Miracle-dz/UniFAR-FTUs huggingface dataset:
Analyzing the Performance of Millimeter Wave MIMO Antenna under Different Orientation of Unit Element

In this paper, a compact and simplified geometry monopole antenna with high gain and wideband is introduced. The presented antenna incorporates a microstrip feedline and a circular patch with two circular rings of stubs, which are inserted into the reference circular patch antenna to enhance the bandwidth and return loss. Roger RT/Duroid 6002 is used as the material for the antenna, and has overall dimensions of WS × LS = 12 mm × 9 mm. Three designs of two-port MIMO configurations are derived from the reference unit element antenna. In the first design, the antenna element is placed parallel to the reference antenna, while in the second design, the element is placed orthogonal to the reference element of the antenna. In the third design, the antenna elements are adjusted to be opposite each other. In this study, we analyze the isolation between the MIMO elements with different arrangements of the elements. The MIMO configurations have dimensions of 15 mm × 26 mm for two of the cases and 15 mm × 28.75 mm for the third case. All three MIMO antennas are made using similar materials and have the same specifications as the single element antenna. Other significant MIMO parameters, including the envelope correlation coefficient (ECC), diversity gain (DG), channel capacity loss (CCL), and mean effective gain (MEG), are also researched. Additionally, the paper includes a table summarizing the assessment of this work in comparison to relevant literature. The results of this study indicate that the proposed antenna is well-suited for future millimeter wave applications operating at 28 GHz.
Opinions of Students Learning Turkish as a Foreign Language on the Use of E-Portfolio in Writing Lessons

This study aims to investigate the opinions of students learning Turkish as a foreign language on the use of the e-portfolio method in writing classes. During the implementation phase of this case study, two methods were used concurrently. The first method was face-to-face instruction centered on the coursebook. The second method was the e-portfolio method utilizing digital tools. After the implementation, data regarding the participants’ opinions were collected through interview technique, and the collected data were analyzed through content analysis. According to the research findings, there is a diversity of opinions among students regarding digital writing practices. Generation Z students tend to evaluate digital writing more positively. Language control and support are positively received by students. It has been observed that digital writing offers spatial and temporal independence, enhances student-teacher and student-student interaction, and contributes to collaboration and skill development in the context of peer learning. It is concluded that digital writing increases learning motivation and generally improves Turkish writing skills. As a teaching tool, in addition to textbooks and notebooks, the use of digital resources, especially e-portfolio creation tools and dictionaries, which offer unlimited variety, has become a necessity. Based on the study results, it is recommended to use a hybrid approach where traditional and digital writing-based e-portfolio methods are used together in education. Accordingly, curriculum should be updated, digital tools should be used more effectively, and technology infrastructure should be improved. Centers or courses teaching Turkish as a foreign language should take the initiative for infrastructure improvements. In this context, it is recommended that researchers in the field of online teaching of writing, speaking, listening, and reading skills conduct studies and educators develop applications.
Application of the Extended Ground Truth Concept for Risk Anticipation Concerning Ecosystems

Mapping is a fundamental tool in the study of HFRV\VWHPV��,WL VXVXDOO\�GRQHE \�? HOGUHFRUGV�� EXWWKLV� method consumes a lot of time and resources. Remote sensing is a complementary tool, but still needs ground- WUXWKFHUWL? FDWL RQ��GXHWRWKHV FDOHIDFWRU��,Q� WKLVDUWLFOH� we present a concept, the ((WHQGHG�*URXQG� 7UXWK , which tries to keep the advantages of both mapping and remote- sensing techniques. The concept offers the use of imaging tools while providing a ground truth. We then develop this concept using one example concerning ecosystem analysis.
Epicardial adipose tissue, metabolic disorders, and cardiovascular diseases: recent advances classified by research methodologies

Abstract Epicardial adipose tissue (EAT) is located between the myocardium and visceral pericardium. The unique anatomy and physiology of the EAT determines its great potential in locally influencing adjacent tissues such as the myocardium and coronary arteries. Classified by research methodologies, this study reviews the latest research progress on the role of EAT in cardiovascular diseases (CVDs), particularly in patients with metabolic disorders. Studies based on imaging techniques demonstrated that increased EAT amount in patients with metabolic disorders is associated with higher risk of CVDs and increased mortality. Then, in‐depth profiling studies indicate that remodeled EAT may serve as a local mediator of the deleterious effects of cardiometabolic conditions and plays a crucial role in CVDs. Further, in vitro coculture studies provided preliminary evidence that the paracrine effect of remodeled EAT on adjacent cardiomyocytes can promote the occurrence and progression of CVDs. Considering the important role of EAT in CVDs, targeting EAT might be a potential strategy to reduce cardiovascular risks. Several interventions have been proved effective in reducing EAT amount. Our review provides valuable insights of the relationship between EAT, metabolic disorders, and CVDs, as well as an overview of the methodological constructs of EAT‐related studies.
Resource Management for Heterogeneous Semantic and Bit Communication Systems

A multi-user heterogeneous semantic and bit communication framework is proposed. An access point (AP) serves multiple users via either the semantic communication (SemCom) or the conventional bit communication (BitCom). Orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) techniques are employed for efficiently facilitating this heterogeneous multi-user network. A long-term (equivalent) semantic throughput maximization problem is formulated for jointly optimizing the communication mode selection, NOMA user pairing scheme, and the corresponding resource allocation at each time slot. A twin-delayed deep deterministic policy gradient with reference neuron enhanced Softmax (TD3-RNS) algorithm is proposed, where a fixed-value neuron is employed as the reference to improve the training efficiency. Simulation results demonstrate that 1) the proposed NOMA-based heterogeneous transmission outperforms the baselines which merely use SemCom or BitCom; 2) the proposed TD3-RNS achieves superior performance than the conventional TD3 algorithm.
An Unsupervised Domain Adaption Approach for Cross-Modality RGB-Infrared Person Re-Identification

Dual-camera systems commonly employed in surveillance serve as the foundation for RGB-infrared (IR) cross-modality person re-identification (ReID). However, significant modality differences give rise to inferior performance compared to single-modality scenarios. Furthermore, most existing studies in this area rely on supervised training with meticulously labeled datasets. Labeling RGB-IR image pairs is more complex than labeling conventional image data, and deploying pretrained models on unlabeled datasets can lead to catastrophic performance degradation. In contrast to previous solutions that focus solely on cross-modality or domain adaptation issues, this article presents an end-to-end unsupervised domain adaptation (UDA) framework for the cross-modality person ReID, which can simultaneously address both of these challenges. This model employs source domain classes, target domain clusters, and unclustered instance samples for the training, maximizing the comprehensive use of the dataset. Moreover, it addresses the problem of mismatched clustering labels between the two modalities in the target domain by incorporating a label matching module that reassigns reliable clusters with labels, ensuring correspondence between different modality labels. We construct the loss function by incorporating distinctiveness loss and multiplicity loss, both of which are determined by the similarity of neighboring features in the predicted feature space and the difference between distant features. This approach enables efficient feature clustering and cluster class assignment to occur concurrently. Eight UDA cross-modality person ReID experiments are conducted on three real datasets and six synthetic datasets. The experimental results unequivocally demonstrate that the proposed model outperforms the existing state-of-the-art algorithms to a significant degree. Notably, in RegDB $\to $ RegDB_light, the Rank-1 accuracy exhibits a remarkable improvement of 8.24%.
A Family of Ladder Multi-Resonant Switched-Capacitor Converters With Extended Voltage Gain Range and Complete Soft Charging

In this paper, a family of Ladder multi-resonant switched-capacitor converters (MRSCC) is proposed to deal with the issues of a high transient current spike, inherent capacitor charge sharing loss, hard-switched operation, and inability for lossless voltage regulation for traditional Ladder switched-capacitor converters (SCC). By incorporating a multi-resonant core (MRC) and adopting the on-time fixed frequency modulation, a “charge balance” state with overlapped resonant currents is introduced. Consequently, the conversion ratio of the Ladder MRSCC can be regulated continuously, widely, and efficiently, even at light load conditions. In addition, all transistors achieve zero-current-switching (ZCS) turn-on, and all diodes obtain ZCS turn-off. The complete soft-charging operation between capacitors is obtained, eliminating the high transient current spike and charge-sharing loss effectively. In addition, the synchronous Ladder MRSCC with a clamp circuit is proposed to further eliminate the high-frequency ringing and reduce the conduction loss, which makes it potentially applicable to compact applications, including power supplies for portable devices and panel-level photovoltaic systems. A comprehensive analysis of different operation modes, boundary conditions, component stress, topology implementation, and topology comparison is presented to assist converter operation and hardware design. A 55W prototype with the 3X Ladder MRSCC was developed to verify the effectiveness of the proposed topology, modulation strategy, and circuits.
Action values for mobile (NH4NO3-extractable) trace elements in soils based on the German national standard DIN 19730

This is a brief report about the derivation of background values (German: Hintergundwerte or Referenzwerte), action values (Prufwerte) and threshold values (Grenzwerte or Belastungswerte or Massnahmenwerte) for mobile trace elements in soils. The method chosen to determine mobile amounts of trace elements in soils is an ammonium nitrate extraction procedure: 20 g soil to 50 ml of 1 molar ammonium nitrate solution, shaken for 2 hours. This procedure became the German national standard DIN 19730 in 1995. The background, action and threshold values have been integrated into the regulation for soil protection in Baden-Wurttemberg, which was the first such regulation in Germany. In combination with the determination of the so-called total contents of elements in soils, the DIN 19730 can be used as a basis for risk assessment, for limiting agricultural use and as a sensitive instrument to detect soils with high amounts of potentially leachable elements.
Traffic Steering for Cellular-Enabled UAVs: A Federated Deep Reinforcement Learning Approach

This paper investigates the fundamental traffic steering issue for cellular-enabled unmanned aerial vehicles (UAVs), where each UAV needs to select one from different Mobile Network Operators (MNOs) to steer its traffic for improving the Quality-of-Service (QoS). To this end, we first formulate the issue as an optimization problem aiming to minimize the maximum outage probabilities of the UAVs. This problem is non-convex and non-linear, which is generally difficult to be solved. We propose a solution based on the framework of deep reinforcement learning (DRL) to solve it, in which we define the environment and the agent elements. Furthermore, to avoid sharing the learned experiences by the UAV in this solution, we further propose a federated deep reinforcement learning (FDRL)-based solution. Specifically, each UAV serves as a distributed agent to train separate model, and is then communicated to a special agent (dubbed coordinator) to aggregate all training models. Moreover, to optimize the aggregation process, we also introduce a FDRL with DRL-based aggregation (DRL2A) approach, in which the coordinator implements a DRL algorithm to learn optimal parameters of the aggregation. We consider deep Q-learning (DQN) algorithm for the distributed agents and Advantage Actor-Critic (A2C) for the coordinator. Simulation results are presented to validate the effectiveness of the proposed approach.
High radiation performance and multi-band acoustically driven piezoelectric antenna based on energy trapping theory

The paper introduces a novel design method for an acoustically driven piezoelectric antenna with high radiation performance and broadband characteristics based on energy trapping theory. The reasonableness of the design method is demonstrated by analytically deriving the radiated magnetic field, radiated efficiency and resonant frequency, which are further validated by simulation analysis. Furthermore, a prototype is fabricated and measured, and the results indicate remarkable improvements compared to the non-energy trapping mode, the bandwidth is widened by 10%, the radiation efficiency is increased by 28%, the radiation magnetic field is increased by three times, the transmission distance is increased by 2.75 times. The radiation enhancement and multi-band capability of the proposed antenna has been successfully demonstrated. Additionally, we have successfully implemented amplitude modulation signals transmission using proposed antenna. These results highlight the significant potential of the proposed antenna for portable, miniaturized, and high-performance wireless communication devices.
Evaluating SDN Applicability in the Edge

Multi-Access Edge computing (MEC) and Software Defined Networking (SDN) are novel paradigms, often utilised together, and aim to simplify the management of resources and offer cloud capabilities at the edge. SDN was originally designed for complex and large networks though recently found applications in smaller networks with fewer links. Little effort is given to the evaluation of SDN applicability at the Edge, especially in scenarios where Internet of Things (IoT) deployments are involved. This work presents an evaluation of SDN technology applicability at the edge in terms of data plane and control plane resource consumption. Our findings justify the wide acceptance of SDN and show that the control plane consumes relatively few resources compared to MEC resource pool. However, given the current trends of SDN, there are several possible improvements with respect to the cost of new equipment and the availability of tools.
GROWTH ASPECTS, PUBERTAL ATTAINMENT AND SEMEN CHARACTERISTICS OF BUFFALO CALVES TREATED WITH SOMATOTROPIN UNDER DIFFERENT CLIMATIC CONDITIONS

ABSTRACT S ixteen growing male buffalo calves were used in two experiments, among them eight calves (average initial body weight was 190.5 kg) were raised in moderate climate MC (September to November) while eight calves (average initial body weight was 202.5 kg) were raised in hot climate HC (July to September). In each experiment, two groups of male buffalo calves (four animals each) were used during pre-pubertal stage at about 10-11 months of calf age. One group was served as non treated group (Control group) whereas the other group was subcutaneously treated with 8 injections each of 500 mg recombinant bovine somatotropin (rBST) on biweekly basis throughout three months . There are no significant differences observed between studied groups in any of growth traits for calves raised during MC or HC conditions. However, both daily weight gain (DWG) and relative growth rate (RGR) were higher in rBST group than in any other groups . Generally, rBST treatment had no significant influence on any of blood metabolites in buffalo calves raised under HC or MC conditions. Despite, concentrations of thyroid hormones were considerably greater in both groups of calves that raised under MC compared with those raised under HC, rBST treatment increased only level of T4 in buffalo calves that raised under MC. Meanwhile, concentration of insulin was not affected by either treatment or season. Both rBST treatment and season had a significant (P<0.01) effect on testosterone concentration. The maximum concentration of testosterone in rBST group treated during MC (0.53 ± 0.02) may indicate positive androgenic effect of rBST treatment under MC conditions Buffalo calves that raised during HC and treated with rBST reached age at mounting and puberty earlier (P<0.05) than the control group while, differences between groups that raised during MC for reaching age at mounting, azospermia and puberty were insignificant. Differences in reaction time of used bulls were insignificant either due to treatment or seasonal changes while, physical characteristics of semen from buffalo calves raised during HC were relatively better than that of calves raised during MC. Raising buffalo calves under HC and adoption of rBST treatment resulted in higher (P<0.05) mass motility of sperms, greater (P<0.05) live sperms and greater (P<0.01) concentration of spermatozoa comparing with non treated group . key words: buffalo calves, somatotropin, growth, metabolism, puberty, semen characteristics, climatic conditions
Mechanical ventilation induces brainstem inflammation in preterm fetal sheep

Background Preterm infants have immature respiratory drive and often require prolonged periods of mechanical ventilation. Prolonged mechanical ventilation induces systemic inflammation resulting in ventilation-induced brain injury, however its effect on brainstem respiratory centers is unknown. We aimed to determine the effects of 24 h of mechanical ventilation on inflammation and injury in brainstem respiratory centres of preterm fetal sheep. Methods Preterm fetal sheep at 110 ± 1 days (d) gestation were instrumented to provide mechanical ventilation in utero. At 112 ± 1 d gestation, fetuses received either mechanical ventilation (VENT; n = 7; 3 ml/kg) for 24 h, or no ventilation (CONT; n = 6). At post-mortem, fetal brainstems were collected for assessment of mRNA and histological markers of inflammation and injury. Results In utero ventilation (IUV) did not alter any blood-gas parameters. IUV significantly increased systemic IL-6 and IL-8 concentrations over the 24 h period compared to CONT. The number of ameboid microglia within the nucleus tractus solitarius and the raphe nucleus increased in VENT fetuses (p < 0.05 for both vs. control). The % area fraction of GFAP + staining was not significantly higher within the preBötzinger complex (p = 0.067) and retrotrapezoid nucleus and parafacial respiratory group (p = 0.057) in VENT fetuses compared to CONT. Numbers of caspase-3 and TUNEL-positive cells were similar between groups. Gene expression (mRNA) levels of inflammation, injury, cell death and prostaglandin synthesis within the brainstem were similar between groups. Conclusion Mechanical ventilation induces a systemic inflammatory response with only moderate inflammatory effects within the brainstem respiratory centres of preterm fetal sheep.
Integrated Transcriptomic and Metabolomic Analysis Reveal the Underlying Mechanism of Anthocyanin Biosynthesis in Toona sinensis Leaves

Toona sinensis, commonly known as Chinese Toon, is a plant species that possesses noteworthy value as a tree and vegetable. Its tender young buds exhibit a diverse range of colors, primarily determined by the presence and composition of anthocyanins and flavonoids. However, the underlying mechanisms of anthocyanin biosynthesis in Toona sinensis have been rarely reported. To explore the related genes and metabolites associated with composition of leaf color, we conducted an analysis of the transcriptome and metabolome of five distinct Toona clones. The results showed that differentially expressed genes and metabolites involved in anthocyanin biosynthesis pathway were mainly enriched. A conjoint analysis of transcripts and metabolites was carried out in JFC (red) and LFC (green), resulting in the identification of 510 genes and 23 anthocyanin-related metabolites with a positive correlation coefficient greater than 0.8. Among these genes and metabolites, 23 transcription factors and phytohormone-related genes showed strong coefficients with 13 anthocyanin derivates, which mainly belonged to the stable types of delphinidin, cyanidin, peonidin. The core derivative was found to be Cyanidin-3-O-arabinoside, which was present in JFC at 520.93 times the abundance compared to LFC. Additionally, the regulatory network and relative expression levels of genes revealed that the structural genes DFR, ANS, and UFGT1 might be directly or indirectly regulated by the transcription factors SOC1 (MADS-box), CPC (MYB), and bHLH162 (bHLH) to control the accumulation of anthocyanin. The expression of these genes was significantly higher in red clones compared to green clones. Furthermore, RNA-seq results accurately reflected the true expression levels of genes. Overall, this study provides a foundation for future research aimed at manipulating anthocyanin biosynthesis to improve plant coloration or to derive human health benefits.
Machine Learning Model Trading with Information Asymmetry

Machine learning (ML) model trading prevents data breaches in privacy-sensitive data-driven applications. Departing from commonly assumed complete information scenarios, we consider the more practical trading scenario where model deception may emerge under information asymmetry. More specifically, the model seller may provide false information on model quality to maximize her payoff. This paper takes the first step in tackling information asymmetry through the lens of model verification. We propose an ML model market that allows buyers to verify model quality before purchasing. Such verification can be costly and often imperfect, which makes the buyer's decision highly nontrivial. We first formulate the ML model trading process as a three-stage sequential game with imperfect information, where the seller determines the model delivery strategy after observing the buyer's order decision. Our analysis reveals that at the equilibrium, the seller will probabilistically conduct model deception, considering the possibility of model verification. The equilibrium deception probability increases with the buyer's verification cost and decreases with verification accuracy. Interestingly, we also show that reducing information asymmetry through verification benefits both the buyer and seller. We further consider a second market model with buyer order information protection, where the buyer's order information is unobservable before the seller makes the delivery strategy. Our analysis shows a surprising result under this market model: protecting buyer's order information will not increase the payoff of either the buyer or seller.