Miracle-dz/UniFAR-FTUs huggingface dataset:
A structural study into halogenated derivatives of mandelic acid as building blocks of chiral coordination polymers

Abstract Mandelic acid and its derivatives are an excellent source of chirality for the construction of chiral coordination polymers (CPs) and metal-organic frameworks (MOFs) for enantioselective applications. To date, limited reports exist for the incorporation of mandelic acid derivatives with halogen substituents such as fluorine and chlorine despite the extra intermolecular interactions possible. The extra sites for hydrogen and halogen bonding in these mandelic acid derivatives may afford interesting modes of coordination and packing in 3 D space. Six CPs containing mandelic acid and its halogenated analogues, (R)-2-chloromandelic acid, 3,5-difluoromandelic acid, 4-trifluoromethylmandelic acid, together with linear dipyridyl co-ligands are reported. These structures consist of three 2 D sql sheets and three 1 D chains with a range of packing motifs influenced by the differing intermolecular interactions present. Graphical Abstract
Students Act as 21st Century Preventive-Pandemic-COVID-19 Model: Improved Advance-Clinical-Toxicology Biomedicine Green-Socio-Economy Science-Technology-Innovations

The pandemic-COVID-19 adverse effects on the environment, travel, education and clinical research, and the global health of humans and animals, and the impact on human-civilization, agriculture, global socio-economy, and damage brain-tissue or long term neurological-disorder, with more than 88-million infections and more than 1.8-million death of human lives. Recently the application of vaccine starts, but its proper efficacy, longevity, cost-effectiveness, allergic-toxic-reaction, and chance of reinfection due to new variant and mutation, are not still known. Though the middle-and upper-classes are able to tackle, but the economically poor-households, the marginalized in the Purba Bardhaman district, and groups like senior-citizens and street-children and animals, are badly affected still now. So in this paper students act as a 21st-century preventive-pandemicCOVID-19 model, improving advanced-clinical-toxicology, biomedicines, green-socio-economy, and science-technologyinnovations-communication by boosting community immunity or herd-immunity, and developing policy-initiative social strategies issues, removing the adverse effects of chemicals on living organisms and clinical studies in all areas of toxicology. This paper is considered the possible pathway of future pandemic COVID-19 like’s virus-free world.
Implementation of analytical fatigue models into opensim to predict the effects of fatigue on anterior cruciate ligament loading

IMPLEMENTATION OF ANALYTICAL FATIGUE MODELS INTO OPENSIM TO PREDICT THE EFFECTS OF FATIGUE ON ANTERIOR CRUCIATE LIGAMENT LOADING Michael A. Samaan Old Dominion University, 2014 Director: Stacie I. Ringleb Co-Director: Sebastian Y. Bawab The anterior cruciate ligament (ACL) provides stability to the knee joint while performing activities such as a side step cut. Neuromuscular fatigue, a reduction in muscle force producing capabilities, alters lower extremity mechanics while performing a side step cut and may increase the risk o f ACL injury, particularly in females. Musculoskeletal modeling allows for the measurement o f muscle forces, which are difficult to measure in-vivo. Therefore, musculoskeletal modeling, may improve our understanding o f the effects o f neuromuscular fatigue on muscle force production and loading o f the ACL. Therefore, the purpose o f this study was to develop a musculoskeletal model which incorporated two analytical fatigue models by Tang et al (2005) and Xia et al (2008). These fatigue models were used to determine the effects of neuromuscular fatigue on muscle force production and ACL loading at various levels of fatigue (i.e. 10%, 25%, 50%, 75% and 90%) and were validated by comparing these results with experimental data. Six recreationally active females performed five anticipated side step cuts both before and after an isolated hamstrings fatigue protocol using the right lower extremity. Root mean square (RMS) differences were calculated between both fatigue models and the experimental hamstrings muscle force 1.91 N k g '1 and 1.88 N k g 1, for RMSjang and RM Sxia, respectively. Despite similar R M S differences, the Xia el al (2008) model was selected for analysis o f fatigue as this model utilized general input parameters. The total quadriceps and hamstrings muscle forces demonstrated significant decreases (p<0.05) as an effect o f fatigue yet the gastrocnemius muscle forces increased (p<0.05). Knee joint extension moment demonstrated significant increases (p<0.05) across all fatigue levels. Despite a reduction in hamstrings muscle force producing capabilities, peak ACL loading did not exhibit a significant increase (p>0.05) due to fatigue. The limited number o f participants in this study suggested an underpowered study and may help explain the lack of significance in various dependent variables including peak ACL loading. Using the model developed in this study can aid researchers in understanding the effects o f fatigue on risk o f ACL injury in order to develop better training programs in order to reduce the risk o f injury. This dissertation is dedicated to my fiancee Erica Helms and my parents Aida and Samaan Samaan. Thank you all for your support, love and guidance.
New Strategies for Accelerated Spatial Encoding with Quadratic Fields in Magnetic Resonance Imaging

New Strategies for Accelerated Spatial Encoding with Quadratic Fields in Magnetic Resonance Imaging Jason Peter Stockmann 2012 Spatial encoding with nonlinear magnetic fields has recently drawn attention for its potential to achieve faster gradient field switching within safety limits, tailored resolution in regions of interest, and improved parallel imaging using encoding fields that complement the sensitivity profiles of RF receive arrays. Proposed methods can broadly be divided into those that employ phase encoding (PatLoc and COGNAC) and those that acquire nonlinear projections (O-Space, Null Space imaging, and 4D-RIO). Projection methods typically reconstruct images using iterative algorithms to backproject the data by exploiting the full encoding matrix. For this reason, they are more sensitive than phase encoding methods to systematic errors introduced by imperfect knowledge of the encoding trajectory. In the present work, voxel-wise phase evolution is mapped at each acquired point in an O-Space trajectory using a variant of chemical shift imaging, capturing all spin dynamics caused by encoding fields, eddy currents, and pulse timing. Phase map calibration is then applied to data acquired from a high-power, 12 cm, Z2 insert coil with a home-built 8-channel RF transmit-receive array on a 3T human scanner. We show the first experimental proof-of-concept O-Space images on in vivo and phantom samples, paving the way for more in-depth exploration of O-Space and other nonlinear projection imaging methods. We also use quadratic phase preparation with a Cartesian pulse sequence to image form a localized field-of-view within the sample. This extends a previously presented method (“GradLoc”) by creating localization with a 3-D encoding field and also by combining it with parallel imaging for scan acceleration.
Long‐term cattle grazing shifts the ecological state of forest soils

Abstract Cattle grazing profoundly affects abiotic and biotic characteristics of ecosystems. While most research has been performed on grasslands, the effect of large managed ungulates on forest ecosystems has largely been neglected. Compared to a baseline seminatural state, we investigated how long‐term cattle grazing of birch forest patches affected the abiotic state and the ecological community (microbes and invertebrates) of the soil subsystem. Grazing strongly modified the soil abiotic environment by increasing phosphorus content, pH, and bulk density, while reducing the C:N ratio. The reduced C:N ratio was strongly associated with a lower microbial biomass, mainly caused by a reduction of fungal biomass. This was linked to a decrease in fungivorous nematode abundance and the nematode channel index, indicating a relative uplift in the importance of the bacterial energy‐channel in the nematode assemblages. Cattle grazing highly modified invertebrate community composition producing distinct assemblages from the seminatural situation. Richness and abundance of microarthropods was consistently reduced by grazing (excepting collembolan richness) and grazing‐associated changes in soil pH, Olsen P, and reduced soil pore volume (bulk density) limiting niche space and refuge from physical disturbance. Anecic earthworm species predominated in grazed patches, but were absent from ungrazed forest, and may benefit from manure inputs, while their deep vertical burrowing behavior protects them from physical disturbance. Perturbation of birch forest habitat by long‐term ungulate grazing profoundly modified soil biodiversity, either directly through increased physical disturbance and manure input or indirectly by modifying soil abiotic conditions. Comparative analyses revealed the ecosystem engineering potential of large ungulate grazers in forest systems through major shifts in the composition and structure of microbial and invertebrate assemblages, including the potential for reduced energy flow through the fungal decomposition pathway. The precise consequences for species trophic interactions and biodiversity–ecosystem function relationships remain to be established, however.
A Review on Feature Selection Techniques for Sentiment Analysis

Sentiment Analysis is the technique of identifying and categorizing emotions in order to examine how people feel about services such as movies, products, events, and politics. It is a widely researched on topic in text mining. This paper presents a review and evaluation results for some feature selection techniques such as TF- IDF, document frequency, word frequency, sparsity reduction and chi square statistics. To test these feature selection techniques, the study used twitter data on stock market and Naïve Bayes Classifier for classification because of its computational simplicity and effectiveness. The implementation of the study has been done in R.
Developments of frequency comb microwave reflectometer for the interchange mode observations in LHD plasma

We have upgraded the multi-channel microwave reflectometer system which uses a frequency comb as a source and measure the distribution of the density fluctuation caused by magneto-hydro dynamics instability. The previous multi-channel system was composed of the Ka-band, and the U-band system has been developed. Currently, the U-band system has eight frequency channels, which are 43.0, 45.0, 47.0, 49.0, 51.0, 53.0, 55.0, and 57.0 GHz, in U-band. Before the installation to the Large Helical Device (LHD), several tests for understanding the system characteristics, which are the phase responsibility, the linearity of output signal, and others, have been carried out. The in situ calibration in LHD has been done for the cross reference. In the neutral beam injected plasma experiments, we can observe the density fluctuation of the interchange mode and obtain the radial distribution of fluctuation amplitude.
Update on techniques for cryopreservation of human spermatozoa

In the 1960s, sperm cryopreservation was developed as a method to preserve fertility. Currently, techniques for the cryopreservation of human spermatozoa have been widely used in assisted reproduction. However, although sperm cryobiology has made notable achievements, the optimal method for the recovery of viable spermatozoa after cryopreservation remains elusive. Postthawing sperm quality can be affected by cryoprotectants, ice formation, storage conditions, and osmotic stress during the freezing process. This review discusses recent advances in different cryopreservation techniques, cryoprotectants, and freezing and thawing methods during cryopreservation and new indications for the use of cryopreserved spermatozoa.
Fusion of multiple deep convolutional neural networks (DCNNs) for improved segmentation of lung nodules in CT images

We are developing DCNN-based methods for the segmentation of lung nodules of a wide variety of sizes, shapes, and margins. In this study, we developed several fusion methods for hybridizing multiple DCNNs with different structures to improve segmentation accuracy. Two groups of fusion methods that combined the output information from our previously designed shallow and deep U-shape based deep learning models (U-DL) were compared. Group-1 denotes the late fusion (LF) methods that concatenated the feature maps output from the last layers (before a sigmoid activation layer) of the two U-DLs. Group-2 denotes early fusion (EF) methods that combined multi-scale output information from the encoders and decoders, or decoders alone, of the two U-DLs. A set of 883 cases from the LIDC-IDRI database which contained lung nodules manually marked by at least two radiologists was selected for this study. We split the data into 683 training and validation and 200 independent test cases. The multiple DCNNs with the fusion method were trained simultaneously and end-to-end. The baseline LF-1 method using pre-defined thresholds achieved an average DICE coefficient of 0.718±0.159. The newly developed LF method using Squeeze and Excitation Attention Block (SEAB) followed by a sigmoid activation layer (LF-4), and two Convolutional Block Attention Modules (CBAM) based EF methods that combined multiscale information from the decoders alone (EF-2) or from both the encoders and decoders (EF-3) of the two U-DLs, achieved significantly (p<0.05) better performance with average DICE coefficients of 0.745±0.135, 0.745±0.142, and 0.747±0.142, respectively.
Application of Chemically and Physically Synthesized Metal Nanoparticles to Staphylococcus aureus

The infections caused by S. aureus have emerged as a grave challenge to human health worldwide. Further, conventional antibiotic therapies for S. aureus-mediated infections are gradually becoming ineffective due to the emergence of drug-resistant strains like methicillin-resistant Staphylococcus aureus (MRSA). In search of alternative novel therapeutic strategies against S. aureus, the use of metal nanoparticles is proliferating. Among different synthesis methods of metal nanoparticles, chemical and physical methods are the most common. Despite reports of metal nanoparticles' efficacy against drug-resistant S. aureus strains, contemporary reports that the bacteria can evolve resistance to nanoparticles are a significant source of concern. There is also the issue of metal nanoparticle toxicity, which affects a variety of organisms. The clinical translatability of published research conclusions is another major hurdle in nanotherapeutics research. More research is needed to make nanoparticle-based treatments a viable and long-term therapy for infections caused by S. aureus. The present review provides an overview of the therapeutic application of physicochemically synthesized nanoparticles (electron beam, mechanical grinding, milling, spray pyrolysis, vapour phase synthesis, electrolysis, photochemical, solutions and gels, wound healing, anticancer, antioxidant, biosensing, cosmetics, antimicrobial, human health care and water treatment) of various metals (transition metals, post-transition metals, alkaline earth metals, rare earth metals, etc.) against various S. aureus strains.
Detection of Sulfur Dioxide by Broadband Cavity-Enhanced Absorption Spectroscopy (BBCEAS)

Sulfur dioxide (SO2) is an important precursor for the formation of atmospheric sulfate aerosol and acid rain. We present an instrument using Broadband Cavity-Enhanced Absorption Spectroscopy (BBCEAS) for the measurement of SO2 with a minimum limit of detection of 0.75 ppbv (3-σ) using the spectral range 305.5–312 nm and an averaging time of 5 min. The instrument consists of high-reflectivity mirrors (0.9985 at 310 nm) and a deep UV light source (Light Emitting Diode). The effective absorption path length of the instrument is 610 m with a 0.966 m base length. Published reference absorption cross sections were used to fit and retrieve the SO2 concentrations and were compared to fluorescence standard measurements for SO2. The comparison was well correlated, R2 = 0.9998 with a correlation slope of 1.04. Interferences for fluorescence measurements were tested and the BBCEAS showed no interference, while ambient measurements responded similarly to standard measurement techniques.
A Multimarker Model for Aberrant Cardiac Geometry after Preeclampsia

One out of four women with a history of preeclampsia shows abnormal cardiac remodeling consistent with subclinical heart failure (HF) in the first decade postpartum. Since these women are susceptible for developing remote symptomatic HF, development of a model for aberrant cardiac geometry as a first screening tool after delivery, is urgently needed. In this cross-sectional study, 752 preeclamptic women were included. Cardiovascular evaluation was conducted between six months and five years postpartum including cardiac ultrasound, systolic and diastolic blood pressure (SBP and DBP), plasma volume (PV) and biomarker assessment. We developed a multimarker model using uni- and multivariable linear regression and used the regression coefficients (RC) to develop a formula and estimate the aberrant cardiac remodeling in our population. Both SBP and PV were shown to be independently correlated with relative wall thickness (RWT) and left ventricular mass index (LVMi). C-reactive protein (CRP) and uric acid were independently correlated with RWT. Fibrinogen did not relate to either LVMi or RWT. This study displays markers of abnormal cardiac remodeling in former preeclamptic women, suggesting a combination of mechanical and biochemical factors that should be involved in worrisome chamber remodeling before clinical symptoms arise.
Research on Shanghai Stock Exchange 50 Index Forecast Based on Deep Learning

After decades of advance development, China's stock market has gradually arisen into one of the world's most important capital markets. The stock price index can well reflect the health status and macro change trend of a country's economic development, which can be said to be a barometer of the country's economic development. Studying the stock price index forecast is of great significance to the entire national economy and to each investor. Using 2 tools, Python and EViews8.0, and taking the Shanghai Stock Exchange 50 index as an example, the long short-term memory (LSTM) model in deep learning (DL) and the Autoregressive Integrated Moving Average (ARIMA) model are selected for fitting and prediction. The research results explain that the Root Mean Squared Error (RMSE) of LSTM model is lower, and the model based on DL method has stronger prediction ability on stock price index than traditional stock prediction model. This model is an effective stock prediction method.
Identification, Structural, and Expression Analyses of SPX Genes in Giant Duckweed (Spirodela polyrhiza) Reveals Its Role in Response to Low Phosphorus and Nitrogen Stresses

SPX genes play important roles in the coordinated utilization of nitrogen (N) and phosphorus (P) in plants. However, a genome-wide analysis of the SPX family is still lacking. In this study, the gene structure and phylogenetic relationship of 160 SPX genes were systematically analyzed at the genome-wide level. Results revealed that SPX genes were highly conserved in plants. All SPX genes contained the conserved SPX domain containing motifs 2, 3, 4, and 8. The 160 SPX genes were divided into five clades and the SPX genes within the same clade shared a similar motif composition. P1BS cis–elements showed a high frequency in the promoter region of SPXs, indicating that SPX genes could interact with the P signal center regulatory gene Phosphate Starvation Response1 (PHR1) in response to low P stress. Other cis–elements were also involved in plant development and biotic/abiotic stress, suggesting the functional diversity of SPXs. Further studies were conducted on the interaction network of three SpSPXs, revealing that these genes could interact with important components of the P signaling network. The expression profiles showed that SpSPXs responded sensitively to N and P deficiency stresses, thus playing a key regulatory function in P and N metabolism. Furthermore, the expression of SpSPXs under P and N deficiency stresses could be affected by environmental factors such as ABA treatment, osmotic, and LT stresses. Our study suggested that SpSPXs could be good candidates for enhancing the uptake ability of Spirodela polyrhiza for P nutrients in wastewater. These findings could broaden the understanding of the evolution and biological function of the SPX family and offer a foundation to further investigate this family in plants.
Structural equation modelling of construction bond administration

Purpose The purpose of this paper is to examine construction bonds, which is a risk management tool for ensuring that projects are delivered successfully, with emphasis on the influence of stakeholders, project characteristics and bonding decision factors. Design/methodology/approach Using case study of completed public building projects, questionnaires were administered on stakeholders that participated in the projects to solicit information on identified issues. Structural equation modelling (SEM) was used to examine relationship among identified factors, and various model selection and validation tests were carried out to arrive at the best-fit model. Findings The final model revealed that type of bond, stakeholders’ influence, project characteristics, risks of bonded projects and bonding decision factors have significant effect on success of bonded construction projects. Of the stakeholders, guarantors and contractors have greater influence on effective administration of bonds. Research limitations/implications The study was limited to Lagos and Ondo states, Nigeria. Data were gathered from clients of public projects, banks and insurance companies (guarantors), as well as contracting, quantity surveying and architectural firms registered with the state governments. This is because of the fact that only such firms can be engaged on projects emanating from the governments. Practical implications To enhance project success, there is a need to adopt construction bond for both public and private projects as against the current practice where it is only mandated for public projects. Originality/value Using SEM, this research examined administration of construction bonds with a view to ascertaining their effects on projects success, thereby providing relevant empirical information for stakeholders for effective administration of construction bond.
Rapid Development of a Data Visualization Service in an Emergency Response

We present the design and development of a data visualization service (RAMPVIS) in response to the urgent need to support epidemiological modeling workflows during the COVID-19 pandemic. Facing a set of demanding requirements and several practical challenges, our small team of volunteers had to rely on existing knowledge and components of services computing, while thinking on our feet in configuring services composition and adopting suitable approaches to services engineering. Through developing the RAMPVIS service, we have gained useful experience of ensuring conformation to services computing standards, enabling rapid development and early deployment, and facilitating effective and efficient maintenance and operation with limited resources. This experience can be valuable to the ongoing effort for combating the COVID-19 pandemic, and provides a blueprint for visualization service development when future needs for visual analytics arise during emergency response.