (Treat 2), and a control (no cotton stalk). Six Xinjiang daolang wethers were cannulated at the rumen and duodenum and fed one of these diets. The effects of these diets on nitrogen and free gossypol absorption and metabolism were determined. Fifteen healthy Xinjiang daolang wethers were assessed for daily gain, tissue lesions, and free gossypol accumulation. Results Dry matter intake decreased with increasing dietary cotton stalk. Total tract dry matter digestibility did not significantly differ among treatments. Dietary cotton stalk significantly decreased volatile fatty acids and increased ammonium nitrogen in the rumen. Nitrogen intake was significantly higher in Treat 2 than in the control or Treat 1. Nitrogen retention and free gossypol intake increased with dietary cotton stalk. Duodenal free gossypol flow did not increase, and free gossypol almost disappeared from the rumen. The free gossypol content of plasma and tissue was increased with dietary cotton stalk with liver free gossypol> muscle free gossypol>kidney free gossypol. Elevated dietary free gossypol decreased platelets, hemoglobin, and serum iron. Aspartate aminotransferase and γ-glutamyltransferase increased in Treat 2. With high long-term dietary cotton stalk intake, liver cells were swollen, and their nuclei dissolved. Renal cells were necrotic and the interstitia were enlarged. Conclusion With short-term cotton stalk administration, only a small amount of free gossypol is retained in the body. In response to long-term or high free gossypol cotton stalk feeding, however, free gossypol accumulates in, and damages the liver and kidneys.
Stem cell‐based therapy for Parkinson’s disease with a focus on human endometrium‐derived mesenchymal stem cells

Parkinson’s disease (PD) as an increasing clinical syndrome is a multifunctional impairment with systemic involvement. At present, therapeutic approaches such as l‐3,4‐dihydroxy‐phenylalanine replacement therapy, dopaminergic agonist administration, and neurosurgical treatment intend to relieve PD symptoms which are palliative and incompetent in counteracting PD progression. These mentioned therapies have not been able to replace the lost cells and they could not effectively slow down the relentless neurodegenerative process. Till now, there is a lack of eligible treatment for PD, and stem cells therapy recently has been considered for PD treatment. In this review, we demonstrate how human stem cell technology especially human endometrium‐derived stem cells have made advancement as a therapeutic source for PD compared with other treatments.
BRCA1 and BRCA2 Germline Mutation Screening in Western Algeria using High Resolution Melting Analysis (HRM).

Breast cancer is the leading cause of cancer deaths in Algerian women. Our aim is to analyze BRCA1 and BRCA2 genes mutations in 100 Algerian patients with a family history suggestive of genetic predisposition to breast cancer. BRCA1 and BRCA2 mutations were searched by High-Resolution Melting (HRM) analysis, followed by direct sequencing, and Multiplex Ligation- Dependent Probe Amplification (MLPA) for large deletions or duplications. An unclassified variant c.5117G>C, p.Gly1706ALA and a pathogenic mutation c. 2125_2126insA, p.Phe709TyrfX3 were detected in the BRCA1 gene. No large deletions or duplications were detected with MLPA. One deleterious mutation c.250C>T, p.Gin84X, and one unclassified variant c.9364G>A, p. Ala3122Thr were identified in BRCA2 gene. The pathological significance of this variant has to be specified and analysis of its segregation in the family and differs from those provided in the literature. Although on a limited cohort, our findings suggest a higher frequency of BRCA1/2 mutations in Algeria and it would be of interest to search for the presence of these pathogenic mutations in other family member for preventing the risk of cancer.
Market-testing a smartphone application for family planning: assessing potential of the CycleBeads app in seven countries through digital monitoring.

Background The advent of new technological approaches to family planning has the potential to address unmet need in low- and middle-income countries. Provision of fertility awareness-based apps have the ability to provide accessible, direct-to-user fertility information to help women achieve their reproductive goals. The CycleBeads app, a digital platform for the Standard Days Method (SDM), a modern method of family planning, helps women achieve or prevent pregnancy, or track their cycles using the only their period start dates. Methods Brief social marketing campaigns were launched by the app developer to monitor cost and distribution of the CycleBeads app, understand the user profile, and assess user experience. Monitoring and evaluation through in-app micro surveys occurred over a 6-cycle period in seven countries: Egypt, Ghana, India, Jordan, Kenya, Nigeria, and Rwanda. In-app micro-surveys were utilized to collect data around demographics, mode of use of the app, prior experiences with family planning, and satisfaction to better understand women's interactions with the apps, and the possibility for meeting unmet need. Analyzes focused on women who were using the app to prevent pregnancy or track their cycles. Results Social media campaigns proved to be an easy, low-cost approach to advertising the CycleBeads app. As a result, 356,520 women downloaded the app, and the cost to the advertiser per download ranged from $0.17-0.69. A majority of app users were between 20-29 years old, married or in exclusive relationships. Overall, 39.9% of users were using the app to prevent pregnancy, 38.5% to plan a pregnancy, and 21.6% were tracking their cycles. Among the users preventing pregnancy, 64.1% of women had not used a family planning method 3 months before downloading the CycleBeads app. One-third of users who were using the app to track their cycles, reported that they had not been using any form of family planning. In all seven countries, nearly 60% of women reported that they would definitely recommend the CycleBeads app to a friend, indicating their satisfaction with the app. Conclusions Our main findings indicate that a social media campaign is a low-cost approach to making the CycleBeads app accessible to women. The app addresses multiple reproductive intentions and attracts a diverse demographic of users across different life stages. For many women the app was the first modern method they used in the last 3 months, showing that fertility awareness-based apps have the potential to address an unmet need. Future studies should focus on changes in behavior during the fertile window, partner communication, and future family planning intentions.
Under the Hood: Using Diagnostic Classifiers to Investigate and Improve how Language Models Track Agreement Information

How do neural language models keep track of number agreement between subject and verb? We show that ‘diagnostic classifiers’, trained to predict number from the internal states of a language model, provide a detailed understanding of how, when, and where this information is represented. Moreover, they give us insight into when and where number information is corrupted in cases where the language model ends up making agreement errors. To demonstrate the causal role played by the representations we find, we then use agreement information to influence the course of the LSTM during the processing of difficult sentences. Results from such an intervention reveal a large increase in the language model’s accuracy. Together, these results show that diagnostic classifiers give us an unrivalled detailed look into the representation of linguistic information in neural models, and demonstrate that this knowledge can be used to improve their performance.