Miracle-dz/UniFAR-FTUs huggingface dataset:
Automated annotation of rare-cell types from single-cell RNA-sequencing data through synthetic oversampling

The research landscape of single-cell and single-nuclei RNA-sequencing is evolving rapidly. In particular, the area for the detection of rare cells was highly facilitated by this technology. However, an automated, unbiased, and accurate annotation of rare subpopulations is challenging. Once rare cells are identified in one dataset, it is usually necessary to generate further specific datasets to enrich the analysis (e.g., with samples from other tissues). From a machine learning perspective, the challenge arises from the fact that rare-cell subpopulations constitute an imbalanced classification problem. We here introduce a Machine Learning (ML)-based oversampling method that uses gene expression counts of already identified rare cells as an input to generate synthetic cells to then identify similar (rare) cells in other publicly available experiments. We utilize single-cell synthetic oversampling (sc-SynO), which is based on the Localized Random Affine Shadowsampling (LoRAS) algorithm. The algorithm corrects for the overall imbalance ratio of the minority and majority class. We demonstrate the effectiveness of our method for three independent use cases, each consisting of already published datasets. The first use case identifies cardiac glial cells in snRNA-Seq data (17 nuclei out of 8635). This use case was designed to take a larger imbalance ratio (~1 to 500) into account and only uses single-nuclei data. The second use case was designed to jointly use snRNA-Seq data and scRNA-Seq on a lower imbalance ratio (~1 to 26) for the training step to likewise investigate the potential of the algorithm to consider both single-cell capture procedures and the impact of “less” rare-cell types. The third dataset refers to the murine data of the Allen Brain Atlas, including more than 1 million cells. For validation purposes only, all datasets have also been analyzed traditionally using common data analysis approaches, such as the Seurat workflow. In comparison to baseline testing without oversampling, our approach identifies rare-cells with a robust precision-recall balance, including a high accuracy and low false positive detection rate. A practical benefit of our algorithm is that it can be readily implemented in other and existing workflows. The code basis in R and Python is publicly available at FairdomHub, as well as GitHub, and can easily be transferred to identify other rare-cell types.
Full Length Research Article STUDIES ON MISCIBILITY OF SODIUM CARBOXY METHYL CELLULOSE/ POLY (ETHYLENE GLYCOL) BLENDS

Miscibility studies have been conducted on solutions of blends of Sodium Carboxy Methyl Cellulose (NaCMC) and Poly (ethyleneglycol ) (PEG) over an extended range of concentrations in water. The Viscosity , Ultrasonic velocity, density, and refractive index of the blends have been measured for different compositions viz., 0/100, 20/80, 40/60, 50/50, 60/40, 80/20 and 100/0 of NaCMC/PEG blends in water at 30 0 C. The interaction parameters such as ∆B, µ and α calculated from viscosity results using Chee and Sun methods indicate that NaCMC/PEG blend is miscible when NaCMC content is more than 50% in the blend. The obtained conclusions have been confirmed by ultrasonic velocity and refractive index results also. The NaCMC/PEG blend films are prepared by solution casting method and are analyzed by Fourier Transform Infrared Spectroscopy, Differential Scanning Calorimetry, X - ray diffraction and Scanning Electron Microscopic techniques that confirmed the semi miscibility nature of this blend.
Co‐optimization of emitter profile and metal grid of selective emitter silicon solar cells

Co‐optimization of the metallization and emitter dopant profile is fully investigated for selective emitter crystalline silicon solar cells. The simulation parameters for the laser doping selective emitter, metallization by plating, silicon nitride passivation, and aluminum back surface field are identified and reached. Internal light flux reflection is also considered in the model. In particular, the influence of the increased light trapping ability of a textured surface on the optimization results is clarified by comparing a cell with a non‐textured surface. In this paper, the optimization results, including the electrical performances of a solar cell are discussed in detail. On the basis of these simulation results, an optimized metallization and emitter dopant profile is proposed. Copyright © 2011 John Wiley & Sons, Ltd.
Preparation, Crystal Structure and Physical Properties of Ternary Compounds (Ln3N)In, Ln: Rare‐Earth Metal.

Abstract The compounds (R3N)In (R=Sc, La–Nd, Sm, Gd–Tm, Lu) were synthesized by arc melting and sintering reactions from the binaries RN and R2In. Combined Rietveld refinements on X-ray and neutron powder diffraction data on the Ce-phase and X-ray diffraction for the other phases reveal the compounds (R3N)In to crystallize in the perovskite structure ((Ce3N)In: Pm 3 m , a=504.89(2) pm; Rietveld: neutron powder diffraction: RF=0.056, RBragg=0.104, X-ray powder diffraction: RF=0.069, RBragg=0.115; refined composition Ce3InN0.92(1), chemical analysis Ce3InN0.91(2)O0.05(1)). Compounds R3In (AuCu3 structure type) are known for R=La–Sm. Nitrogen is able to stabilize this AuCu3-substructure with R=Gd–Tm, Lu and Sc. In measurements of the magnetic susceptibility (Ce, Pr, Nd, Sm, Tb: antiferromagnetic ordering at low temperature) and X-ray absorption spectroscopy at the R-LIII-edges the rare-earth atoms behave like R3+ species in insulating compounds. The electrical resistivity of the Sc, Ce and Nd compounds shows metallic temperature dependence. Chemical bonding was analyzed via LDA-COHP calculations for (La3N)In showing ionic polyhedra NLa6/2 embedded in a metallic matrix.
Borehole Strain Observations Based on a State-Space Model and ApNe Analysis Associated With the 2013 Lushan Earthquake

YRY-4 borehole strainmeters have been installed in Sichuan Province, China, since 2008, aimed at monitoring the crustal activities associated with earthquakes. In this study, data from six YRY-4 strainmeters at the southwestern endpoint of the Longmenshan fault zone were analysed, to study the relationship of tectonic strain changes with the 2013 Lushan earthquake. We developed a state-space model to remove the strain response due to air pressure, solid tides and the changes in the water level to preferentially isolate non-tectonic disturbances. Strain responses to each influencing factor were estimated using the environmental coefficients computed in the state-space model by an adaptive Kalman filter with measurement noise. The results were consistent with the expected response of the strainmeter systems. The corrected strain considered to originate from underground tectonics provides new insights into the changes in the pre-earthquake strain. Approximate negentropy (ApNe) and ${b}$ value were introduced to quantify the probability distribution of the corrected borehole strain and compared with the local seismic activities. The nearest station and two further stations, almost simultaneously recorded short-term ApNe anomalies six to four months before the earthquake. The anomalous region also had a correspondingly low ${b}$ value. Moreover, the anomaly acceleration rates of each station were dependent on the epicentral distances. Further comparison with the strain of random periods illustrated the significance of the extracted anomalies. Our results indicate that the corrected strain may contain seismogenic information and reflect the accelerated strain accumulation of focal areas before the earthquake.
Hybrid Electrothermal Model for Insulator-to- Metal Transition in VO2 Thin Films

Comprehensive model for the insulator to metal phase transition in vanadium dioxide thin film in the presence of external electrical stimulus is proposed. This model divides the film layer into several segments and solves the Joule heating equations due to current flow and heat exchange with the environment and Poole–Frankel equation to obtain carrier concentration in response to the applied voltage, and transition is checked for each cell separately. The model follows the experimental results and exhibits both switching and hysteresis effect in planar structures and ${S}$ -shaped current–voltage characteristics in sandwich metal–insulator–metal structure based on the vanadium dioxide thin film. This model shows that by reducing the vanadium dioxide layer thickness, the electric field-assisted transition plays the dominant role in the transition, and therefore, it is a promising tool for the design and analysis of vanadium dioxide structures with various electrode distances.
Impact of Analogue Switch-Off on Availability of TVWS: A Quantitative Assessment

This paper explores the television white spaces (TVWS) availability in Malawi after the switchover to digital television (TV) broadcasting. Like other countries around the globe, preliminary TVWS availability assessments in the ultrahigh frequency (UHF) band and subsequent deployment of TVWS networks in Malawi was done before the analogue switch-off, and ever since no study has been conducted to assess the impact of the migration on availability of TVWS for Affordable Internet Access (AIA). In this work, aided by the national digital TV plan in the UHF band and spectral measurement campaigns data collected in various locations in areas of Eastern and Southern region of Malawi, we present a thorough analysis of digital TV band occupancy. The study quantifies that almost 78.6% of the UHF band allocated for digital TV transmission is underutilized in a country where 83% percent of the population has no access to the internet due to poor internet infrastructures and high tariffs.
Synthesis and Properties of Multi-Triarylamine-Substituted Carbazole-Based Dendrimers with an Oligothiophene Core for Potential Applications in Organic Solar Cells and Light-Emitting Diodes

In this paper, we report on the synthesis and properties of a novel series of multi-triarylamine-substituted carbazole-based dendrimers G2-OTP(n)-G2 (n = 2−5) with an oligothiophene core. The length of the oligothiophene core varied from 2 to 5 thiophene units. It was found that both the absorption and fluorescence emission peaks red-shifted with increasing oligothiophene core length. As a result, the power conversion efficiencies of the as-fabricated solar cells using the composite of these dendrimers and PCBM as the photoactive layer increased with increasing oligothiophene core length, from 0.04% for G2-DTP-G2 to 0.13% for G2-PTP-G2 under AM 1.5 simulated solar illumination at an irradiation intensity of 100 mW/cm2. After a thermal annealing at 150 °C for 15 min under nitrogen, however, the devices based on the G2-DTP-G2:PCBM blend exhibited the most dramatic improvement and almost best performance, although other devices also showed some improvement. Since only G2-DTP-G2 is the a crystalline material .
MorphFace: A Hybrid Morphable Face for a Robopatient

Physicians use pain expressions shown in a patient's face to regulate their palpation methods during physical examination. Training to interpret patients’ facial expressions with different genders and ethnicities still remains a challenge, taking novices a long time to learn through experience. This letter presents MorphFace: a controllable 3D physical-virtual hybrid face to represent pain expressions of patients from different ethnicity-gender backgrounds. It is also an intermediate step to expose trainee physicians to the gender and ethnic diversity of patients. We extracted four principal components from the Chicago Face Database to design a four degrees of freedom (DoF) physical face controlled via tendons to span $\sim\! 85\%$ of facial variations among gender and ethnicity. Details such as skin colour, skin texture, and facial expressions are synthesized by a virtual model and projected onto the 3D physical face via a front-mounted LED projector to obtain a hybrid controllable patient face simulator. A user study revealed that certain differences in ethnicity between the observer and the MorphFace lead to different perceived pain intensity for the same pain level rendered by the MorphFace. This highlights the value of having MorphFace as a controllable hybrid simulator to quantify perceptual differences during physician training.
The Impact of Internet Socialization on Changing the Professional and Value Orientations of Young People

The Internet is forming a new space of socialization, that contributes to a change in professional and value orientations of youth. The article addresses the cause-and-effect relations of changes in professional and value orientations of young people in the context of Internet socialization. The results of Internet users' surveys conducted by the authors over the past two decades are analyzed in the article.
Energy Transmission of Vortex Beams Through 3rd Order Intensity Dependent Nonlinear Optical Limiters

Third order optical limiting utilizes nonlinear absorption or scatter to preferentially reduce the optical throughput of intense light through a medium. While these processes are dependent on intensity, it is often the transmitted energy or power that needs to be limited to avoid eye, sensor or detector damage. This is problematic when the input is a vortex mode or other higher order Gaussian distributions such as Bessel-Gaussian modes where the relationship between optical power and the on axis intensity is more complicated than for the TEM00 Gaussian mode. Here we show that for higher order Bessel-Gaussian modes that beam power transmission is not equivalent to peak intensity transmission through intensity dependent absorption or scatter based optical limiters. We present a theoretical model and experimental data that demonstrates that the power throughput in these media, increases by 4 and 7 times for n = 1 and 2 Bessel-Gaussian modes, respectively, over that observed when a TEM00 mode is used.
The potential of seaweed liquid fertilizer on the growth and antioxidant enhancement of Helianthus annuus L.

A field experiment was carried out during the chithiraipattam (April-May) in India in 2010 to study the effects of foliar applications of different concentrations of seaweed liquid fertilizer (SLF) of Sargassum wightii on growth, biochemical constituents and antioxidant enzymes of Helianthus annuus L. to explore the possibilities of reducing or avoiding chemical fertilizers and to obtain the highest growth and productive parameters. The foliar spray was given twice in 15days interval at two concentrations (2.5%, 5.0%) of SLF. The aqueous extract of Sargassum wightii was found to promote almost all the parameters such as shoot length, root length, leaf length, leaf breadth, fresh weight, dry weight and number of leaves. The biochemical contents such as chlorophyll a, b, total chlorophyll, carotenoids, carbohydrate, total phenols and antioxidant enzymes such as catalase, peroxidase and glutathione peroxidase (GPX) were also found to be higher in the leaves. Among the two concentrations 2.5% was found to produce better results in almost all the parameters. The results revealed that foliar application of seaweed extract could be a promising option for pollution free non toxic growth enhancement of Helianthus annuus L.
PROCESS CHARACTERISTICS AND FUNCTIONALITY OF SARDINE ( SARDINA PILCHARDUS ) MUSCLE PROTEINS EXTRACTED BY A pH-SHIFT METHOD

The pH-shift method is a recent process used to isolate proteins from animal muscle with good functional properties. It can be used to recover proteins from cheap, underutilized sources and/or process byproducts. In this work, sardine (Sardina pilchardus) muscle proteins were extracted using acidic or alkaline-aided solubilization followed by isoelectric precipitation and compared to the traditional surimi process. This work also reports the comparison between centrifugation and filtration, as means of recovering the precipitated proteins. The highest solubilization of sardine proteins was recorded at pH 2.5 (94%) and 12 (98%), while optimum pH for the isoelectric precipitation of the solubilized proteins in both cases was 6. Protein recovery yields were 600g kg -1 for both acidic and alkaline processes, which are considerably higher than that of the traditional surimi process (400g kg -1 ). When centrifugation was replaced by filtration, protein yields were significantly higher (730g kg -1 for the acidic and 800g kg -1 for the alkaline process), while fat reduction was decreased by 10%compared to the use of centrifugation. The proteins recovered after alkaline solubilization process showed better gelling properties compared to the ones recovered after acidic solubilization. The results of this work clearly show that the process of alkaline solubilization and filtration can successfully be employed to recover proteins with good functional properties from sardine mince.
Biofilm control using chlorine-based disinfectants in model drinking water distribution systems

Model distribution systems (annular reactors) were operated to investigate the biofilm disinfection efficacies of three disinfectants: free chlorine, monochloramine and combination of free chlorine and silver ion. Biofilm cell number, coverage and structure were examined. At the same dosages, monochloramine showed the poorest biofilm disinfection efficiency compared to free chlorine and combination of free chlorine and silver ion. 40 μg/l of Ag + showed positive effect to both two dosages of chlorine (0.5 mg/l and 1 mg/l) to disinfect biofilm bacteria. In addition, combinations of free chlorine and silver ion were found to achieve the highest biofilm coverage reduction, while monochloramine showed the least biofilm removal. Biofilm structure could also be affected by different testing agents.
A Video-Based Method With Strong-Robustness for Vehicle Detection and Classification Based on Static Appearance Features and Motion Features

Vehicle detection and classification plays an important role in intelligent transportation system. Compared with traditional detectors, the detection and classification based on traffic surveillance video shows a huge advantage in its flexibility and continuity. However, to get wide applicability and strong robustness, most current methods focus on improving the accuracy of detectors by adjusting network parameters constantly, or increasing the size of training sets, which challenges the collection and labeling of data, the performance of computers, the scope of application and so on. Moreover, the unique continuity characteristic of the video, which can be used to describe the motion features of vehicle, is often ignored. Take these facts into account, this paper proposed a video-based vehicle detection and classification method, which is based on static appearance features and motion features both. Four detectors of different performance were trained with small training sets, and the designed algorithms for the remove, selection and reorganization of detected objects contribute to obtaining the optimal results of detection and classification. The experiment results show that the proposed method is able to detect and classify vehicles with more than 0.95 accuracy dealing with different road environments.
Comparing Collaborative Filtering and Hybrid based Approaches for Movie Recommendation

This paper analyzes and compares the performance of the Collaborative Filtering and Hybrid based approaches in generating movie recommendations. The Collaborative Filtering approach uses the rating data consisting of two main phases: (1) movie similarity and (2) movie rating prediction. Meanwhile, the Hybrid based approach adds the benefit of a Content-based to the Collaborative Filtering based approach. Thus, it uses both the rating and movie data and is consisting of four main phases: (1) text preprocessing, (2) term weighting, (3) movie clustering, and (4) Collaborative Filtering based approach. Empirical results show that the recommendation performances of both approaches are linear to the size of the movie neighbourhood. However, the Hybridbased approach’s required neighbourhood size is naturally a lot smaller than that of the Collaborative Filtering since the former employs a clustering technique. The performance comparisons show that the Collaborative Filtering based approach always outperforms the Hybrid based at any top-N position in Precision and NDCG metrics. These findings conjecture that the Hybrid approach does not always improve the Collaborative Filtering approach in movie recommendation.
Phonon-plasmon coupled-mode lifetime in semiconductors

Raman scattering measurements of the lifetime of hot phonons in GaN show a decrease with increasing electron concentration. Density-dependent lifetimes have also been deduced from noise measurements of AlGaN/GaN channels. We suggest that the results from Raman scattering can be understood by the frequency dependence of the anharmonic interaction for coupled modes and that the results from noise measurements can be understood qualitatively by the anharmonic interaction plus the migration of coupled modes.
Cross-validation of machine learning algorithms for malware detection using static features of Windows portable executables: A Comparative Study

With the expansion in the notoriety of modern technology, cyber-attacks have also increased. Traditional techniques to distinguish between malware and benign files are usually signature-based or behavior-based; the following methods can be less accurate and resource hungry. A robust technique is needed which is more efficient and takes less time as compared to traditional techniques. Machine learning can play an important role in this scenario due to its predictive capabilities based upon training. In this study, we use existing machine learning algorithms for classification and clustering using static features of malware-benign portable executables. Cross-validation is performed using two datasets; a publicly available dataset and a self-collected dataset. The self-collected dataset comprises 21,486 samples, whereas, the publicly available dataset comprises 138,047 samples. In the case of supervised classification, accuracies were observed to be above 80% whereas in the case of unsupervised F1-score above 0.9 was observed.
Learning Goal Conditioned Socially Compliant Navigation From Demonstration Using Risk-Based Features

One of the main challenges of operating mobile robots in social environments is the safe and fluid navigation therein, specifically the ability to share a space with other human inhabitants by complying with the explicit and implicit rules that we humans follow during navigation. While these rules come naturally to us, they resist simple and explicit definitions. In this letter, we present a learning-based solution to address the question of socially compliant navigation, which is to navigate while maintaining adherence to the navigational policies a person might use. We infer these policies by learning from human examples using inverse reinforcement learning techniques. In particular, this letter contributes an efficient sampling-based approximation to enable model-free deep inverse reinforcement learning, and a goal conditioned risk-based feature representation that adequately captures local information surrounding the agent. We validate our approach by comparing against a classical algorithm and a reinforcement learning agent and evaluate our feature representation against similar feature representations from the literature. We find that the combination of our proposed method and our feature representation produce higher quality trajectories and that our proposed feature representation plays a critical role in successful navigation.