ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Stopping power accuracy and achievable spatial resolution of helium ion imaging using a prototype particle CT detector system

A precise relative stopping power map of the patient is crucial for accurate particle therapy. Charged particle imaging determines the stopping power either tomographically - particle computed tomography (pCT) - or by combining prior knowledge from particle radiography (pRad) and x-ray CT. Generally, multiple Coulomb scattering limits the spatial resolution. Compared to protons, heavier particles scatter less due to their lower charge/mass ratio. A theoretical framework to predict the most likely trajectory of particles in matter was developed for light ions up to carbon and was found to be the most accurate for helium comparing for fixed initial velocity. To further investigate the potential of helium in particle imaging, helium computed tomography (HeCT) and radiography (HeRad) were studied at the Heidelberg Ion-Beam Therapy Centre (HIT) using a prototype pCT detector system registering individual particles, originally developed by the U.S. pCT collaboration. Several phantoms were investigated: modules of the Catphan QA phantom for analysis of spatial resolution and achievable stopping power accuracy, a paediatric head phantom (CIRS) and a custommade phantom comprised of animal meat enclosed in a 2 % agarose mixture representing human tissue. The pCT images were reconstructed applying the CARP iterative reconstruction algorithm. The MTF10% was investigated using a sharp edge gradient technique. HeRad provides a spatial resolution above that of protons (MTF1010%=6.07 lp/cm for HeRad versus MTF10%=3.35 lp/cm for proton radiography). For HeCT, the spatial resolution was limited by the number of projections acquired (90 projections for a full scan). The RSP accuracy for all inserts of the Catphan CTP404 module was found to be 2.5% or better and is subject to further optimisation. In conclusion, helium imaging appears to offer higher spatial resolution compared to proton imaging. In future studies, the advantage of helium imaging compared to other imaging modalities in clinical applications will be further explored.
Households' Assets Dynamics and Ecotourism Choices in the Western Highlands of Cameroon

Ecotourism is increasingly accepted as a suitable alternative for sustaining rural livelihoods. In spite of this trend, quantitative assessments of relationships between household assets and ecotourism choices, and the policy implications thereof, currently account for only a negligible number of studies in sub-Saharan Africa. This paper contributes to this evidence gap by analyzing the extent to which households' assets drive ecotourism choices on a representative sample of 200 households in Cameroon. The Principal Component Analysis (PCA) and the Human Development Index (HDI) were used to construct indices for ecotourism choices. The ordinary least square and logit models were also employed to estimate the effect of various household assets on ecotourism choices. A high preference was observed for the production and sale of arts and crafts items and the promotion of cultural heritage sites as key ecotourism choices. More women are found to participate in conservation education, as opposed to culture-related activities such as arts and crafts. Access to education and training were inversely related to cultural festival promotion. The results suggest the need to: (i) stem the overdependence on conservation sites for wood supply to the arts and crafts sector, (ii) enforce endogenous cultural institutional regulations, including those that increase female participation in guiding future ecotourism choices. This paper contributes to ecotourism development and conservation theory, with regards to unbundling household level predictors of ecotourism choices, and has implications on the design of policies to implement environmentally less-demanding ecotourism activities.
Safety of Magnetic Resonance Imaging After Implantation of Stainless Steel Embolization Coils

Stainless steel embolization coils (SSEC) have been used for over four decades for vascular occlusion. Recently, the safety of these coils in a magnetic resonance environment has been called into question, with important ramifications for thousands of patients with existing coils in place. We performed a retrospective chart review at five tertiary care pediatric centers evaluating all children and young adults with implanted SSEC who underwent magnetic resonance imaging (MRI). Data reviewed included demographics, coil implantation, MRI studies, and follow-up evaluations. Complications such as heating, discomfort, or device migration were specifically sought. Two hundred and ninety-seven patients with implanted SSEC underwent 539 MRI examinations. The median age at SSEC implantation was 2.3 years (1 week-23.2 years). The MRI studies were performed a median of 7.4 years (4 days-23.1 years) after implantation. No patients experienced any reported complications associated with their MRI examinations during the study or at median follow-up post-MRI of 4.8 years (1 day-23 years). In this large, retrospective review of patients with implanted SSEC undergoing MRI, there were no reported adverse events. These findings support the recent change by Cook Medical Inc. of their standard embolization coils from a designation of magnetic resonance unsafe to conditional.
Motion Correlation Discovery for Visual Tracking

Motion information plays an important role in identifying moving objects, which has not been well utilized in state of-the-art tracking algorithms. In this letter, we propose a unified framework integrating two tracking problems, i.e., pixel-level foreground probabilistic inference and motion parameter estimation. Our model employs motion fields to propagate probability forward, and discovers motion patterns in the spatial domain to distinguish targets from the background. It takes advantage of continuity and inertia of both target and camera motion, and provides reliable evidence to resolve confusion caused by appearance similarity between targets and the background. Target localization is effectively achieved from the pixel-level foreground probabilistic map. Experimental results demonstrate that the proposed method significantly improves our baseline method, and achieves performance comparable to state-of-the-art tracking methods with more complex features.
The AIM Photonics MPW: A Highly Accessible Cutting Edge Technology for Rapid Prototyping of Photonic Integrated Circuits

Silicon photonics has been heralded for a number of high technology fields, but access to a high quality technology has been limited to vertically integrated design/fabrication companies, or fabless companies with significant resources to engage high volume fabs. More recently, research and development hubs have developed and released process design kits and multi-project wafer programs to lower the barrier. We present the first silicon photonics multi-project wafer (MPW) service produced in a state-of-the-art 300 mm fabrication facility. The MPW service is enabled by a best-in-class process design kit (PDK) which allows designers to layout and obtain photonic integrated circuits (PICs) that work properly on the first run. The fabrication of these circuits is carried out at the SUNY Polytechnic Institute which operates a world class 300 mm cleanroom that, besides silicon photonics, develops sub-7 nm CMOS architectures. The industrial-level management of this facility and its equipment provides high quality photonic devices which are repeatable from run-to-run along with rapid turnaround time. The devices that are available to designers via the process design kit are produced by Analog Photonics and have been verified on actual runs. The performance of these devices is comparable to the state-of-the-art and enables a wide variety of silicon photonic applications.
A novel agonist for the HGF receptor MET promotes differentiation of human pluripotent stem cells into hepatocyte-like cells

Hepatocyte growth factor (HGF) is the natural ligand of the MET receptor tyrosine kinase. This ligand-receptor couple is essential for the maturation process of hepatocytes. Previously, the rational design of a synthetic protein based on the assembly of two K1 domains from HGF led to the production of a potent and stable MET receptor agonist. In this study, we compared the effects of K1K1 with HGF during the differentiation of hepatocyte progenitors derived from human induced pluripotent stem cells (hiPSCs). In vitro, K1K1, in the range of 20 to 200 nM, successfully substituted for HGF and efficiently activated ERK downstream signaling. Analysis of the levels of hepatocyte markers showed typical liver mRNA and protein expression (HNF4α, albumin, alpha-fetoprotein, CYP3A4) and phenotypes. Although full maturation was not achieved, the results suggest that K1K1 is an attractive candidate MET agonist suitable for replacing complex and expensive HGF treatments to induce hepatic differentiation of hiPSCs.
Transformer-Based Model for Electrical Load Forecasting

Amongst energy-related CO2 emissions, electricity is the largest single contributor, and with the proliferation of electric vehicles and other developments, energy use is expected to increase. Load forecasting is essential for combating these issues as it balances demand and production and contributes to energy management. Current state-of-the-art solutions such as recurrent neural networks (RNNs) and sequence-to-sequence algorithms (Seq2Seq) are highly accurate, but most studies examine them on a single data stream. On the other hand, in natural language processing (NLP), transformer architecture has become the dominant technique, outperforming RNN and Seq2Seq algorithms while also allowing parallelization. Consequently, this paper proposes a transformer-based architecture for load forecasting by modifying the NLP transformer workflow, adding N-space transformation, and designing a novel technique for handling contextual features. Moreover, in contrast to most load forecasting studies, we evaluate the proposed solution on different data streams under various forecasting horizons and input window lengths in order to ensure result reproducibility. Results show that the proposed approach successfully handles time series with contextual data and outperforms the state-of-the-art Seq2Seq models.
Comparison of bacterial diversity in full scale anammox bioreactors operated under different conditions

Bacterial community structure of full-scale anammox bioreactor is still mainly unknown. It has never been analyzed whether different anammox bioreactor configurations might result in the development of different bacterial community structures among these systems. In this work, the bacterial community structure of six full-scale autotrophic nitrogen removal bioreactors located in The Netherlands and China operating under three different technologies and with different influent wastewater characteristics was studied by the means of pyrotag sequencing evaluation of the bacterial assemblage yielded a great diversity in all systems. The most represented phyla were the Bacteroidetes and the Proteobacteria, followed by the Planctomycetes. 14 OTUs were shared by all bioreactors, but none of them belonged to the Brocadiales order. Statistical analysis at OTU level showed that differences in the microbial communities were high, and that the main driver of the bacterial assemblage composition was different for the distinct phyla identified in the six bioreactors, depending on bioreactor technology or influent wastewater characteristics.
Estimating the onset of spring from a complex phenology database: trade-offs across geographic scales

Phenology is an important indicator of ecological response to climate change. Yet, phenological responses are highly variable among species and biogeographic regions. Recent monitoring initiatives have generated large phenological datasets comprised of observations from both professionals and volunteers. Because the observation frequency is often variable, there is uncertainty associated with estimating the timing of phenological activity. "Status monitoring" is an approach that focuses on recording observations throughout the full development of life cycle stages rather than only first dates in order to quantify uncertainty in generating phenological metrics, such as onset dates or duration. However, methods for using status data and calculating phenological metrics are not standardized. To understand how data selection criteria affect onset estimates of springtime leaf-out, we used status-based monitoring data curated by the USA National Phenology Network for 11 deciduous tree species in the eastern USA between 2009 and 2013. We asked, (1) How are estimates of the date of leaf-out onset, at the site and regional levels, influenced by different data selection criteria and methods for calculating onset, and (2) at the regional level, how does the timing of leaf-out relate to springtime minimum temperatures across latitudes and species? Results indicate that, to answer research questions at site to landscape levels, data users may need to apply more restrictive data selection criteria to increase confidence in calculating phenological metrics. However, when answering questions at the regional level, such as when investigating spatiotemporal patterns across a latitudinal gradient, there is low risk of acquiring erroneous results by maximizing sample size when using status-derived phenological data.
Surface similarity parameter: A new machine learning loss metric for oscillatory spatio-temporal data

Supervised machine learning approaches require the formulation of a loss functional to be minimized in the training phase. Sequential data are ubiquitous across many fields of research, and are often treated with Euclidean distance-based loss functions that were designed for tabular data. For smooth oscillatory data, those conventional approaches lack the ability to penalize amplitude, frequency and phase prediction errors at the same time, and tend to be biased towards amplitude errors. We introduce the surface similarity parameter (SSP) as a novel loss function that is especially useful for training machine learning models on smooth oscillatory sequences. Our extensive experiments on chaotic spatio-temporal dynamical systems indicate that the SSP is beneficial for shaping gradients, thereby accelerating the training process, reducing the final prediction error, increasing weight initialization robustness, and implementing a stronger regularization effect compared to using classical loss functions. The results indicate the potential of the novel loss metric particularly for highly complex and chaotic data, such as data stemming from the nonlinear two-dimensional Kuramoto-Sivashinsky equation and the linear propagation of dispersive surface gravity waves in fluids.
Bacterial catabolism of acetovanillone, a lignin-derived compound

Bacterial catabolic pathways have considerable potential as industrial biocatalysts for the valorization of lignin, a major component of plant-derived biomass. Here, we describe a pathway responsible for the catabolism of acetovanillone, a major component of several industrial lignin streams. Rhodococcus rhodochrous GD02 was previously isolated for growth on acetovanillone. A high-quality genome sequence of GD02 was generated. Transcriptomic analyses revealed a cluster of eight genes up-regulated during growth on acetovanillone and 4-hydroxyacetophenone, as well as a two-gene cluster up-regulated during growth on acetophenone. Bioinformatic analyses predicted that the hydroxyphenylethanone (Hpe) pathway proceeds via phosphorylation and carboxylation, before β-elimination yields vanillate from acetovanillone or 4-hydroxybenzoate from 4-hydroxyacetophenone. Consistent with this prediction, the kinase, HpeHI, phosphorylated acetovanillone and 4-hydroxyacetophenone. Furthermore, HpeCBA, a biotin-dependent enzyme, catalyzed the ATP-dependent carboxylation of 4-phospho-acetovanillone but not acetovanillone. The carboxylase's specificity for 4-phospho-acetophenone (kcat/KM = 34 ± 2 mM-1 s-1) was approximately an order of magnitude higher than for 4-phospho-acetovanillone. HpeD catalyzed the efficient dephosphorylation of the carboxylated products. GD02 grew on a preparation of pine lignin produced by oxidative catalytic fractionation, depleting all of the acetovanillone, vanillin, and vanillate. Genomic and metagenomic searches indicated that the Hpe pathway occurs in a relatively small number of bacteria. This study facilitates the design of bacterial strains for biocatalytic applications by identifying a pathway for the degradation of acetovanillone.
Interpretable intrusion detection for next generation of Internet of Things

This paper presents a new framework for intrusion detection in the next-generation Internet of Things. MinMax normalization strategy is used to collect and preprocess data. The Marine Predator algorithm is then used to select relevant features to be used in the learning process. The selected features are then trained with an advanced and state-of-the-art recurrent neural network that includes an attention mechanism. Finally, Shapely values are calculated to determine how much each feature contributes to the final output. The dataset NSL-KDD was used for intensive simulations. The results show the advantages of the proposed system as well as its superiority over state-of-the-art methods. In fact, the proposed solution achieved a rate of more than 94% for both true negative and true position, while the rates of the existing solutions are below 90% for the challenging NSL-KDD datasets.
Photophysical and Fluorescence Nitroaromatic Sensing Properties of Methylated Derivative of a Pamoic Acid Ester

Rapid and selective detection of nitroaromatic explosives is very important for public safety, life, and environmental health. Current instrumental techniques suffer from high cost and poor site used. In order to investigate fluorescence sensing of nitroaromatics, we prepare a new small fluorescence probe derived from pamoic acid. This study covers the synthesis of Pamoic acid based [diisopropyl 4,4'-methylenebis(3-methoxy-2-naphthoate)] (2) material and characterization of its structure. The methylation of Pamoic acid ester, which we have successfully synthesized in our previous studies, was carried out in this study. Determination of the photophysical and fluorescent nitroaromatic detection properties of the compound forms the basis of the study. Structural characterization of the synthesized compound [diisopropyl 4,4'-methylenebis(3-methoxy-2-naphthoate)] (2) was characterized using spectroscopic methods. In addition, Molecular structure of the synthesized compound was determined by single crystal X-ray diffraction studies. In the final step, compounds [diisopropyl 4,4'-methylenebis(3-hydroxy-2-naphthoate)] (1) and [diisopropyl 4,4'-methylenebis(3-methoxy-2-naphthoate)] (2) were tested as fluorescent probes for the detection of some nitroaromatic explosives. It is seen that Nitrobenzene provides the best quenching effect on the compound [diisopropyl 4,4'-methylenebis(3-hydroxy-2-naphthoate)] (1) containing the -OH group, with lowest the limit of detection (LOD) value. It was observed that Picric acid provided the best quenching effect with lowest the limit of detection (LOD) value in the compound [diisopropyl 4,4'-methylenebis(3-methoxy-2-naphthoate)] (2) obtained by methylation of the -OH group in the compound [diisopropyl 4,4'-methylenebis(3-hydroxy-2-naphthoate)] (1).
Surgery of extrahepatic bile duct cancer - current evidence and recommendations

Extrahepatic cholangiocarcinoma is a rare disease with poor prognosis, requiring comprehensive multidisciplinary management. Only radical resection gives hope for long-term survival. Most patients have either an unresectable disease or their condition does not allow for radical surgery. The method of choice for resectable perihilar cholangiocarcinoma is en-block liver resection including the extrahepatic bile duct, or pancreatoduodenectomy for distal cholangiocarcinoma. Hepatopancreatoduodenectomy can be performed in selected patients if the entire hepato-choledochus is affected. Liver transplantation after neoadjuvant treatment can be also considered in highly selected patients with unresectable perihilar cholangiocarcinoma. These procedures are technically demanding, are associated with high morbidity and relevant mortality, and must be concentrated in tertiary hepatobiliary centers. Preoperative optimization (bile duct drainage, nutrition, portal venous embolization, etc.) plays a crucial role in reducing postoperative morbidity and mortality.
Securing a wireless world

Securing wireless networks poses unique research challenges. In this paper, we survey the state-of-the-art approaches to providing security for three popular wireless networking paradigms, namely, IEEE 802.11 based WLANs, third-gene ration cellular networks, and mobile ad hoe networks. We identify the security threats as well as examine the current solutions. We further summarize lessons learned, discuss open issues, and identify future research directions.
X-Ray Scatter Estimation Using Deep Splines

X-ray scatter compensation is a very desirable technique in flat-panel X-ray imaging and cone-beam computed tomography. State-of-the-art U-net based scatter removal approaches yielded promising results. However, as there are no physics' constraints applied to the output of the U-Net, it cannot be ruled out that it yields spurious results. Unfortunately, in the context of medical imaging, those may be misleading and could lead to wrong conclusions. To overcome this problem, we propose to embed B-splines as a known operator into neural networks. This inherently constrains their predictions to well-behaved and smooth functions. In a study using synthetic head and thorax data as well as real thorax phantom data, we found that our approach performed on par with U-net when comparing both algorithms based on quantitative performance metrics. However, our approach not only reduces runtime and parameter complexity, but we also found it much more robust to unseen noise levels. While the U-net responded with visible artifacts, the proposed approach preserved the X-ray signal's frequency characteristics.
Hydrothermal synthesis of PVP-passivated clove bud-derived carbon dots for antioxidant, catalysis, and cellular imaging applications

In recent times, carbon dots (CDs) are emerging for numerous interdisciplinary applications by modulating their inherent chemical functionality during or post-synthesis modification. The current study reports the hydrothermal synthesis of polyvinylpyrrolidone K-30 (PVP) passivated clove bud-derived carbon dots (PPCCDs) for multifaceted applications. The adopted technique is facile and environmentally friendly for the production of CDs with in situ PVP passivation. Physicochemical characterization of CDs is performed using various spectroscopic and microscopic techniques. The study reveals the formation of nitrogen-doped spherical PPCCDs with an average hydrodynamic size of ∼ 4.9 nm. It is also evident that there is modulation in optical properties and quantum efficiency as a result of PVP passivation. The study further demonstrates their suitability in biological environments as observed by pH stability, photostability, and cytocompatibility results. PPCCDs have shown significant antioxidant activity against DPPH (EC50: 57 µg/mL), suppression of superoxide anion radical (EC50: 53 µg/mL), and an efficient catalytic activity towards degradation of Rhodamine-B (Rh-B) dye. UV-Visible spectroscopy unveil the reaction mechanism during antioxidant and catalytic activities of CDs that are validated by Electron paramagnetic resonance (EPR) spectroscopy with an indication of effective electron or proton donating abilities. Its bioimaging potential is evidenced through cellular fluorescence imaging with 3T3 and L929 cell lines.