Miracle-dz/UniFAR-FTUs huggingface dataset:
Semiparametric methods for incomplete longitudinal count data with an application to health and retirement study

ABSTRACT In this paper, we propose and explore a novel semiparametric approach to analyzing longitudinal count data. We address the issue of missingness in longitudinal data and propose a weighted generalized estimations equations approach to fitting marginal mean response models for count responses with dropouts. Also, we investigate a spline regression approach to approximating the curvilinear relationship between the mean response and covariates. The asymptotic properties of the proposed estimators are studied in some detail. The empirical properties of the estimators are investigated using Monte Carlo simulations. An application is also provided using actual survey data obtained from the Health and Retirement Study (HRS).
Exploring the mechanism of the anti-hypertension properties of Morinda citrifolia through a bioinformatics approach

Traditionally, noni (Morinda citrifolia L.) has been used to treat hypertension in tropical countries. The noni extract was proven to reduce blood pressure and relatively safe to the liver and kidney in the animal model. This extract could inhibit angiotensin-converting enzyme (ACE) and plays a pivotal role in controlling blood pressure. However, the active compound of the extract that has function as the ACE inhibitor is still unknown. Therefore, the objective of this study was to examine the mechanism of anti-hypertension of noni methanol extract as well as its active compound that acts as the ACE inhibitor by using a bioinformatics approach. An enzyme activity analysis showed that noni methanol extract inhibits ACE activity based on a dose-dependent manner. Further analysis using bioinformatic analysis suggested that three active compounds of Morinda citrifolia, namely linoleic acid, palmitate, and oleic acid, might be bound to PPARA and NOS3 protein. The two targeted protein is predicted as a regulator of blood pressure through the PPARA pathway. The findings showed that M. citrifolia has numerous active compounds containing multiple protein targets, which regulate blood pressure. However, in vitro and in vivo research should be conducted to provide evidence for the mechanism.
Anoectochilus medogensis (Goodyerinae, Cranichideae, Orchidaceae), a new species from Tibet, China

Based on field observations and examination of preserved specimens, Anoectochilus medogensis is described as a new species from Tibet, China. Phylogenetic evidence using combined plastid regions (matK, trnL-F and rbcL) further supports the systematic status of A. medogensis. A detailed morphological description, photographic plates and line drawings, as well as conservation assessment are also provided for this new species.
Ambidexterity in Cross-Sector Collaborations Involving Public Organizations

Abstract This article extends the concept of organizational ambidexterity to encompass knowledge exploration and exploitation in cross-sector collaborations. Collaborations are frequently charged to devise or implement innovative solutions to longstanding complex public problems. Research on organizational management suggests that the capability to both explore and exploit knowledge—dubbed organizational ambidexterity—is an important contributor to innovation and long-term organizational performance. If cross-sector collaborations must innovate to address longstanding problems, and innovation requires the ability to explore and exploit knowledge, then collaborations too should benefit from developing ambidextrous capabilities. Using an illustrative case of a large-scale cross-sector collaboration in the transportation field, we investigate whether and how a cross-sector collaboration can explore and exploit knowledge. Based on our analysis, we demonstrate that collaborative ambidexterity exists and discuss external antecedents and mechanisms internal to the collaboration that enable collaborative ambidexterity. We conclude with a set of propositions to advance theory and provide an agenda for future research.
Molecular dynamics trajectory for benchmarking MDAnalysis

MD trajectory of apo adenylate kinase with CHARMM27 force field and simulated with explicit water and ions in NPT at 300 K and 1 bar. Saved every 240 ps for a total of 1.004 µs. Produced on PSC Anton. The trajectory only contains the protein and all solvent stripped. Superimposed on the CORE domain of AdK by RMSD fitting. The topology is contained in the PSF file (CHARMM format). The trajectory is contained in the DCD file (CHARMM/NAMD format).
Quantitative analysis of total magnetic anomaly maps on archaeological sites—Part 2

In this study, which is the second part of quantitative analysis of total magnetic anomaly maps on archaeological sites, it is aimed to analyze the depth values of potential buried structures that cause anomalies from the total magnetic anomaly maps of an archaeological excavation area. In the first step, depth values of the structures whose boundaries were determined on the improved total magnetic anomaly map of the model were analyzed. Depth values of blocks were calculated by using of tilt angle depth (TAD), source parameter imaging (SPI), and improved source parameter imaging (iSPI) methods. In the second step, the depth values at these boundaries were calculated. The total magnetic anomaly map of the mound area, for which the structure boundary analysis was made was calculated, and the depth values at the potential structure boundaries were calculated. Finally, the depth values are visualized on the simplified structure map of the region by combining and simplifying the potential structure boundary locations.
Coping with the transition to remote instruction: Patterns of self-regulated engagement in a large post-secondary biology course

Abstract The COVID-19 disruption presented considerable challenges for university students, requiring the sudden need for increased engagement in remote learning environments and the ability to cope with academic and familial demands. To examine how students self-regulated their learning during the disruption, we surveyed undergraduates (n = 226) enrolled in four sections of a large biology course once during the first week of the semester, immediately after the disruption, and through the end of the semester. The results indicated significant decreases in student motivation, increases in students’ perceived costs, and quadratic changes in self-reported coping strategies and mental depletion during disrupted learning. In a final model, students’ self-efficacy and perceptions of cost, as well as feelings of anger and personal responsibility for family combined to form a parsimonious set of predictors that explained variance in course performance.
Systematic Analysis of Sugar Unloading And Accumulation Mechanism In Sucrose- And Hexose- Accumulating Tomato Fruits

Sugar is the key factor in the formation of fruit quality. Hexose is the main form of sugar accumulated in ordinary cultivated tomatoes, while a small number of wild-type tomato varieties can also accumulate sucrose. Although several studies have focused on wild sucrose-accumulating tomatoes, the sugar accumulation mechanism in tomato is still unclear. Here, two cherry tomatoes lines that accumulated sucrose and hexose respectively were selected to analyze the assimilates unloading pathway and sugar accumulation mechanism using CF tracing, cytological observation, proteomics methods, etc. The results indicated that the later stages of fruit development were key stages for sugar accumulation, and sucrose-accumulating (S) cherry tomatoes had higher sucrose contents in the fruits, while hexose-accumulating (H) cherry tomatoes accumulated more glucose, fructose and starch. The unloading pathway of assimilates in the S cherry tomato was switched from apoplastic to symplastic during fruit development, and the opposite was true in the H type. Plasmodesmata transport may be the main means of sucrose accumulation and high activity or expression levels of acid invertase (AI) and SUT1 may be important factors in hexose accumulation in H and S cherry tomatoes, respectively. In addition to sugar metabolism, photosynthesis, fatty acid metabolism and other secondary metabolism pathways also play important roles in sugar accumulation. This study provides detailed evidence for the tomato sugar accumulation mechanism from the perspective of cell structure, physiology and molecular biology, providing a theoretical basis for the improvement of tomato quality and aiding the utilization of tomato genetic resources.
Forecasting Particulate Pollution in an Urban Area: From Copernicus to Sub-Km Scale

Particulate air pollution has aggravated cardiovascular and lung diseases. Accurate and constant air quality forecasting on a local scale facilitates the control of air pollution and the design of effective strategies to limit air pollutant emissions. CAMS provides 4-day-ahead regional (EU) forecasts in a 10 km spatial resolution, adding value to the Copernicus EO and delivering open-access consistent air quality forecasts. In this work, we evaluate the CAMS PM forecasts at a local scale against in-situ measurements, spanning 2 years, obtained from a network of stations located in an urban coastal Mediterranean city in Greece. Moreover, we investigate the potential of modelling techniques to accurately forecast the spatiotemporal pattern of particulate pollution using only open data from CAMS and calibrated low-cost sensors. Specifically, we compare the performance of the Analog Ensemble (AnEn) technique and the Long Short-Term Memory (LSTM) network in forecasting PM2.5 and PM10 concentrations for the next four days, at 6 h increments, at a station level. The results show an underestimation of PM2.5 and PM10 concentrations by a factor of 2 in CAMS forecasts during winter, indicating a misrepresentation of anthropogenic particulate emissions such as wood-burning, while overestimation is evident for the other seasons. Both AnEn and LSTM models provide bias-calibrated forecasts and capture adequately the spatial and temporal variations of the ground-level observations reducing the RMSE of CAMS by roughly 50% for PM2.5 and 60% for PM10. AnEn marginally outperforms the LSTM using annual verification statistics. The most profound difference in the predictive skill of the models occurs in winter, when PM is elevated, where AnEn is significantly more efficient. Moreover, the predictive skill of AnEn degrades more slowly as the forecast interval increases. Both AnEn and LSTM techniques are proven to be reliable tools for air pollution forecasting, and they could be used in other regions with small modifications.
Effect of amino acid, pH and mineral salts on glass transition and flow behaviour of soy protein concentrate

The objective of this study was to assess the effect of proline, mineral salts (NaCl and Na2SO4) and pH combined with moisture content on the glass transition temperature (Tg) and flow-starting temperature (Tf) of soy protein concentrate (SPC). Initial screening of the variables based on fractional factorial design showed insignificant effect of NaCl on Tg and Tf. The design was extended to a face-centred central composite design (CCD) excluding NaCl and data evaluated by use of response surface methodology. The established model for Tg (R 2 = 0.824) shows significant negative first-order effects of moisture, proline and Na2SO4, and a positive interaction effect of moisture and Na2SO4. The Tf model (R 2 = 0.937) shows significant negative first-order effects of moisture and proline, a positive first-order and negative square effect of pH, and a negative interaction effect of moisture and proline. The main effect on Tg and Tf was 2.2 and 1.3 times higher, respectively, for moisture compared to proline. The study confirms that proline (or other free amino acids) can replace moisture as protein plasticiser in the extrusion process. Minor effects can also be obtained by reduction in pH.
Pd(II) ion adsorption onto emulsion gel beads in a fixed bed

ABSTRACT We developed previously an emulsion gel adsorbent for improved metal adsorption. This study focuses on a continuous adsorption–desorption process of metal ions from a solution onto emulsion gel beads using the fixed-bed method. The monodisperse millimeter-sized emulsion gel beads, a polymeric hydrogel containing randomly distributed oil microdroplets of di-n-hexylsulfide as an extractant, were prepared using an automatic production method combining sedimentation polymerization and two-fluid atomization. The isotherms and the kinetics for Pd(II) adsorption were investigated. A continuous adsorption–desorption process was successfully demonstrated, and the breakthrough curve was successfully predicted by a mathematical analysis.
Improved gray wolf particle filtering and high‐fidelity second‐order autoregressive equivalent modeling for intelligent state of charge prediction of lithium‐ion batteries

The rapid development of new energy vehicles puts forward higher requirements for the lithium‐ion batteries model construction, high‐efficiency condition monitoring and collaborative estimation. An improved high‐fidelity second‐order autoregressive model is proposed and constructed, and the autoregressive model is integrated with the second‐order equivalent circuit model, which can achieve an accurate and reliable description of the batteries internal dynamic change process. To achieve the accurate expression of the battery's external characteristics and internal state, the forgetting factor is combined with the recursive least square algorithm to improve the parameter identification accuracy and optimality while reducing the space complexity of the algorithm. A novel gray wolf particle filtering algorithm is proposed, which eliminates the particles severe degradation in traditional algorithms and enhances the ability of particles to resist degradation. The algorithm superiority and generalization are verified under complex working conditions. The experimental results show that the accuracy of the high‐fidelity second‐order autoregressive model can reach 99%, which can well simulate the complex chemical reaction process inside the lithium‐ion battery. Experimental simulation is performed under constant current conditions. Compared with the extended Kalman filter, unscented Kalman filter, and particle filter algorithms, the gray wolf particle filter algorithm has reduced the root mean square error by 3.39%, 0.90%, and 2.84%, and the mean absolute error has reduced by 1.95%, 0.51%, and 2.22%. Under dynamic stress test conditions, the root mean square error is reduced by 1.54%, 0.33%, and 0.78%, and the average absolute error is reduced by 1.4%, 0.22%, and 0.76%. In addition, when tested under different environmental conditions, although the improved algorithm has a relatively long running time, the estimation accuracy of the algorithm is greatly improved and the execution efficiency is high. The improved algorithm provides a theoretical basis for the reliability and stability of the onboard operation of lithium‐ion batteries.
Excessive number of high asperities for sputtered rough films

The roughness of solids is crucial for interactions between bodies at short separations due to capillary or van der Waals--Casimir forces and for contact mechanics. Specifically, it is critical for the fabrication and operation of microelectromechanical systems, for which functional materials are deposited using thin film coating technologies. Here, it is demonstrated that the materials deposited by magnetron sputtering or thermally evaporated on a cold Si substrate reveal a significantly larger number of high asperities than that predicted by the normal distribution. Such asperities define the distance between the solids in contact that is the key parameter for many problems. The effect is related to the nonequilibrium deposition conditions and is suppressed if the material is deposited on a hot substrate or annealed. The high asperity tails can be described by the extreme value distribution or in some cases by the exponential distribution.
Degradation of Brominated Organic Compounds (Flame Retardants) by a Four-Strain Consortium Isolated from Contaminated Groundwater

Biodegradation of pollutants in the environment is directly affected by microbial communities and pollutant mixture at the site. Lab experiments using bacterial consortia and substrate mixtures are required to increase our understanding of these processes in the environment. One of the deficiencies of working with environmental cultures is the inability to culture and identify the active strains while knowing they are representative of the original environment. In the present study, we tested the aerobic microbial degradation of two brominated flame retardants, tribromo-neopentyl alcohol (TBNPA) and dibromo neopentyl glycol (DBNPG), by an assembled bacterial consortium of four strains. The four strains were isolated and plate-cultured from a consortium enriched from the impacted groundwater underlying the Neot Hovav industrial area (Negev, Israel), in which TBNPA and DBNPG are abundant pollutants. Total degradation (3–7 days) occurred only when the four-strain consortium was incubated together (25 °C; pH −7.2) with an additional carbon source, as both compounds were not utilized as such. Bacterial growth was found to be the limiting factor. A dual carbon–bromine isotope analysis was used to corroborate the claim that the isolated strains were responsible for the degradation in the original enriched consortium, thus ensuring that the isolated four-strain microbial consortium is representative of the actual environmental enrichment.
Social and economic effects of illicit financial flows in South Africa

Mining plays an important role in the South African economy and society at large, as is the case for many countries with a significant mining sector. The South African Chamber of Mines (2016) estimates that the mining industry contributed R286 billion to the economy, which translates to 7.1% of Gross Domestic Product (GDP), in 2015. Furthermore, the Chamber of Mines indicates that almost half a million (457 698) people were employed in the mining industry in 2015, which translates to 3% of all employed people in South Africa (South African Chamber of Mines, 2016). It is in this context that this chapter deals with Illicit Financial Flows (IFFs) in the mining sector in South Africa. IFFs are a big challenge, especially in the extractives sectors.
Text Mining of Hazard and Operability Analysis Reports Based on Active Learning

In the field of chemical safety, a named entity recognition (NER) model based on deep learning can mine valuable information from hazard and operability analysis (HAZOP) text, which can guide experts to carry out a new round of HAZOP analysis, help practitioners optimize the hidden dangers in the system, and be of great significance to improve the safety of the whole chemical system. However, due to the standardization and professionalism of chemical safety analysis text, it is difficult to improve the performance of traditional models. To solve this problem, in this study, an improved method based on active learning is proposed, and three novel sampling algorithms are designed, Variation of Token Entropy (VTE), HAZOP Confusion Entropy (HCE) and Amplification of Least Confidence (ALC), which improve the ability of the model to understand HAZOP text. In this method, a part of data is used to establish the initial model. The sampling algorithm is then used to select high-quality samples from the data set. Finally, these high-quality samples are used to retrain the whole model to obtain the final model. The experimental results show that the performance of the VTE, HCE, and ALC algorithms are better than that of random sampling algorithms. In addition, compared with other methods, the performance of the traditional model is improved effectively by the method proposed in this paper, which proves that the method is reliable and advanced.
Oxygen-plasma treatment-induced surface engineering of biomimetic polyurethane nanofibrous scaffolds for gelatin-heparin immobilization

Abstract Polyurethane (PU) has been extensively used in vascular tissue engineering due to its outstanding mechanical performance and blood compatibility behavior. Here, biomimetic PU-based scaffolds were prepared using an electrospinning technique and gelatin-heparin was introduced as a surface modifier after oxygen plasma treatment to improve cell attachment and release an anticoagulation agent. Morphology, Fourier transform infrared (FTIR) spectroscopy, compression strength, swelling and biodegradation ratio, drug release level and cellular interactions were evaluated. According to the scanning electron microscopy (SEM) micrographs, gelatin-heparin immobilized PU nanofibers exhibited a smooth surface and a bead free structure that nanofibers distributed in the range of 300–1000 nm. The mechanical strength of constructs, swelling and biodegradation ratio, and drug release level illustrated higher values for oxygen plasma-treated samples compared with bilayered scaffolds. Cellular adhesion and biocompatibility ameliorated after plasma treatment. All the mentioned findings indicated the initial physicomechanical and biological potential of biomimetic PU-based fibers in the improvements of vascular scaffolds.
Logging effects on seedling regeneration and diversity in a tropical moist semi-deciduous forest in Ghana

ABSTRACT The effect of time lag after logging on seedling dynamics was assessed in logged and unlogged forest plots located in the Pra-Anum Forest Reserve. Remnant tree attributes were sampled in six plots with sizes of 25 × 25 m in each forest type. Within each forest type, ten subplots with sizes 1 × 1 m were established for sampling seedling regeneration dynamics. Enumerated seedlings were grouped as pioneer, non-pioneer light demander, and shade-tolerant species. Regenerating seedlings were more diverse in the recently logged forest area characterised by Broussonetia papyrifera and Musanga cecropioides, and least in the unlogged forest driven predominantly by Celtis mildbraedii and Baphia nitida. Pioneer species were primarily dominant in the recently logged forest, while shade-tolerant and non-pioneer light-demanding species characterised the logged-over forest. Species richness and canopy openness of remnant stands explained 32 percent of the variations in regeneration richness between the logged and unlogged areas. Twenty-seven percent of the variations in seedling abundance was also explained by remnant trees richness, their size diameter and the degree to which their canopy has been opened. Logging-induced disturbance favours the sporadic emergence of pioneer species in recently disturbed areas which are later replaced by non-pioneer light-demanding or shade-tolerant species as light becomes limiting in the understory.
Ensemble Precipitation Estimation Using a Fuzzy Rule-Based Model

In this study, a Takagi-Sugeno (TS) fuzzy rule-based (FRB) model is used for ensembling precipitation time series. The TS FRB model takes precipitation predictions of grid-based regional climate models (RCMs) from the EUR11 domain, available from the CORDEX database, as inputs to generate ensembled precipitation time series for two meteorological stations (MSs) in the Mediterranean region of Turkey. For each MS, RCM data that are available at the closest grid to the corresponding MSs are used. To generate the fuzzy rules of the TS FRB model, the subtractive clustering algorithm (SC) is utilized. Together with the TS FRB, the simple ensemble mean approach is also applied, and the performances of these two model results and individual RCM predictions are compared. The results show that ensembled models outperform individual RCMs, for monthly precipitation, for both MSs. On the other hand, although ensemble models capture the general trend in the observations, they underestimate the peak precipitation events.