Miracle-dz/UniFAR-FTUs huggingface dataset:
Detection of reinforcement bar fractures by measuring the remanent and active magnetic field

The magnetic flux leakage method enables the detection of reinforcement bar fractures, resulting from fatigue or high tensile loading, as they may occur in bridges. An experimental measuring device was developed in a preceding project for laboratory application, enabling the evaluation of single reinforcement bars. The aim is to establish a surface measurement, which simplifies the detection of reinforcing steel breaks in cases where the exact position of the bars is unknown. The extended meas­ urement range will provide more information about the test object, such that new criteria to evaluate the condition of the reinforcement can be developed. Alternatively to the assessment by remanent magnetisation, measurements can be made using active magnetic fields. This method will be im­ proved in terms of measurement width, depth, velocity and handling, in order to develop a hand-held device for practical application.
Haploidentical transplantation outcomes for secondary acute myeloid leukemia: Acute Leukemia Working Party (ALWP) of the European Society for Blood and Marrow Transplantation (EBMT) study

Secondary acute myeloid leukemia (sAML) traditionally has inferior outcomes compared to de novo AML. Allogeneic hematopoietic cell transplantation (HCT) is the sole potentially curative therapy. This study analyzes the outcomes for unmanipulated haploidentical HCT (haploHCT) for sAML using the Acute Leukemia Working Party (ALWP) registry of the European Society for Blood and Marrow Transplantation (EBMT). We identified 154 patients with sAML who underwent haploHCT from 2006 to 2016. Median age at HCT was 60 years with time from diagnosis to HCT 5 months. At transplantation, 69 patients were in first CR and 85 had active disease. Fifty‐seven (38.0%) patients underwent myeloablative conditioning and 97 (62.0%) reduced intensity conditioning (RIC) conditioning. Multivariate analysis showed that there was no difference in RI, nonrelapse mortality (NRM), leukemia free survival (LFS), overall survival (OS), or GVHD‐free/relapse free survival (GRFS) for conditioning intensity, age, performance status, or graft source. Active disease was associated with higher RI and inferior LFS, OS, and GRFS compared with patients in CR at time of transplant. T‐cell depletion with anti‐thymoglobulin resulted in higher NRM and inferior LFS, OS, and GRFS compared to post‐transplant cyclophosphamide (PTCy) (HR 2.25, 2.01, 2.16, and 1.73, respectively with P values <.05). Our data shows that haploHCT is a feasible alternative for sAML when matched transplantation is unavailable.
Direct‐acting antiviral treatment of chronic HCV‐infected patients on opioid substitution therapy: Still a concern in clinical practice?

BACKGROUND AND AIMS There is limited real-world information on the effectiveness of antiviral treatment of chronic hepatitis C virus (HCV) infection with direct-acting antivirals (DAA) in people on opioid substitution therapy (OST). This study compared sustained virological response (SVR) rates and proportion of lost to follow-up (LTFU) between OST and non-OST patients in the German Hepatitis C-Registry (DHC-R). DESIGN National multi-centre prospective real-world registry (German Hepatitis C-Registry, DHC-R). Non-OST patients comprised patients with former/current drug use (non-OST/DU) and patients never consuming drugs (non-OST/NDU). SETTING A total of 254 medical centres in Germany, including 123 centres providing OST. PARTICIPANTS A total of 7747 chronic HCV patients started DAA therapy (739 OST and 7008 non-OST; 1500 non-OST/DU; 5508 non-OST/NDU) patients. Five hundred and twenty-eight OST and 5582 non-OST patients had completed antiviral therapy and at least one follow-up documentation [intention-to-treat (ITT) population]. MEASUREMENTS Study outcomes were SVR, proportion of LTFU and safety of treatment. FINDINGS SVR (ITT) was documented in 85% (450 of 528) OST patients versus 86% (969 of 1126) in non-OST/DU (P = 0.651) and 92% (4113 of 4456) non-OST/NDU (P < 0.001) patients. Independent predictors for SVR (P < 0.01 in multivariate analysis) included HCV genotype non-3 [adjusted odds ratio (aOR) = 1.11; 95% confidence interval (CI) = 1.07-1.15], female sex (aOR = 1.59; CI = 1.30-1.94), platelet counts >90 × 109/l (aOR = 1.51, CI = 1.14-2.01), cirrhosis (aOR = 0.77; CI = 0.62-0.96) and patient group (OST/DI (aOR = 0.58; CI = 0.42-0.78); non-OST/DU (OR: 0.63; CI = 0.50-0.78). In per-protocol analysis (PP), SVR rates were ≥ 94% in all patient groups. In OST the proportion of LTFU was higher (10.2%) than in non-OST/DU (8.5%) and non-OST/NDU (3.2%, P < 0.001) patients. Independent factors for LTFU (P < 0.01) were HCV genotype non-3 (aOR = 0.92; CI = 0.88-0.96), female sex (aOR: 0.7; CI = 0.53-0.92), pre-treatment (aOR = 0.64; CI = 0.50-0.82), OST/DI (aOR = 3.35; CI = 2.35-4.78) and non-OST/DU (aOR = 2.38; CI = 1.80-3.14). CONCLUSIONS In Germany, direct-acting antiviral treatment of former or current drug users with or without opioid substitution therapy can achieve equally high sustained virological response rates as in patients with no history of drug use.
Text Detection by Faster R-CNN with Multiple Region Proposal Networks

We propose an end-to-end consistently trainable text detection method based on the Faster R-CNN. The original Faster R-CNN is an end-to-end CNN for fast and accurate object detection. By considering the characteristics of texts, a novel architecture that make use of its ability on object detection is proposed. Although the original Faster R-CNN generates region of interests (RoIs) by a region proposal network (RPN) using the feature map of the last convolutional layer, the proposed method generates RoIs by multiple RPNs using the feature maps of multiple convolutional layers. This method uses multiresolution feature maps to detect texts of various sizes simultaneously. To aggregate the RoIs, we introduce RoI-merge layer, and this layer enables to select valid RoIs from multiple RPNs effectively. In addition, a training strategy is proposed for realizing end-to-end training and making each RPN be specialized in text region size. Experimental results using ICDAR2013/2015 RRC test dataset show that the proposed Multi-RPN method improved detection scores and kept almost the same detection speed as compared to the original Faster R-CNN and recent methods.
Chitosan and Citral Alone or in Combination For Controlling Early Blight Disease of Potato Plants Under Field Conditions.

Early blight caused by Alternaria solani is the most important disease attacking potato plants. Chitosan or Citral alone or in combinations were tested to study their effect against early blight disease of potato plants under field conditions . Different concentrations of chitosan and Citral were tested to study their inhibitory effect on linear growth of Alternaria solani in vitro . Both treatments significantly reduced the linear growth of Alternaria solani. Complete inhibition was obtained with chitosan at 5.0 g / L and Citral at 5.0 mL/ L. The highest reduction was achieved with chitosan at 4.0 g / L and Citral at 4.0 mL/ L. which reduced the linear growth by 93.3 and 95.6 % respectively. Moreover, under field conditions results indicated that chitosan and Citral alone or in combination significantly reduced the disease incidence. The highest reduction was obtained combined treatments between chitosan at 2.0 g/ L. and Citral at 4.0 or 5.0 ml / L which reduced the early blight incidence more than 76.6 and 83.3 % respectively during two growing seasons as compared with untreated plants. As for tuber yield the highest increase was obtained with combined treatments between chitosan at 2.0 g/ L. and Citral at 4.0 or 5.0 ml / L which increased the tuber yield more than 88.6 and 80.0 % during two growing seasons respectively as compared with untreated plants. These treatments also increased chitinase activity which increased the activity by 124.2 and 127.3 % respectively as compared with untreated plants. It could be suggested that using a combination treatments of chitosan and Citral may be used for controlling early blight disease of potato plants under field conditions.
Geometrical and orientation investigations on the electronic structures of elements adsorption on graphene via density functional theory

Nano-sized materials have promising contemporary and novel technological applications as they possess favourable properties due to quantum effects. The nano-sized graphene material exhibits remarkable electrical, optical, thermal and mechanical characteristics. Adding impurities or doping constitutes an effective way in fine-tuning properties of graphene for specific applications. This study aims to investigate the geometrical aspects of elements adsorption on graphene to produce more accurate models of the electronic structure of graphene as a result of the doping. Previous models investigated mainly the adsorption sites (bridge, hollow, top); however, they could not systematically explain certain phenomena, e.g. nonlinearity of band gaps to atomic ratios in oxygen-adsorbed graphene. We hypothesise that this is attributed to the positions and orientation of the adatoms (adsorbed elements) relative to one another, which is, in essence, a geometrical phenomenon. In the present study, geometrical investigations of elemental adsorption on graphene focused on side (single-, double-sided), site (bridge, hollow, top) and orientation (the position of adatom relative to one another and graphene). The computational simulations were conducted by using the generalized gradient approximation (GGA) functional within the density functional theory (DFT) framework. The VASP (Vienna Ab initio Simulation Package) software was utilised for all simulations. Trends in the elemental adsorption on graphene in terms of sides/sites/orientations are presented in terms of: binding energy (stability); migration (barrier) energy; adatom height; graphene distortion; Fermi energy; magnetization; charge transfer and energy band gap. The calculated results of 10 elements (Na, Mg, Al, Si, P, S, F, Cl, Br and I) adsorbed on pristine graphene indicate that the geometrical combination of side, site and orientation is vital in determining the most stable configuration of the adsorbed systems. This study reinforces the notion that the involvement of site/orientation of element (or functional group) is essential in future models of adsorption on graphene.
FLUORIDE RELEASE FROM THREE DIFFERENT GLASS IONOMER CEMENTS IN DE-IONISED WATER - AN IN VITRO STUDY

An vitro study was done to evaluate the release of fluoride from three different glass ionomer cements (GC 2 GOLD LABEL, KETAC MOLAR EASY MIX AND KETAC N 100 ). The release profile of the three different glass ionomer cements was studied in de-ionised water using a fluoride ion specific electrode. GC 2 GOLD LABEL showed the highest amount of fluoride release as compared to the other two materials in the first 24-48 hours . The cumulative amount of fluoride released at the end of 28 day was highest in KETAC N 100. An initial fluoride burst was seen in all the three materials. The amount of fluoride release declined at the end of two to three weeks and plateaued at the end of 28 th day.
Nutritional Status and Effect of Maternal Employment among Children Aged 6–59 Months in Wolayta Sodo Town, Southern Ethiopia: A Cross-sectional Study

Background Childhood malnutrition remains common in many parts of the world; the magnitude of worldwide stunting, underweight and wasting in children under five years of age were 24.7 %, 15.1 % and 7.8 %, respectively. More than 150 million children under the age of five years in the developing world are malnourished. Ethiopia is one of the countries in sub-Saharan Africa with the highest rates of malnutrition. In Ethiopia, 44.4% and 9.7% of children under-five years old were stunted and wasted, respectively. This study was aimed to assess nutritional status and effect of maternal employment among children aged 6–59 months. Methods A cross-sectional study was conducted in Wolayta Sodo Town, Southern Ethiopia. Socio-demographic characteristics, child feeding and healthcare seeking practice of mothers, and child's anthropometric status were assessed. Probability proportional to size sampling approach was used to select a sample of 316 mothers having children aged 6–59 months. The study was ethically approved by Institutional Review Board of Health Science College, Hawasa University. Result The overall result revealed that the prevalence of stunting was 22.2%, of which 21.8% and 22.6% were in children of employed and unemployed mothers, respectively. Low-weight-for age was 10.8% for children of employed mothers and 13.4% for children of unemployed mothers. Wasting was 8.8% and 10.8% for children of employed and unemployed mothers, respectively. There was no statistically significant association between maternal employment and nutritional status of their children. However, chronic malnutrition (stunting) was influenced by being educated mother (OR: 0.37) child age group of 24–59 months (OR: 0.36) and households' fifth wealth quintile (OR: 0.28). Conclusion Low prevalence of stunting was observed. Stunting is a public health concern in the study area. Furthermore, stunting is significantly influenced by mothers' education, household wealth and child age. However, maternal employment was not statistically associated with child nutritional status. Thus, nutritional intervention initiatives should focus on improving household food security, maternal education and agricultural diversification.
Modified Bacteriophage S16 Long Tail Fiber Proteins for Rapid and Specific Immobilization and Detection of Salmonella Cells

ABSTRACT Bacteriophage-based assays and biosensors rival traditional antibody-based immunoassays for detection of low-level Salmonella contaminations. In this study, we harnessed the binding specificity of the long tail fiber (LTF) from bacteriophage S16 as an affinity molecule for the immobilization, enrichment, and detection of Salmonella. We demonstrate that paramagnetic beads (MBs) coated with recombinant gp37-gp38 LTF complexes (LTF-MBs) are highly effective tools for rapid affinity magnetic separation and enrichment of Salmonella. Within 45 min, the LTF-MBs consistently captured over 95% of Salmonella enterica serovar Typhimurium cells from suspensions containing from 10 to 105 CFU · ml−1, and they yielded equivalent recovery rates (93% ± 5%, n = 10) for other Salmonella strains tested. LTF-MBs also captured Salmonella cells from various food sample preenrichments, allowing the detection of initial contaminations of 1 to 10 CFU per 25 g or ml. While plating of bead-captured cells allowed ultrasensitive but time-consuming detection, the integration of LTF-based enrichment into a sandwich assay with horseradish peroxidase-conjugated LTF (HRP-LTF) as a detection probe produced a rapid and easy-to-use Salmonella detection assay. The novel enzyme-linked LTF assay (ELLTA) uses HRP-LTF to label bead-captured Salmonella cells for subsequent identification by HRP-catalyzed conversion of chromogenic 3,3′,5,5′-tetramethylbenzidine substrate. The color development was proportional for Salmonella concentrations between 102 and 107 CFU · ml−1 as determined by spectrophotometric quantification. The ELLTA assay took 2 h to complete and detected as few as 102 CFU · ml−1S. Typhimurium cells. It positively identified 21 different Salmonella strains, with no cross-reactivity for other bacteria. In conclusion, the phage-based ELLTA represents a rapid, sensitive, and specific diagnostic assay that appears to be superior to other currently available tests. IMPORTANCE The incidence of foodborne diseases has increased over the years, resulting in major global public health issues. Conventional methods for pathogen detection can be laborious and expensive, and they require lengthy preenrichment steps. Rapid enrichment-based diagnostic assays, such as immunomagnetic separation, can reduce detection times while also remaining sensitive and specific. A critical component in these tests is implementing affinity molecules that retain the ability to specifically capture target pathogens over a wide range of in situ applications. The protein complex that forms the distal tip of the bacteriophage S16 long tail fiber is shown here to represent a highly sensitive affinity molecule for the specific enrichment and detection of Salmonella. Phage-encoded long tail fibers have huge potential for development as novel affinity molecules for robust and specific diagnostics of a vast spectrum of bacteria.
TK1 overexpression is associated with the poor outcomes of lung cancer patients: a systematic review and meta-analysis.

AIM The study aimed to unveil the effect of TK1 expression on the clinicopathological significance and prognosis in patients with lung cancer. Results & methodology: Studies for meta-analysis were selected according to a thorough literature search in databases (PubMed, EMBASE and Chinese databases). Ten studies containing 1393 lung cancer patients were investigated in our analysis. The TK1 overexpression was associated with poorer overall survival(OS) in lung cancer patients (hazard ratio = 1.881; 95% CI:1.318-2.684, Z = 3.48; p = 0.001). Furthermore, The TK1 expression is associated with the clinicopathological features of lung cancer patients (tumor type, age, lymph node metastasis, distant metastasis and tumor, node, metastasis [TNM] stages). Discussion & conclusion: The TK1 expression might have a supportive implication in assessing biological behavior and prognosis of lung cancer patients.
Model-Driven Domain-Specific Middleware

Middleware was introduced to facilitate the development of sophisticated applications based on a uniform methodology and industry standards. However, early research and practice suggested that no one-size-fits-all approach was suitable for all application domains and scenarios. This gave rise to industry initiatives to standardize domain-specific middleware services and profiles, as well as research efforts on configurable, reflective, and adaptive middleware. The industry's approach led to easy deployment, although with a level of flexibility limited by the extent of existing profiles. The approach of the research community, on the other hand, enabled high flexibility, allowing any middleware configuration to be defined. Nevertheless, creating sound configurations using this approach is a challenging task, limiting the target audience to expert engineers. As a consequence, both initiatives do not scale with the current proliferation of specialized application domains. In this paper, we target this problem with an approach that leverages model-driven engineering for the construction of domain-specific middleware platforms. A set of high-level, yet expressive, building blocks is defined in the form of a metamodel, which is used to create models that specify the desired middleware configuration. We argue that this approach enables the rapid development of middleware platforms to match the proliferation of application domains, at the same time as it does not require per-application middleware construction or even highly skilled middleware engineers. We present the current state of our research and discuss research directions to fully realize the approach.
Deficiency of transcription factor RelB perturbs myeloid and DC development by hematopoietic-extrinsic mechanisms

Significance The transcription factor RelB has been thought to be required for dendritic cell (DC) development, although analysis of radiation bone marrow chimeras has raised some questions regarding this issue that have never been resolved. We have reevaluated the role of RelB in DC and myeloid development. We found that DC development was independent of a cell-intrinsic action of RelB in most tissues and that only the terminal maturation of Notch2-dependent splenic cDC2 cells was partially reduced in the absence of cell-intrinsic RelB expression. Moreover, the profound myeloid expansion seen in Relb−/− mice was due to an unrecognized action of RelB in nonhematopoietic cells, indicating that RelB is a critical component of the niche regulating the normal myeloid compartment. RelB is an NF-κB family transcription factor activated in the noncanonical pathway downstream of NF-κB–inducing kinase (NIK) and TNF receptor family members including lymphotoxin-β receptor (LTβR) and CD40. Early analysis suggested that RelB is required for classical dendritic cell (cDC) development based on a severe reduction of cDCs in Relb−/− mice associated with profound myeloid expansion and perturbations in B and T cells. Subsequent analysis of radiation chimeras generated from wild-type and Relb−/− bone marrow showed that RelB exerts cell-extrinsic actions on some lineages, but it has remained unclear whether the impact of RelB on cDC development is cell-intrinsic or -extrinsic. Here, we reevaluated the role of RelB in cDC and myeloid development using a series of radiation chimeras. We found that there was no cell-intrinsic requirement for RelB for development of most cDC subsets, except for the Notch2- and LTβR-dependent subset of splenic CD4+ cDC2s. These results identify a relatively restricted role of RelB in DC development. Moreover, the myeloid expansion in Relb−/− mice resulted from hematopoietic-extrinsic actions of RelB. This result suggests that there is an unrecognized but critical role for RelB within the nonhematopoietic niche that controls normal myelopoiesis.
Delayed Impact of Fair Machine Learning

Static classification has been the predominant focus of the study of fairness in machine learning. While most models do not consider how decisions change populations over time, it is conventional wisdom that fairness criteria promote the long-term well-being of groups they aim to protect. This work studies the interaction of static fairness criteria with temporal indicators of well-being. We show a simple one-step feedback model in which common criteria do not generally promote improvement over time, and may in fact cause harm. Our results highlight the importance of temporal modeling in the evaluation of fairness criteria, suggesting a range of new challenges and trade-offs.
Smoke Detection Model Based on Adaptive Feature Extraction Network

Efficient detection of smoke plays a critical role in preventing and suppressing fires. However, smoke is generally of variable shapes and colors, blurred borders, and irregular textures, which makes smoke detection based on deep learning a challenging task. Aiming at this problem, a smoke detection adaptive deep model named DB-YOLO is proposed. In the model, Spatial attention-based Dynamic Convolution kernel (SDConv) is designed and embedded as a feature extraction block to improve the ability of extracting representative features from images of diverse textures. Besides, an improved Bi-directional Feature Pyramid Network (BiFPN) is integrated as a feature fusion block to fuse multi-scale features. Results show that mAP@0.5 of the DB-YOLO can increase by 6.08% to 14.40% in smoke dataset compared to currently popular object detection models.