Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative genomics of CXCR4 MUT and CXCR4 WT single cells in Waldenstr¨om ’ s macroglobulinemia

Cristina Jiménez, Lian Xu, Nickolas Tsakmaklis, Maria G. Demos, Amanda Kofides, Gloria G. Chan, Maria Luisa Guerrera, Jiaji G. Chen, Xia Liu, Manit Munshi, Christopher J. Patterson, Guang Yang, Jorge J. Castillo, Steven P. Treon, and Zachary R. Hunter Bing Center for Waldenström’s Macroglobulinemia, Dana-Farber Cancer Institute, Boston, MA; and Department of Medicine, Harvard Medical School, Boston, MA
Response of Soil Microbial Community Structure to Phosphate Fertilizer Reduction and Combinations of Microbial Fertilizer

The excessive application of phosphorus (P) fertilizer is becoming a major agricultural problem, which reduces the utilization rate of the P fertilizer and degrades soil quality. The following five P fertilizer treatments were investigated to know how they affect soil properties, enzyme activity, bacterial and fungal community structure. 1) no P fertilizer (P0); 2) farmers’ traditional P fertilization scheme (FP); 3) 30% reduction in P fertilizer application (P1, microbial blended fertilizer as base fertilizer); 4) 30% reduction in P fertilizer application (P2, diammonium phosphate as starting fertilizer); 5) 30% reduction in P fertilizer application (P3, microbial inoculum seed dressing). The P fertilizer reduction combined with microbial fertilizer significantly increased soil organic matter (SOM), total phosphorus (TP), available phosphorus (AP) available potassium (AK) contents, and acid phosphatase activity (ACP), however, soil urease activity was significantly reduced. Moreover, the P fertilizer reduction combined with microbial fertilizer significantly increased the relative abundance of a potential beneficial genus (i.e., Bacillus, Pseudomonas, Penicillium, and Acremonium) and potentially pathogenic genus (i.e., Fusarium, Gibberella, and Drechslera). The structural equation model (SEM) revealed that different P fertilizer reduction systems had significant indirect effects on bacterial and fungal community structures. The results suggested that the P fertilizer reduction combined with microbial fertilizer systems regulated the pathogenic and beneficial genus which created a microbial community that is favorable for maize growth. Moreover, the findings highlighted the importance of soil properties in determining the soil bacterial and fungal community structure.
Prediction and Risk Stratification of Cardiovascular Disease in Diabetic Kidney Disease Patients

Background Diabetic kidney disease (DKD) patients are facing an extremely high risk of cardiovascular disease (CVD), which is a major cause of death for DKD patients. We aimed to build a deep learning model to predict CVD risk among DKD patients and perform risk stratifying, which could help them perform early intervention and improve personal health management. Methods A retrospective cohort study was conducted to assess the risk of the occurrence of composite cardiovascular disease, which includes coronary heart disease, cerebrovascular diseases, congestive heart failure, and peripheral artery disease, in DKD patients. A least absolute shrinkage and selection operator (LASSO) regression was used to perform the variable selection. A deep learning-based survival model called DeepSurv, based on a feed-forward neural network was developed to predict CVD risk among DKD patients. We compared the model performance with the conventional Cox proportional hazards (CPH) model and the Random survival forest (RSF) model using the concordance index (C-index), the area under the curve (AUC), and integrated Brier scores (IBS). Results We recruited 890 patients diagnosed with DKD in this retrospective study. During a median follow-up of 10.4 months, there are 289 patients who sustained a subsequent CVD. Seven variables, including age, high density lipoprotein (HDL), hemoglobin (Hb), systolic blood pressure (SBP), smoking status, 24 h urinary protein excretion, and total cholesterol (TC), chosen by LASSO regression were used to develop the predictive model. The DeepSurv model showed the best performance, achieved a C-index of 0.767(95% confidence intervals [CI]: 0.717–0.817), AUC of 0.780(95%CI: 0.721–0.839), and IBS of 0.067 in the validation set. Then we used the cut-off value determined by ROC (receiver operating characteristic) curve to divide the patients into different risk groups. Moreover, the DeepSurv model was also applied to develop an online calculation tool for patients to conduct risk monitoring. Conclusion A deep-learning-based predictive model using seven clinical variables can effectively predict CVD risk among DKD patients and perform risk stratification. An online calculator allows its easy implementation.
Unsupervised Haze Removal for Aerial Imagery Based on Asymmetric Contrastive CycleGAN

Aerial image dehazing is an important preprocessing step, since haze extremely degrades the imaging quality and affects subsequent the applications of aerial imagery. Most current haze removal methods achieve encouraging performance by relying on paired synthetic data, while are limited to their generality and scalability in the practical tasks. To this end, this paper aims to learn an effective unsupervised dehazing model from an unpaired set of clear and hazy aerial images. Motivated by the great advantages of contrastive learning in unsupervised representation field, we first attempt to formulate a Asymmetric Contrastive CycleGAN dehazing framework (namely ACC-GAN) to maximize the mutual information between the hazy domain and the haze-free domain. In the latent representation space, the introduced contrastive constraint ensures that the restored image is pulled closer to the clear image and pushed away from the hazy image, so as to indirectly regularize the unsupervised dehazing process. Importantly, different from the standard CycleGAN, we develop an additional feature transfer network into the forward path to form the asymmetric structure of ACC-GAN, which can enhance encoded features from hazy domain to haze-free domain. During training, multi-dimension loss terms are jointly built into a loss committee for generating dehazed results with higher naturalness and better fidelity. Experimental results on synthesis and real-world datasets indicate that our method is superior to existing unsupervised dehazing approaches, and is also very competitive to other related supervised models.
Monitoring of Three-Phase Signals Based on Singular-Value Decomposition

In this paper, a new approach for the analysis of three-phase electrical signals is considered. While most of the existing techniques are based on fixed transforms such as the Clarke transform, this paper investigates the use of a data-driven approach called the singular value decomposition (SVD). As compared to other transforms, this paper shows that the SVD has the distinct advantage of clearly separating the contributions of the phasor configuration and signal instantaneous parameters. Under additive white Gaussian noise, this paper also describes several algorithms based on the SVD for signal monitoring. The first algorithm can detect unbalanced systems and classify them into two categories: 1) system with an off-nominal subspace and 2) systems with ellipticity. The second algorithm can estimate the angular frequency based on the periodogram of the right singular vectors. As compared to other existing approaches, simulations show that the proposed techniques give a good compromise between computational complexity and statistical performance.
Obesity-Related Chronic Kidney Disease: Principal Mechanisms and New Approaches in Nutritional Management

Obesity is the epidemic of our era and its incidence is supposed to increase by more than 30% by 2030. It is commonly defined as a chronic and metabolic disease with an excessive accumulation of body fat in relation to fat-free mass, both in terms of quantity and distribution at specific points on the body. The effects of obesity have an important impact on different clinical areas, particularly endocrinology, cardiology, and nephrology. Indeed, increased rates of obesity have been associated with increased risk of cardiovascular disease (CVD), cancer, type 2 diabetes (T2D), dyslipidemia, hypertension, renal diseases, and neurocognitive impairment. Obesity-related chronic kidney disease (CKD) has been ascribed to intrarenal fat accumulation along the proximal tubule, glomeruli, renal sinus, and around the kidney capsule, and to hemodynamic changes with hyperfiltration, albuminuria, and impaired glomerular filtration rate. In addition, hypertension, dyslipidemia, and diabetes, which arise as a consequence of overweight, contribute to amplifying renal dysfunction in both the native and transplanted kidney. Overall, several mechanisms are closely related to the onset and progression of CKD in the general population, including changes in renal hemodynamics, neurohumoral pathways, renal adiposity, local and systemic inflammation, dysbiosis of microbiota, insulin resistance, and fibrotic process. Unfortunately, there are no clinical practice guidelines for the management of patients with obesity-related CKD. Therefore, dietary management is based on the clinical practice guidelines for the nutritional care of adults with CKD, developed and published by the National Kidney Foundation, Kidney Disease Outcome Quality Initiative and common recommendations for the healthy population. Optimal nutritional management of these patients should follow the guidelines of the Mediterranean diet, which is known to be associated with a lower incidence of CVD and beneficial effects on chronic diseases such as diabetes, obesity, and cognitive health. Mediterranean-style diets are often unsuccessful in promoting efficient weight loss, especially in patients with altered glucose metabolism. For this purpose, this review also discusses the use of non-classical weight loss approaches in CKD, including intermittent fasting and ketogenic diet to contrast the onset and progression of obesity-related CKD.
Active Condensation of Filaments Under Spatial Confinement

Living systems exhibit self-organization, a phenomenon that enables organisms to perform functions essential for life. The interior of living cells is a crowded environment in which the self-assembly of cytoskeletal networks is spatially constrained by membranes and organelles. Cytoskeletal filaments undergo active condensation in the presence of crosslinking motor proteins. In past studies, confinement has been shown to alter the morphology of active condensates. Here, we perform simulations to explore systems of filaments and crosslinking motors in a variety of confining geometries. We simulate spatial confinement imposed by hard spherical, cylindrical, and planar boundaries. These systems exhibit non-equilibrium condensation behavior where crosslinking motors condense a fraction of the overall filament population, leading to coexistence of vapor and condensed states. We find that the confinement lengthscale modifies the dynamics and condensate morphology. With end-pausing crosslinking motors, filaments self-organize into half asters and fully-symmetric asters under spherical confinement, polarity-sorted bilayers and bottle-brush-like states under cylindrical confinement, and flattened asters under planar confinement. The number of crosslinking motors controls the size and shape of condensates, with flattened asters becoming hollow and ring-like for larger motor number. End pausing plays a key role affecting condensate morphology: systems with end-pausing motors evolve into aster-like condensates while those with non-end-pausing crosslinking motor proteins evolve into disordered clusters and polarity-sorted bundles.
Integrating Writing Assignments at an American Branch Campus in Qatar: Challenges, Adaptations, and Recommendations

Recently, many western institutions have established international branch campuses (IBCs) in many parts of the MENA region. However, to be successful, IBCs must adapt to the needs of the context in which they operate. This chapter investigates challenges and adaptations in integrating academic writing across the curriculum at a branch campus of an American university in Qatar. Interviews with 65 faculty across disciplines highlight faculty perceptions of students’ challenges with writing, and adaptations faculty make in response. Based on their findings, the authors make recommendations for adapting writing instruction for English-medium universities in the Middle East, especially at IBCs.
Colour Duplex and/or Contrast-Enhanced Ultrasound Compared with Computed Tomography Angiography for Endoleak Detection after Endovascular Abdominal Aortic Aneurysm Repair: A Systematic Review and Meta-Analysis

This study aims to assess the role of Color Duplex Ultrasound with or without contrast media for surveillance following endovascular aortic aneurysm repair (EVAR). A systematic search of the literature published until April 2022 was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The pooled rates of endoleak detection through Contrast-Enhanced or Color Duplex Ultrasound (CEUS or CDUS) and Computed Tomography Angiography (CTA) with 95% confidence intervals (CIs) were estimated using random-effect analysis. Thirty-eight studies were considered eligible for inclusion. The total number of patients in the included studies was 5214 between 1997 and 2021. The overall pooled rate of endoleak detection using CDUS and CTA was 82.59% and 97.22%, while the rates for CEUS and CTA were 96.67% and 92.82%, respectively. The findings of the present study support the use of the CEUS for endoleak detection. However, it should be integrated into institutional protocols for EVAR surveillance to further evaluate its clinical utility in the post-EVAR period before it can be recommended as the sole imaging modality after EVAR.
Aquila Optimizer Based Optimal Allocation of Soft Open Points for MultiObjective Operation in Electric Vehicles Integrated Active Distribution Networks

: The appropriate position and sizing of soft open points (SOPs) for reducing the detrimental impact of electric vehicle (EV) load penetration and renewable energy (RE) variation on active distribution networks (ADNs) are provided in this study. Soft open points (SOPs) have been used to create a multi-objective framework that considers loss minimization and voltage profile enhancement. The non-linear multi-variable complicated SOP allocation problem is solved for the first time using a modern meta-heuristic Aquila optimizer (AO). The modified IEEE 33-bus benchmark and IEEE 69-bus ADNs are used in the simulations. Before SOPs, the average real power loss in IEEE 33-bus AND was 370.329 kW, but after SOPs, it was reduced to 259.356 kW (i.e., 29.96 percent reduction). Similarly, effective SOPs integration in the IEEE 69-bus resulted in a loss reduction of 81.07 percent. AO's computational efficiency is also compared to that of multiobjective particle swarm optimization (MOPSO), particle swarm optimization (PSO), and cuckoo search algorithm (CSA). The AO has produced better results in terms of lower losses, improved voltage profile despite variations in EV load penetration, and RE and load volatility in ADNs, according to the
Six-track multi-finger standard cell library design for near-threshold voltage operation in 130 nm complementary metal oxide semiconductor technology

In this study, a six-track standard cell library with a multi-finger layout structure is proposed to improve the delay, energy, and area of the digital circuit design for near-threshold operation. The proposed library is optimised by using the parasitic effects of the technology and optimising the layout. To enhance the performance and energy efficiency, inverse narrow width effect has been considered in the design, whereby the minimum width of the process was used as the based width unit. To minimise the design area, the standard cell was designed in the lowest possible height with a multi-finger layout structure. The proposed library with a few basic cells was developed and characterised in 130 nm technology, which is available for synthesis and automatic place-and-route (P&R). The proposed library was analysed and compared with two eight-track multiplier layout libraries in the cell and block design level. Based on the place-and-route results of ISCAS'85 benchmark circuits, the proposed six-track library could achieve up to 27% of delay improvement, 29% energy reduction and 44% area reduction as compared to the multiplier structure library at the minimum critical path delay.
Single Spin Asymmetries in l p(transv. pol.) -->h X processes and TMD factorisation

Some estimates for the transverse Single Spin Asymmetry, A_N, in the inclusive processes l p(transv. pol.) -->h X, given in a previous paper, are expanded and compared with new experimental data. The predictions are based on the Sivers distributions and the Collins fragmentation functions which fit the azimuthal asymmetries measured in Semi-Inclusive Deep Inelastic Scattering (SIDIS) processes (l p(transv. pol.) -->l' h X). The factorisation in terms of Transverse Momentum Dependent distribution and fragmentation functions (TMD factorisation) -- i.e., the theoretical framework in which SIDIS azimuthal asymmetries are analysed -- is assumed to hold also for the inclusive process l p -->h X at large P_T. The values of A_N thus obtained agree in sign and shape with the data. Some predictions are given for future experiments.
Beyond glacier-wide mass balances: parsing seasonal elevation change into spatially resolved patterns of accumulation and ablation at Wolverine Glacier, Alaska

Abstract We present spatially distributed seasonal and annual surface mass balances of Wolverine Glacier, Alaska, from 2016 to 2020. Our approach accounts for the effects of ice emergence and firn compaction on surface elevation changes to resolve the spatial patterns in mass balance at 10 m scale. We present and compare three methods for estimating emergence velocities. Firn compaction was constrained by optimizing a firn model to fit three firn cores. Distributed mass balances showed good agreement with mass-balance stakes (RMSE = 0.67 m w.e., r = 0.99, n = 41) and ground-penetrating radar surveys (RMSE = 0.36 m w.e., r = 0.85, n = 9024). Fundamental differences in the distributions of seasonal balances highlight the importance of disparate physical processes, with anomalously high ablation rates observed in icefalls. Winter balances were found to be positively skewed when controlling for elevation, while summer and annual balances were negatively skewed. We show that only a small percent of the glacier surface represents ideal locations for mass-balance stake placement. Importantly, no suitable areas are found near the terminus or in elevation bands dominated by icefalls. These findings offer explanations for the often-needed geodetic calibrations of glaciological time series.
Low-Density Particleboards Modified with Expanded and Unexpanded Fillers—Characteristics and Properties

Reducing the density of wood-based materials is a desirable research direction in the development of the wood-based materials sector. Even though lightweight wooden particleboards have been commercially available for many years, they still have a number of disadvantages, especially their low strength parameters. The aim of this paper was to determine the possibility of producing particleboards of reduced density for use in the furniture industry, as a result of using expanded polystyrene and two types of microspheres (expanded and unexpanded) to modify the core layer of three-layer particleboards. Analysis of the results of testing the particleboards’ properties when using various types of modifiers (expanded and unexpanded fillers), urea formaldehyde (UF) glue content (high: 10%/12% and low: 8%/10%), various glue-dosing methods, and different particle sizes, allows us to conclude that the most satisfactory effect was found when using EPS. One partly positive effect was observed when using the Expancel-type 031 DU 40 as a filler; therefore, it is recommended that research be continued in this area. Using microspheres that have not been used before as a filler in the production of wood-based panels is the novelty of the presented research. The proposed technology has potential for application in the industry.
Entrepreneurial orientation of SMEs, total quality management and firm performance

Purpose The purpose of this paper is to investigate the effects of entrepreneurial orientation (EO) and total quality management (TQM) on the performance of small- and medium-sized manufacturing enterprises. Design/methodology/approach Frameworks for describing EO and TQM derived from the literature were reviewed and used to develop a questionnaire. The hypothesized relationships of this model are tested with the data collected from 121 manufacturing small and medium enterprises (SMEs) by using AMOS. The approach has been directed toward justification of EO and TQM strategy for its support to competitive manufacturing in the context of Indian manufacturing industries. Findings The results indicate that EO plays an influential role on the adoption of TQM strategy, and also has a direct effect on firm performance (FP). The results also indicate that the significance of the direct effect of EO on FP is reduced when the indirect effect of EO through TQM is included in the total effect model. Firms with higher level of EO will be more successful in adopting TQM strategy, which helps them in developing new capabilities that allow them to achieve better performance. Research limitations/implications The research is cross-sectional in nature and, therefore, it does not permit us to account for the lag between implementation and performance. Second, the performance measures are subjective and may be subject to response bias. Practical implications The study presented in this paper offers entrepreneurs, academics and practitioners a better understanding of the relationship and impact of the EO and TQM on the manufacturing performance. Thus, entrepreneurs and practitioners will be able to make better and more effective decisions about the implementation of TQM practices. Originality/value By linking EO strategy and TQM practices to world-class manufacturing practices and performance in Indian manufacturing SMEs, this research adds a new dimension to study of world-class manufacturing and more generally to the best practices and practice-performance debates. This knowledge is important and unique, because it emphasizes that in addition to quality management practices, which are focused on efficient process management aspects of the organization, EO should also be given equal emphasis, in order to improve manufacturing performance of SMEs.