Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Non-isolated Bi-directional DC-DC Converter for Battery Charging Application

High efficiency and uninterruptible power supplies are the main factors aiding to a lot of attention for bidirectional DC/DC converters. In this paper a bi-directional DC/DC converter (BDC) for battery charging applications is presented. The converter configuration has provided a way to charge between the batteries of two different energy storage systems (ESS). In this work a non-isolated bi-directional DC/DC converter is designed which possess high efficiency with respect to the isolated topology of bidirectional DC/DC converter. The controlling techniques discussed in this paper is used to charge the battery in the bidirectional fashion for which the BDC is employed. MATLAB/Simulink platform is used to perform the simulations. The simulation end results ensures the implementation of bi-directional charging of the batteries.
Preparation and Release of pH-Sensitive β-Cyclodextrin Derivative Micelles Loaded with Paclitaxel

In this paper, a new amphiphilic mono-6-β-cyclodextrin octadecylimine (6-β-CD-N-ODMA) copolymer was synthesized based on β-cyclodextrin and octadecylamine, which can self-assemble to form polymeric micelles. Drug-loaded micelles (a new drug carrier) were obtained using 6-β-CD-N-ODMA and paclitaxel (PTX) by the dialysis method. Orthogonal experiments were used to optimize the preparation method of the drug-loaded micelles. The drug-loading content of the carrier prepared by the optimized method was 1.97%. The physicochemical properties of blank micelles and drug-loaded micelles were evaluated by the fluorescence probe method, infrared spectra, dynamic light scattering, and scanning electron microscopy. The release properties of the carrier were investigated. The carrier has good pH sensitivity and the cumulative release rate after 96 h was 88% in PBS (pH = 5.0). The Ritger–Peppas equation is the optimal model for PTX released at pH 5.0, implying that the hydrolysis effect of 6-β-CD-N-ODMA is the main reason for PTX release. The results indicate that the developed carrier can increase the solubility of PTX and possess potential for increased clinical efficacy of PTX.
The complete chloroplast genome of Utricularia tenuicaulis Miki (Lentibulariaceae) isolated in Korea

Abstract Utricularia tenuicaulis Miki 1935 is an aquatic carnivorous plant species found in East Asia including Korea and Japan. In this study, the chloroplast genome of U. tenuicaulis was successfully sequenced. The assembled genome (153,976 bp; GC ratio, 37.0%) contains four subregions, with the large single copy (LSC; 84,596 bp; 34.9%) and small single copy (SSC; 17,946 bp; 30.5%) regions separated by 25,718 bp of inverted repeat regions (42.7%), and includes 126 genes (81 protein-coding genes, 8 rRNAs, and 37 tRNAs). Phylogenetic analyses based on the whole-chloroplast genomes of 18 species, including 17 Lentibulariaceae species and one outgroup species, suggest a close relationship between U. tenuicaulis and Utricularia macrorhiza Leconte 1824. A comparison of genomic variation between U. tenuicaulis and U. macrorhiza confirmed the validity of the specific discrimination of U. tenuicaulis.
Being and becoming beginning military leaders: Implications for leadership learning

ABSTRACT The purpose of the study is to describe junior military officers’ leadership development experiences and to draw implications for leadership learning in their professional development. The research uses a systematic grounded theory design. Through in-depth interviews of 19 military officers, the data were coded and analyzed with a paradigm model that was developed to describe the development of military officers’ experiences as leaders. The findings show that military leadership development is a process that is defined by the experiences of establishing oneself as a vocational leader, developing confidence in leadership skills, and leading with mission clarity and genuine concern for their “subordinates. ” The results reinforce the notion that leadership development is a continuous learning process beyond formal program and other transient events. Results also imply that fundamental assumptions for formal leadership development programs must be conceptualized and conceived as a process of “being, becoming, and belonging. ” This non-positivist empirical study answers the call for more qualitative and interpretive approaches in leadership development research and contribute to the body of knowledge of leadership learning in military leadership development.
Dynamic AD of GPU Broadcast Kernels

We show how forward-mode automatic differentiation (AD) can be employed within larger reverse-mode computations to dynamically differentiate broadcast operations in a GPU-friendly manner. Our technique fully exploits the broadcast Jacobian’s inherent sparsity structure, and unlike a pure reverse-mode approach, this “mixed-mode” approach does not require a backwards pass over the broad-casted operation’s subgraph, obviating the need for several reverse-mode-speciﬁc programmability restrictions on user-authored broadcast operations. Most notably, this approach allows broadcast fusion in primal code despite the presence of data-dependent control ﬂow. We discuss an experiment in which a Julia implementation of our technique outperformed pure reverse-mode TensorFlow and Julia implementations for differentiating through broadcast operations within an HM-LSTM cell update calculation. 2
Amaging: Acoustic Hand Imaging for Self-adaptive Gesture Recognition

A practical challenge common to state-of-the-art acoustic gesture recognition techniques is to adaptively respond to intended gestures rather than unintended motions during the real-time tracking on human motion flow. Besides, other disadvantages of under-expanded sensing space and vulnerability against mobile interference jointly impair the pervasiveness of acoustic sensing. Instead of struggling along the bottlenecked routine, we innovatively open up an independent sensing dimension of acoustic 2-D hand-shape imaging. We first deductively demonstrate the feasibility of acoustic imaging through multiple viewpoints dynamically generated by hand movement. Amaging, hand-shape imaging triggered gesture recognition, is then proposed to offer adaptive gesture responses. Digital Dechirp is novelly performed to largely reduce computational cost in demodulation and pulse compression. Mobile interference is filtered by Moving Target Indication. Multi-frame macro-scale imaging with Joint Time-Frequency Analysis is performed to eliminate image blur while maintaining adequate resolution. Amaging features revolutionary multiplicative expansion on sensing capability and dual dimensional parallelism for both hand-shape and gesture-trajectory recognition. Extensive experiments and simulations demonstrate Amaging’s distinguishing hand-shape imaging performance, independent from diverse hand movement and immune against mobile interference. 96% hand-shape recognition rate is achieved with ResNet18 and 60× augmentation rate.
Identification of Cigarette Smoking-Related Novel Biomarkers in Lung Adenocarcinoma

Objective The aims of this study were to screen the gene mutations that are able to predict the risk of cigarette smoking-related lung adenocarcinoma (LUAD) and to evaluate its prognostic significance. Methods Clinical data and genetic information were retrieved from the TCGA database, and the patients with LUAD were divided into three groups including never smoking, light smoking, and heavy smoking according to cigarette smoking dose. Differentially mutated genes (DMGs) of each group were analyzed. At the same time, the function of DMGs in three smoking groups was evaluated by GO function and KEGG pathway analysis. The driver genes and protein variation effect of DMGs were performed to further screen key genes. The survival characteristics of the gene expression and mutation of those genes were analyzed and plotted to visualize by the Kaplan-Meier model. Result The DMGs for different smoking doses were identified. The driver and deleterious mutation in the DMGs were screened and gene interaction network was constructed. The DMGs with driver mutations and deleterious mutations that were associated with the overall survival in the heavy smoking patients were considered as the candidate genes for novel markers of smoking-related LUAD. The final novel risk factor gene was identified as MYH7 and the high express of MYH7 in LUAD correlation with patients' gender, lymph node metastasis, T stage, and clinical stage. Conclusions In summary, it can be concluded that MYH7 is a novel biomarker for heavy smoking-related LUAD and it is significantly correlated with the prognosis of lung cancer and is related to the clinical characteristics of lung cancer.
MOLECULAR RESPONSES OF HEAT STRESS DURING EARLY EMBRYONIC DEVELOPMENT AND ALLEVIATION STRATEGIES

It is well-known that exposure of female farm animals to heat elevation negatively affects all biological activities required to establish pregnancy. The reduction in pregnancy rate during the hot season can approach 50% in dairy cows and 60% in dairy buffaloes. Indeed, earlier investigations done in buffalo indicated seasonal fluctuations of oocyte quality and most studies confirmed a significant reduction in morphological oocytes quality when recovered during hot season. In vivo studies have reported a clear reduction in meiotic maturation of oocytes exposed to heat stress due to decreased blood flow to reproductive tract, low progesterone level and increased glucocorticoids profile. Buffalo oocytes recovered during summer had a lower percentage of nuclear maturation in vitro (42.9%) compared to those collected in winter (85%). Heat shock at 42 °C for 6 hours during in vitro maturation of camel oocytes significantly decreased the polar body extrusion rate (20.7%) compared to control group (32.3%). At the cellular level, decreased nuclear maturation during heat stress was coupled with reduction in mitochondrial activity, protein biosynthesis and impairment of cellular microstructure system organizing nuclear progression to accomplish maturation such as spindle formation, microfilament and microtubule distribution. Heat-induced alterations in cytoplasmic as well as nuclear maturation were coupled with down-regulation of oocyte transcripts such as GDF9, POU5F1, and C-MOS and genes involved in metabolism (GLUT1) and antioxidant defense (SOD2) that regulate maturation process and preimplantation development. These cellular and molecular defects led to compromising early cleavage and blastocyst formation. Blastocyst rate was lower (42%) for camel oocytes exposed to heat shock compared with control counterparts (48%). The rate of developed buffalo blastocyst was lower during summer (13%) than winter (28.3%) which explained by high rate of chromosome abnormalities and alteration of genes regulating key molecular processes that compromise viability of embryos. Providing females farm animals with optimum management system including housing is the first strategy to reduce environmental heat load. Changing composition of animal feeds is a second possible way to alleviate heat stress. Genetic selection for heat tolerance is long term breeding goal with continuous global warming that ensure good productive as well as reproductive performance.
High-Voltage Pulse Generators for Electroporation Applications: A Systematic Review

In recent years, the use of electroporation process has attracted much attention, due to its application in various industrial and medical fields. Electroporation is a microbiology technique which creates tiny holes in the cell membrane by the applied electric field. The electroporation process needs high-voltage pulses to provide the required electric field. To generate high-voltage pulses, a pulse generator device must be used. High-voltage pulse generators can be mainly divided into two major groups: Classical pulse generators and power electronics-based pulse generators. As their name suggests, the first group is associated with the primary and elementary pulse generators like Marx generators, and the second group is associated with the pulse generators that have been updated with the advancement of power electronics like Modular Multilevel Converters. These two major groups are also divided into several subgroups which are reviewed in detail in this paper. This study reviews the literature presented in the field of pulse power and pulse generators proper for the electroporation process and addresses their strengths and weaknesses. Several tables are provided to highlight and discuss the characteristics of each subgroup. Finally, a comparative study among different groups of pulse generators is performed which is followed by a classification performance analysis.
Analysis of Extended Information Provided by Bluetooth Traffic Monitoring Systems to Enhance Short-Term Level of Service Prediction

Bluetooth monitoring systems (BTMS) have opened a new era in traffic sensing, providing a reliable, economical, and easy-to-deploy solution to uniquely identify vehicles. Raw data from BTMS have traditionally been used to calculate travel time and origin–destination matrices. However, we could extend this to include other information like the number of vehicles or their residence times. This information, together with their temporal components, can be applied to the complex task of forecasting traffic. Level of service (LOS) prediction has opened a novel research line that fulfills the need to anticipate future traffic states, based on a standard link-based variable, accepted for both researchers and practitioners. In this paper, we incorporate BTMS’s extended variables and temporal information to an LOS classifier based on a Random Undersampling Boost algorithm, which is proven to efficiently respond to the data unbalance intrinsic to this problem. By using this approach, we achieve an overall recall of 87.2% for up to 15-min prediction horizons, reaching 96.6% predicting congestion, and improving the results for the intermediate traffic states, especially complex given their intrinsic instability. Additionally, we provide detailed analyses on the impact of temporal information on the LOS predictor’s performance, observing improvements up to a separation of 50 min between last features and prediction horizons. Furthermore, we study the predictor importance resulting from the classifiers to highlight those features contributing the most to the final achievements.
Unsupervised depth estimation for ship target based on single view UAV image

ABSTRACT The goal of depth estimation is to obtain the depth image which reflects the distance between the object and the camera point. Depth image can provide depth information for tasks, such as three-dimensional (3D) reconstruction and distance perception. With the development of the environment perception research of the unmanned ship and unmanned aerial vehicle (UAV), depth estimation has been widely used in the field of water transportation. However, the research of ship depth estimation based on monocular images has just started, and there is no unsupervised deep learning depth estimation method for ship target based on single view UAV image. This paper proposes an unsupervised deep learning ship depth estimation method based on single view UAV images. Firstly, the realistic rendering software is used to construct a new ship training dataset with simple backgrounds and regular lighting conditions. Secondly, based on the differentiable rendering framework, a knowledge distillation depth estimation network is designed to train a student network with much smaller number of model parameters. Finally, the ship depth estimation network is obtained through unsupervised training. The experiment results show that the designed knowledge distillation depth estimation network can generate better depth estimation results compared with the current state-of-the-art (SOTA) method, and the weight file size of our model is smaller.
EVALUATION OF FORAGE TURNIP + CEREAL MIXTURES FOR FORAGE YIELD AND QUALITY TRAITS

The most researches in temperate areas has focused mixtures of spring cereals with forage turnip. In this study, forage turnip “FT” with barley “B”, wheat “W” and oat “O” intercropping at different seed rates (100:0%, 75+25%, 50+50%, and 25+75%) were examined for hay yield, protein yield, relative feed value (RFV), condensed tannin, total phenolic, total flavonoid, and mineral contents (K, P, Ca, and Mg) 2019 and 2020 years. The experiment was arranged as a Randomized Complete Block Design with three replications in Bilecik-Turkey. In combined years, the hay yield was ranged between 5.45-10.27 t ha-1. The protein yield was the highest in alone forage turnip (1.43 t ha-1), 75FT+25B% (1.72 t ha-1), 75FT+25O% (1.72 t ha-1), 50FT+50B% (1.49 t ha-1) and 50FT+50O% (1.80 t ha-1). The condensed tannin content was ranged between 1.82-2.83%. The highest RFV was observed in 25FT+75O% (136.29) and 50FT+50O% (125.42) mixtures. As a result, showed that intercropping forage turnip with barley and oat improved the yield and quality of the hay compared to their monocrops in the present study. Accordingly, forage turnip with barley and oat at 75+25% and 50+50% seed rates exhibited the best results regarding forage yield and quality in the Bilecik ecological conditions.
The role of entanglement in work extraction

We consider reversible work extraction from identical quantum batteries. From an ensemble of individually passive states, work can be produced only via global unitary (and thus entangling) operations. However, we show here that there always exists a method to extract all possible work without creating any entanglement, at the price of generically requiring more operations (i.e. additional time). We then study faster methods to extract work and provide a quantitative relation between the amount of generated multipartite entanglement and extractable work. Our results suggest a general relation between entanglement generation and the power of work extraction.
Women's Estrus and Extended Sexuality: Reflections on Empirical Patterns and Fundamental Theoretical Issues

How do women's sexual interests change across their ovulatory cycles? This question is one of the most enduring within the human evolutionary behavioral sciences. Yet definitive, agreed-upon answers remain elusive. One empirical pattern appears to be robust: Women experience greater levels of sexual desire and interest when conceptive during their cycles. But this pattern is not straightforward or self-explanatory. We lay out multiple possible, broad explanations for it. Based on selectionist reasoning, we argue that the conditions that give rise to sexual interests during conceptive and non-conceptive phases are likely to differ. Because conceptive and non-conceptive sex have distinct functions, the sexual interests during conceptive and non-conceptive phases are likely to have different strategic ends. We discuss provisional evidence consistent with this perspective. But the exact nature of women's dual sexuality, if it exists, remains unclear. Additional empirical research is needed. But perhaps more crucially, this topic demands additional theory that fruitfully guides and interprets future empirical research.
Osteoporosis – an increasingly important issue for both young and aging citizens of Malaysia

In both sexes, peak bone mineral density (BMD) occurs in early adulthood.1 Thereafter, there is a gradual decrease in BMD which is hardly noticeable until the middle years, and which in a significant proportion of the population leads to an incipient osteopenia that may eventually progress to frank osteoporosis. Such gradual change is but one of a plethora of slow functional declines in tissue activity that start in early middle age and inevitably contribute progressively to morbidity in the aged.
A Review of various 3-D Modelling Techniques and an Introduction to Point Clouds

The substantial lead of 3D models and computer graphics over 2D images is no mystery. Apart from being a hot topic in scientific and engineering society, 3D data models are found to be of widespread usage in fields like virtual reality, e-commerce, robotics, auto-pilot vehicles and other dominant techniques to successfully overcome the limitations of 2D projections, with their demands increasing with every passing digital age. This research paper is divided into 2 parts: the first part enlightens us about the various 3D modelling techniques with advantages, limitations and applications of each one of them while the latter part of the paper introduces the latest pioneer in the field of 3D modelling titled as ′Point Clouds′, an open source project capable of carrying out tasks like 3D classification, 3D detection, 3D segmentation, augmentation, flow estimation etc. To conclude our work, we outlined the various features of the Point Cloud Library along with their uses and future research summons.
Connectivity Maintenance in Uncertain Networks under Adversarial Attack

This paper studies the problem of connectivity maintenance in adversarial uncertain networks, where a defender prevents the largest connected component from being decomposed by an attacker. In contrast with its deterministic counterpart, connectivity maintenance in an uncertain network involves additional testing on edges to determine their existence. To this end, by modeling a general uncertain network as a random graph with each edge associated with an existence probability and a testing cost, our goal is to design a general adaptive defensive strategy to maximize the expected size of the largest remaining connected component with minimum expected testing cost and, moreover, the strategy should be independent of the attacking patterns. The computational complexity of the connectivity maintenance problem is unraveled by proving its NP-hardness. To accurately tackle the problem, based on dynamic programming we first propose an optimal defensive strategy for a specific class of uncertain networks with uniform testing costs. Thereafter multi-objective optimization is adopted to generalize the optimal strategy for general uncertain networks through weighted sum of normalized size and cost. Due to the prohibitive price of an optimal strategy, two approximate defensive strategies are further designed to pursue decent performance with quasilinear complexity. We first derive a heuristic approach by quantifying the edge vulnerability through an analogy from the degree centrality in deterministic networks to the probability degree and connectivity weight in uncertain networks. For performance guarantee, we then devise an adaptive greedy policy incorporating the minimax rule from game theory, which minimizes the possible loss suffered by the defender in a worst-case scenario caused by the attacker and has an approximation ratio of (1 − 1/e). Extensive experiments on both synthetic and real-world network datasets under diverse attacking patterns demonstrate the superiority of the proposed strategies over baselines.