Miracle-dz/UniFAR-FTUs huggingface dataset:
Everyday Life of Slum Children: A Case Study from Education Perspective

Every year, the city of Pune attracts migrant workers due to urbanization, and these migrants form residential pockets called slums. Today, around 40% of Pune's population lives in urban slums, around 11% of children, who have little or no access to education with the everyday hand-to-mouth struggle for survival. This study explores the lives of slum children and their educational conditions. Three case studies were conducted with three slums from uptown areas of Pune. Focus group discussions, interviews, and visual survey methods were employed, leading to qualitative analysis. Analysis threw light on the everyday challenges faced by slum children in accessing education. The visual studies imply the need for architectural intervention. The findings also suggest policy implications towards the provision of education towards the betterment of the lives of slum children. Working and learning are the two social processes; without breaking the legal structures on child labor, children working within the home as domestic labor or in the household enterprise is a common occurrence in urban centers, particularly among those who are household income is derived from the informal sector and who have lower income levels. Working modes and times differ depending on the situation. Owing to the size of India's informal economy and attempts to reduce child labor trafficking, a strong emphasis has been placed on developing and implementing social policies that address child labor.
Agreement in Walking Speed Measured Using Four Different Outcome Measures: 6-Meter Walk Test, 10-Meter Walk Test, 2-Minute Walk Test, and 6-Minute Walk Test

Background: Walking speed is considered the sixth vital sign because it is a valid, reliable, and sensitive measure for assessing functional status in various populations. Purpose: The current study assessed agreement in walking speed using the 6-meter walk test, (6MWT) 10-meter walk test (10MWT), 2-minute walk test (2minWT), and 6-minute walk test (6minWT). We also determined differences in walking speed. Methods: Seventy-three healthy adults (44 females, 29 males; mean [SD] age=31.36 [10.33] years) participated. Lafayette Electronic timing devices measured walking speed for the 6MWT and 10MWT. Measuring wheels and stopwatches measured walking distance and speed for the 2minWT and 6minWT. Participants completed 1 trial, and all tests were administered simultaneously. Results: The intraclass correlation coefficient (2, 4) for the different measures of walking speed was excellent at 0.90 (95% confidence intervals, 0.86-0.93). The correlation was 0.95 between 6MWT and 10MWT, 0.94 between 2minWT and 6minWT, 0.67 between 6MWT and 2minWT, 0.63 between 10MWT and 2minWT, and 0.59 between 10MWT and 6minWT (all p < 0.05). No differences in walking speed were found between the four walking tests. Conclusion: Administration of any of the four walking tests provided reliable measurement of walking speed.
From Interseismic Deformation With Near‐Repeating Earthquakes to Co‐Seismic Rupture: A Unified View of the 2020 Mw6.8 Sivrice (Elazığ) Eastern Turkey Earthquake

The East Anatolian Fault (EAF) is a left‐lateral transform fault accommodating the relative motion between the Anatolian and Arabian plates. On January 24, 2020, Mw6.8 Sivrice (Elazığ) earthquake is the largest event that occurred along the EAF since the nineteenth century. The earthquake provides a unique opportunity to capture a critical stage of the seismic cycle from the interseismic deformation to co‐seismic rupture. In this study, we examine the relationship between the interseismic fault activity and co‐seismic behavior of the earthquake. A kinematic model of the earthquake obtained from strong‐motion, GNSS and teleseismic waveforms along with static displacements from GNSS and InSAR data shows that the mainshock ruptured only 45 km of the 95 km long Sivrice‐Pütürge segment. Rupture initiated adjacent to the interseismically weakly coupled northeastern section and propagated unilaterally toward southwest with a rupture velocity of ∼2.5 km/s, stopping ∼30 km before the southwestern segment boundary. The earthquake did not generate any surface offsets. We identified 4 long‐term near‐repeating earthquake clusters beneath the highest co‐seismic slip zone adjacent to the northeastern creeping section. The mainshock was dynamically triggered by a M ∼ 5.4 foreshock located within the zone of near‐repeating earthquakes. We suggest that creep along the weakly coupled section of the fault loaded the neighboring locked section leading to the repeating earthquakes below the locked zone. The earthquake partially ruptured a fault segment characterized by high rate of diffuse seismicity, structural complexities and heterogeneous coupling, leading to a source characterized by a complex source time function with relatively slow rupture velocity.
Polyphasic Characterization of Microbiota of “Mastredda”, a Traditional Wooden Tool Used during the Production of PDO Provola dei Nebrodi Cheese

The biofilms of the wooden tables used for the acidification of the curd were investigated for PDO Provola dei Nebrodi cheese, a traditional stretched cheese made in eastern Sicily (southern Italy) from raw cows’ milk. To this purpose the wooden tables of four dairy facilities were analysed for their microbiota by scanning electron microscopy (SEM) analysis and a combined culture-independent and -dependent microbiological approach. SEM inspection showed an almost continuous biofilm formation. MiSeq Illumina analysis identified 8 phyla, 16 classes, 25 orders, 47 families and 50 genera. Corynebacterium, Bifidobacterium and lactic acid bacteria (LAB) were detected in all samples. In particular, the LAB genera detected on all wooden tables were Lactobacillus, Streptococcus and Lactococcus. LAB dominated the surfaces of all wooden tables with levels higher than 7.0 Log CFU/cm2. In particular, the LAB found at the highest levels were mesophilic cocci. Coagulase positive staphylococci, Salmonella spp. , Listeria monocytogenes and Shiga-toxigenic Escherichia coli were never detected. Twenty-seven dominating LAB strains were identified within the genera Enterococcus, Lactobacillus, Lacticaseibacillus, Lactiplantibacillus, Levilactobacillus, Lactococcus, Leuconostoc, Pediococcus and Streptococcus. This work showed that the wooden table used during the production of PDO Provola dei Nebrodi cheese is a safe system and a microbiologically active tool.
Luteolin: A Potential Multiple Targeted Drug Effectively Inhibits Diabetes Mellitus Protein Targets

Background: Diabetes is a significant health problem that has reached worrisome proportions: almost half of the world's population now has diabetes. Diabetes mellitus, or diabetes, is a severe, long-term disease in which a person's blood glucose levels are elevated due to their body's inability to make any or enough insulin, or to properly utilise the insulin that it does produce. The chemicals extracted from medicinal plants were shown to be both safer and more bioactive than manufactured medicines. Objective: The goal of this research was to use molecular docking to find possible binding affinities of luteolin, a phytocompound from Rumex vesicarius L, to five target proteins, in order to find the lead molecule against diabetes. Methodology: One chemical was isolated from Rumex vesicarius L. leaves in this research. The binding affinity of the complexes was calculated using molecular docking studies. The docking procedure was carried out using AutoDock Tools 1.5. 6, which brought the ligand together with the target proteins. Results: The binding energies of Luteolin with major Glutamine-fructose-6-phosphate amido transferase (GFAT1), Pancreatic α-Amylase, Forkhead box protein O1(FOX01), α--glucosidase, and Dipeptidyl peptidase-4 (DPP-4) were determined to be -6.89, -6.80, -6.36, -9.35, and -7.72 kcal. Conclusion: Our findings suggest that luteolin can target not only α--glucosidase but also DPP4 and other targets, suggesting that they may be used as type 2 diabetes mellitus inhibitors. We believe that this phytochemical, luteolin, may be utilised in preclinical studies as an anti-diabetic drug to combat diabetes mellitus.
A Power Flow Tracing Method Based on Power Electronic Signaling for P2P Electricity Trading in DC Microgrids

This article proposes a novel power flow tracing method based on power electronic signaling for peer-to-peer (P2P) electricity trading in dc microgrids. It employs a superimposed low-frequency sinusoidal carrier to trace dc power flows according to the bus port impedance characteristics of power converters. In order to support fair and accurate P2P trading, source-to-load power signaling (S2LPS) and source-to-source power verification (S2SPV) methods are presented. Through S2LPS, the P2P dc power flow from a specific distributed source (DS) to a power load (PL) is determined by detecting the carrier's active power at the PLs bus port. The same carrier is used to check the actual output power of the DS by S2SPV. By implementing S2LPS and S2SPV, the power flows of the system are traced, recorded, and verified by each DS and PL. Accurate power flow tracing is achieved on the physical layer, providing reliable data for P2P electricity trading. The principles of the proposed method are deduced in detail. Furthermore, the modifications to the control loops of DSs and PLs are depicted for implementations in dc microgrids. Finally, a 2.5 kW experimental platform is built to validate the correctness and feasibility of the proposed method.
On the Direction of Time: From Reichenbach to Prigogine and Penrose

The question why natural processes tend to flow along a preferred direction has always been considered from within the perspective of the Second Law of Thermodynamics, especially its statistical formulation due to Maxwell and Boltzmann. In this article, we re-examine the subject from the perspective of a new historico-philosophical formulation based on the careful use of selected theoretical elements taken from three key modern thinkers: Hans Reichenbach, Ilya Prigogine, and Roger Penrose, who are seldom considered together in the literature. We emphasize in our analysis how the entropy concept was introduced in response to the desire to extend the applicability of the Second Law to the cosmos at large (Reichenbach and Penrose), and to examine whether intrinsic irreversibility is a fundamental universal characteristics of nature (Prigogine). While the three thinkers operate with vastly different technical proposals and belong to quite distinct intellectual backgrounds, some similarities are detected in their thinking. We philosophically examine these similarities but also bring into focus the uniqueness of each approach. Our purpose is not providing an exhaustive derivations of logical concepts identified in one thinker in terms of ideas found in the others. Instead, the main objective of this work is to stimulate historico-philosophical investigations and inquiries into the problem of the direction of time in nature by way of crossdisciplinary examinations of previous theories commonly treated in literature as disparate domains.
KCB-Net: A 3D knee cartilage and bone segmentation network via sparse annotation

Knee cartilage and bone segmentation is critical for physicians to analyze and diagnose articular damage and knee osteoarthritis (OA). Deep learning (DL) methods for medical image segmentation have largely outperformed traditional methods, but they often need large amounts of annotated data for model training, which is very costly and time-consuming for medical experts, especially on 3D images. In this paper, we report a new knee cartilage and bone segmentation framework, KCB-Net, for 3D MR images based on sparse annotation. KCB-Net selects a small subset of slices from 3D images for annotation, and seeks to bridge the performance gap between sparse annotation and full annotation. Specifically, it first identifies a subset of the most effective and representative slices with an unsupervised scheme; it then trains an ensemble model using the annotated slices; next, it self-trains the model using 3D images containing pseudo-labels generated by the ensemble method and improved by a bi-directional hierarchical earth mover's distance (bi-HEMD) algorithm; finally, it fine-tunes the segmentation results using the primal-dual Internal Point Method (IPM). Experiments on four 3D MR knee joint datasets (the SKI10 dataset, OAI ZIB dataset, Iowa dataset, and iMorphics dataset) show that our new framework outperforms state-of-the-art methods on full annotation, and yields high quality results for small annotation ratios even as low as 10%.
Promoting the Emergence of Behavior Norms in a Principal–Agent Problem—An Agent-Based Modeling Approach Using Reinforcement Learning

One of the complexities of social systems is the emergence of behavior norms that are costly for individuals. Study of such complexities is of interest in diverse fields ranging from marketing to sustainability. In this study we built a conceptual Agent-Based Model to simulate interactions between a group of agents and a governing agent, where the governing agent encourages other agents to perform, in exchange for recognition, an action that is beneficial for the governing agent but costly for the individual agents. We equipped the governing agent with six Temporal Difference Reinforcement Learning algorithms to find sequences of decisions that successfully encourage the group of agents to perform the desired action. Our results show that if the individual agents’ perceived cost of the action is low, then the desired action can become a trend in the society without the use of learning algorithms by the governing agent. If the perceived cost to individual agents is high, then the desired output may become rare in the space of all possible outcomes but can be found by appropriate algorithms. We found that Double Learning algorithms perform better than other algorithms we used. Through comparison with a baseline, we showed that our algorithms made a substantial difference in the rewards that can be obtained in the simulations.
Assessing Radiometric Calibration of FY-4A/AGRI Thermal Infrared Channels Using CrIS and IASI

The quality of thermal infrared (TIR) radiances from the FY-4A advanced geostationary radiation imager (AGRI) and their derived products is very important for weather predictions. The demand for more accurate weather forecasting models is increasing, so it is necessary to evaluate and improve the calibration accuracy of AGRI. This study aims to evaluate the AGRI TIR radiometric calibration accuracy by comparing two well-calibrated hyperspectral radiometers, the cross-track infrared sounder (CrIS), and the infrared atmospheric sounding interferometer (IASI). Most of the AGRI TIR channels are calibrated with an absolute brightness temperature (Tb) bias less than 0.5 K currently. The Tb bias of AGRI and CrIS\IASI depends on the target temperature, and it is smaller and more stable for higher Tb and increases for lower Tb. CH_14 shows the largest Tb bias (−0.53 K) and standard deviation (0.64 K), CH_10 and CH_11 record slightly positive Tb biases, and the other four channels exhibit negative Tb biases. The diurnal mean Tb bias is very consistent except for CH_11, which varies greatly among different time bins. The Tb bias of CH_09 is very consistent after the calibration update in February 2018. CH_10 shows a gradual bias decrease with bias from 1.0 to 0.6 K. CH_11 shows a gradual bias decrease with bias from 0.4 to 0.1 K with large fluctuations. CH_14 shows a gradual bias decrease with large fluctuation and like CH_11. CH_12 and CH_13 exhibit seasonal variations where the Tb bias reaches its maximum around June and minimum around February. In general, the Tb bias shows different spatial patterns in different channels and CH_11 shows obvious spatial distribution characteristics that is monthly dependent.
16.3 W Peak-Power Pulsed All-Diode Laser Based Multi-Wavelength Master-Oscillator Power-Amplifier System at 964 nm

An all-diode laser-based master oscillator power amplifier (MOPA) configuration for the generation of ns-pulses with high peak power, stable wavelength and small spectral line width is presented. The MOPA emits alternating at two wavelengths in the spectral range between 964 nm and 968 nm, suitable for the detection of water vapor by absorption spectroscopy. The monolithic master oscillator (MO) consists of two slightly detuned distributed feedback laser branches, whose emission is combined in a Y-coupler. The two emission wavelengths can be adjusted by varying the current or temperature to an absorption line and to a non-absorbing region. The power amplifier (PA) consists of a ridge-waveguide (RW) section and a tapered section, monolithically integrated within one chip. The RW section of the PA acts as an optical gate and converts the continuous wave input beam emitted by the MO into a sequence of short optical pulses, which are subsequently amplified by the tapered section to boost the output power. For a pulse width of 8 ns, a peak power of 16.3 W and a side mode suppression ratio of more than 37 dB are achieved at a repetition rate of 25 kHz. The measured spectral width of 10 pm, i.e., 0.1 cm−1, is limited by the resolution of the optical spectrum analyzer. The generated pulses emitting alternating at two wavelengths can be utilized in a differential absorption light detection and ranging system.
Input-Aware Sparse Tensor Storage Format Selection for Optimizing MTTKRP

Canonical polyadic decomposition (CPD) is one of the most common tensor computations adopted in many scientific applications. The major bottleneck of CPD is matricized tensor times Khatri-Rao product (MTTKRP). To optimize the performance of MTTKRP, various sparse tensor formats have been proposed such as CSF and HiCOO. However, due to the spatial complexity of the tensors, no single format fits all tensors. To address this problem, we propose SpTFS, a framework that automatically predicts the optimal storage format for an input sparse tensor. Specifically, SpTFS leverages a set of sampling methods to lower the sparse tensor to fixed-sized matrices and sparsity features. In addition, SpTFS adopts both supervised learning based and unsupervised learning based methods to predict the optimal sparse tensor storage formats. For supervised learning, we propose TnsNet that combines convolution neural network (CNN) and the feature layer, which effectively captures the sparsity patterns of the input tensors. Once trained, the TnsNet can be used with either density or histogram representation of the input tensor for optimal format prediction. Whereas for unsupervised learning, we propose TnsClustering that consists of a feature encoder using convolutional layers and fully connected layers, and a K-means++ model to cluster sparse tensors for optimal tensor format prediction, without massively profiling on the hardware platform. SpTFS can use the above two models to predict the optimal tensor storage format for accelerating MTTKRP accurately. The experimental results show that both TnsNet and TnsClustering can achieve higher prediction accuracy and performance speedup compared to the state-of-the-art works.
Assessment of phonon scattering-related mobility in β-Ga2O3

The momentum scattering time for electron–phonon interaction in β-Ga2O3 was derived within the relaxation time approximation considering all infra-red active optical modes. A first principle calculation was applied to separately obtain the scattering rates due to polar and non-polar phonon–electron interactions, and then spherically averaged coupling coefficients for each polar optical mode were calculated. The method was tested to analyze, in the framework of the relaxation time approximation, transport data in semiconductors having different optical phonons. This approach can be reliably applied if the band may be considered as isotropic. Hall density and mobility curves were fitted simultaneously with the same parameters, after Hall-to-drift data conversion through a Hall scattering factor calculated self-consistently within the routine. In the theoretical mobility calculations, both polar and non-polar phonon interactions were considered besides impurity scattering. The Farvacque correction was included in the momentum scattering rate for electron interaction with the optical phonons, and its effect on mobility calculation is critically discussed. Hall transport data of β-Ga2O3 taken from the literature were fitted to test the approach, and good agreement between the experimental and calculated mobilities was obtained.
Using coverage-based rarefaction to infer non-random species distributions

Understanding how species are non-randomly distributed in space, as well as how the resulting spatial structure of diversity responds to ecological, biogeographic and anthropogenic drivers is a critical piece of the biodiversity puzzle. However, most metrics that quantify the spatial structure of diversity (i.e., community differentiation), such as Whittaker’s classical β-diversity metric are influenced by sampling effects. As a result, these measures are influenced by species pool size, species abundance distributions and numbers of individuals. Null models have been proposed to evaluate the degree of differentiation among communities due to spatial structuring relative to that expected from sampling effects. However, to date, these null models do not accommodate the influence of sample completeness (i.e. the proportion of the species pool in the sample). Here, we develop an approach that makes use of individual- and coverage-based rarefaction and extrapolation. Using spatially explicit simulations, we show that our derived metric, βC, captures changes in intraspecific aggregation independently of changes in the species pool size. We then provide two case studies examining spatial structure in forest plots spanning latitudinal gradients: (1) a re-analysis of the “Gentry” plot dataset, and (2) comparing a high diversity plot in Barro Colorado Island, Panama with a low diversity plot in Harvard Forest, Massachusetts, USA. We find no evidence for systematic changes in spatial structure with latitude in these datasets. As it is rooted in biodiversity sampling theory and explicitly controls for sample completeness, our approach represents an important advance over existing null models for spatial aggregation. Potential applications of the approach range from better descriptors of biogeographic diversity patterns to the consolidation of local and regional diversity trends in the current biodiversity crisis. Open research statement The novel code for the calculation of βC can be found in supplementary material S4. Empirical data sets utilized for this research are as follows: Phillips & Miller (2002), Orwig et al. (2015), Condit et al. (2019). Our research repository including the novel code is also available at https://github.com/t-engel/betaC and will be uploaded to Zenodo upon acceptance of this manuscript.