Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient FPGA-Based Convolutional Neural Network Implementation for Edge Computing

—In recent years, accelerating convolutional neural networks on Field Programmable Gate Array (FPGA) to improve the performance of the inference phase of artificial intelligent edge computing applications is a promising approach. This paper presents our proposed architecture for building a convolution neural network acceleration core on FPGA. The proposed FPGA-based core targets edge computing platforms where hardware resources and power efficiency are essential requirements. We use the MobileNet neural network model for image classification as a case study to evaluate our proposed system. We compare our work with a quad-core ARM Cortex processor at 1.2GHz and achieve speed-ups by up to 14.77 × convolution operators. Although our system is worse than a 6-core Intel Core i7 processor, it is more energy-efficiency than the Intel processor. Our proposed system is the best fit for edge computing.
Welder Recruitment Decision Support System Using the SMARTER Method

The high level of competition in the world of welding services business today makes the welding workshop entrepreneurs struggle hard to optimize the human resources as the welders own. The task is to recruit a skilled worker. This is due to the fact that the company is able to compete in the world of business services, the manufacturer of welding is very interested in the quality of the product so that the consumer is interested in improving the services offered by the business owner. In this study, to support the results of decision-making made in the recruitment process of welders, the SMARTER method is applied. On the final results of this study can be seen that the results of the application of the SMARTER method for comparison with 5 alternatives that are selected, that is, who obtained the first ranking is Joko with a value of 1.74. Then in the next ranking position is Tian (1.56) as the second ranking, Rian (1.06) third rank, Raden R (0.88) fourth ranking, and Budi Ramadhan (0.36) in the last ranking position
A Hybrid Convolutional Neural Network Model for Automatic Diabetic Retinopathy Classification From Fundus Images

Objective: Diabetic Retinopathy (DR) is a retinal disease that can cause damage to blood vessels in the eye, that is the major cause of impaired vision or blindness, if not treated early. Manual detection of diabetic retinopathy is time-consuming and prone to human error due to the complex structure of the eye. Methods & Results: various automatic techniques have been proposed to detect diabetic retinopathy from fundus images. However, these techniques are limited in their ability to capture the complex features underlying diabetic retinopathy, particularly in the early stages. In this study, we propose a novel approach to detect diabetic retinopathy using a convolutional neural network (CNN) model. The proposed model extracts features using two different deep learning (DL) models, Resnet50 and Inceptionv3, and concatenates them before feeding them into the CNN for classification. The proposed model is evaluated on a publicly available dataset of fundus images. The experimental results demonstrate that the proposed CNN model achieves higher accuracy, sensitivity, specificity, precision, and f1 score compared to state-of-the-art methods, with respective scores of 96.85%, 99.28%, 98.92%, 96.46%, and 98.65%.
Paradigm Shift in the Management of Acute Myeloid Leukemia—Approved Options in 2023

Simple Summary Acute Myeloid Leukemia is the most common aggressive blood cancer in adults. Treatment for this condition is divided into induction followed by consolidation. The mainstay of treatment is chemotherapy, and until a decade ago, only traditional chemotherapy was approved for this condition. Induction involves treatment with intense chemotherapy for a span of 7 days. Once blood counts recover, patients undergo bone marrow biopsy to ensure remission status for the disease. Elderly patients who were considered too weak to receive intense therapy were treated with single-agent low-intensity therapy until the approval of a few new combinations starting in 2018. As a result, over the last 10 years, 10 new medications have been approved for the treatment of this type of leukemia. We discuss the evidence behind these treatment regimens and combinations. Abstract The word Leukemia was coined nearly 200 years ago by Rudolf Virchow. Once a death sentence, Acute Myeloid Leukemia (AML) is now a treatable condition. The introduction of “7 + 3” chemotherapy, originally reported from the Roswell Park Memorial institute in Buffalo, New York, in 1973, changed the treatment paradigm for AML. About twenty-seven years later, FDA approved the first targeted agent, gemtuzumab, to be added to this backbone. During the last seven years, we have had ten new drugs approved for the management of patients with AML. Work by many dedicated scientists led to AML achieving the elite status of being the first cancer to have the whole genome sequenced using next-generation sequencing. In the year 2022, we witnessed the introduction of new classification systems for AML by the international consensus classification and the world health organization, both emphasizing molecular classification of the disease. In addition, the introduction of agents such as venetoclax and targeted therapies have changed the treatment paradigm in older patients ineligible for intensive therapy. In this review, we cover the rationale and evidence behind these regimens and provide insights into the newer agents.
Taiwanese University Teachers’ Motivation and Language Choice for Scholarly Publishing

Within a global trend of academic publishing in English, publication in indigenous languages, nevertheless, in many contexts, continues to thrive. Multilingual scholars often need to negotiate international engagement and local commitment by publishing both in English and their first language. The study, based on individual in-depth semi-structured interviews with university bilingual teachers from social sciences in Taiwan, focuses on examining their motivation and language choice (i.e., first language only, English only, or both English and first language) for publishing their research articles, and factors that may influence their motivation and language choice. The study showed that (1) against the widely-held view of utility in getting published in English as the single most important driving force, it pointed to a complex picture of Taiwanese university teachers’ motivation and language choice for scholarly publishing; (2) the privilege attached to publishing in internationally indexed journals stood out as the major factor orienting Taiwanese university teachers toward writing in English and using various strategies to facilitate successful publication; (3) international publication in English nonetheless increases, but Chinese would still retain its position as the language of research and publication; and (4) the tension in the negotiation was likely to grow with the continuous push toward the globalization of the academia which had a great impact on university teachers. This study provides useful insight into understanding university teachers’ motivation and language choice for scholarly publishing. Some recommendations are made when guiding school planners for helping university teachers to cope with international publication versus local publication.
Set in Stone? Mobile Practices Evolution in Later Life

In what ways do mobile communication practices change through later life? To what extent do sociodemographic characteristics, country of residence, and well-being relate to these changing practices? To answer these questions, we used an online, longitudinal study targeting internet users aged 60 and over in six countries (Austria, Canada, Israel, the Netherlands, Spain, and Romania). The focus is on the 3,125 respondents who declared using a mobile phone in every wave (2016, 2018, and 2020). Results show an increasing usage diversification already before the Covid-19 pandemic. A latent class analysis identified three different styles of mobile practices. The most sophisticated relies on almost all the analyzed functions, while the most unsophisticated is limited to voice calls, texting (mainly SMS), and photographs to a lesser extent. Finally, a multinomial analysis provided a picture of the individual characteristics related to the usage styles in the period. The most relevant dimensions were country of residence and age, followed by internet use intensity. The country of residence is relevant to explaining usage because the telecommunications price structure determines the priority given to the mobile phone in (senior) individuals’ everyday lives. The article contributes nuanced evidence of the trajectories of digital practices in later life. At the same time, the findings support and better inform country-based policies, services, and products for more effective inclusion of the older population in today’s hyper-digitized societies.
Mechanism of "Huang Qi-Yin Yang Huo" on the Treatment of Osteoporosis by Active Components Based on Network Pharmacology and Molecular Docking

: Objective: To investigate the effect of Huang Qi-Yin Yang Huo on osteoporosis (OP) by means of network pharmacology and molecular docking, in order to provide a basis for its basic research and clinical application. Methods: The active components and targets of the drug pair were obtained by means of TCMSP database and literature supplement. OMIM, GeneCards, DisGeNet, TTD and DrugBank databases were used to screen the targets related to osteoporosis, and Wayne tool was used to obtain the intersection targets. CytoScape 3.7. 2 software was used to construct the “drug-ingredient-disease” network and screen core components according to node-degree values. Protein interaction network (PPI) was constructed with STRING 11.5, and core targets were screened according to node-degree values. Metascape was used for gene ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Gene and Genes (KEGG) pathway enrichment analysis, and the interactions between core components and core targets were verified by molecular docking. Results: 46 kinds of active components were identified by drug pair screening, and 128 intersection targets were identified. The target protein enrichment pathways included MAPK signaling pathway, PI3K-Akt signaling pathway, HIF-1 signaling pathway and estrogen signaling pathway. The results of Molecular docking showed that the core components had good binding ability with the core target. Conclusion: Huang Qi-Yin Yang Huo may treat osteoporosis through multi-target and multi-pathway treatment, mainly regulating osteoblast differentiation, osteoclast inhibition, cell apoptosis and inflammation regulation, etc., providing a new idea and method for further research on the mechanism of osteoporosis in the future
Polyploid Induction and Identification of Rosa roxburghii f. eseiosa

Rosa roxburghii f. eseiosa Ku is a variety of Rosa roxburghii, with two known genotypes: Wuci 1 and Wuci 2. The lack of prickle on the peel of R. roxburghii f. eseiosa makes it easy to pick and process, but its fruit size is small. Therefore, we aim to induce polyploidy in order to obtain a larger fruit variety of R. roxburghii f. eseiosa. In this study, current-year stems of Wuci 1 and Wuci 2 were used as materials for polyploid induction, which was carried out through colchicine treatment coupled with tissue culture and rapid propagation technology. Impregnation and smearing methods were effectively used to produce polyploids. Using flow cytometry and a chromosome counting method, it was found that one autotetraploid of Wuci 1 (2n = 4x = 28) was obtained by the impregnation method before primary culture, with a variation rate of 1.11%. Meanwhile, seven Wuci 2 bud mutation tetraploids (2n = 4x = 28) were produced by smearing methods during the training seedling stage. When tissue-culture seedlings were treated with 20 mg/L colchicine for 15 days, the highest polyploidy rate was up to 60%. Morphological differences between different ploidys were observed. The side leaflet shape index, guard cell length, and stomatal length of the Wuci 1 tetraploid were significantly different from those of the Wuci 1 diploid. The terminal leaflet width, terminal leaflet shape index, side leaflet length, side leaflet width, guard cell length, guard cell width, stomatal length, and stomatal width of the Wuci 2 tetraploid were significantly different from those of the Wuci 2 diploid. Additionally, the leaf color of the Wuci 1 and Wuci 2 tetraploids changed from light to dark, with an initial decrease in chlorophyll content followed by an increase. In summary, this study established an effective method for inducing polyploids in R. roxburghii f. eseiosa, which could provide a foundation for the breeding and development of new genetic resources for R. roxburghii f. eseiosa and other R. roxburghii varieties in the future.
Patterned Reed–Muller Sequences with Outer A-Channel Codes and Projective Decoding for Slot-Controlled Unsourced Random Access

We propose a novel slot-pattern-control based coded compressed sensing for unsourced random access with an outer A-channel code capable of correcting t errors. Specifically, an RM extension code called patterned Reed–Muller (PRM) code is proposed. We demonstrate the high spectral efficiency due to its enormous sequence space and prove the geometry property in the complex domain that enhances the reliability and efficiency of detection. Accordingly, a projective decoder based on its geometry theorem is also proposed. Next, the “patterned” property of the PRM code, which partitions the binary vector space into several subspaces, is further extended as the primary principle for designing a slot control criterion that reduces the number of simultaneous transmissions in each slot. The factors affecting the chance of sequence collisions are identified. Finally, the proposed scheme is implemented in two practical outer A-channel codes: (i) the t-tree code and (ii) the Reed–Solomon code with Guruswami–Sudan list decoding, and the optimal setups are determined to minimize SNR by optimizing the inner and outer codes jointly. In comparison with the existing counterpart, our simulation results confirm that the proposed scheme compares favorably with benchmark schemes regarding the energy-per-bit requirement to meet a target error probability as well as the number of accommodated active users in the system.
Low water availability has a greater influence on the development of coffee seedlings than an increase in temperature

Coffee is an important product in the world, essential for thousands of producing families. However, climate change has generated variations in temperature and precipitation that negatively impact the maturation of crops. To quantify the combined effect of drought stress and elevated temperatures, plants of Coffea arabica cv. Ouro Verde IAC H5010-5 were evaluated under the climatic conditions of La Molina, Peru, with four treatments (WT: 100% available water + air temperature (22.7°C); -WT: < 50% available water + air temperature (22.7°C); W+T: 100% available water + elevated air temperature (22.7 + 2.5°C), and –W+T: < 50% available water + elevated air temperature (22.7 + 2.5°C)). In general, morphological indices were decreased by -WT and –W+T (P≤0.05). Plants subjected to -W+T, significantly affected quality indices like root:shoot ratio, robustness, and Dickson (P≤0.05). The -WT plants had a nitrogen content of 2.46%, the highest nitrogen content compared to other treatments. Isolated and combined stress had negative differential effects on plant development, and water scarcity (as an individual factor) was the repercussion, in most cases, that was more prominent than the effect of high temperature.
A General Algorithm of Complex Surface Development

A general algorithm based on geometry flattening/mechanics revision principle is presented in this paper.This general algorithm can solve the development of complex surface.Firstly,faceted model is used to represent a complex surface.Secondly,2D original flattening is obtained to form 3D surface.Thirdly,a physical model composed of a set of nodes connected by springs is constructed to optimize the original flattening.Compared to earlier method,this approach provides more flexibility for solving CAD/CAM surface development problems.
Sparse Logistic Regression-Based EEG Channel Optimization Algorithm for Improved Universality across Participants

Electroencephalogram (EEG) channel optimization can reduce redundant information and improve EEG decoding accuracy by selecting the most informative channels. This article aims to investigate the universality regarding EEG channel optimization in terms of how well the selected EEG channels can be generalized to different participants. In particular, this study proposes a sparse logistic regression (SLR)-based EEG channel optimization algorithm using a non-zero model parameter ranking method. The proposed channel optimization algorithm was evaluated in both individual analysis and group analysis using the raw EEG data, compared with the conventional channel selection method based on the correlation coefficients (CCS). The experimental results demonstrate that the SLR-based EEG channel optimization algorithm not only filters out most redundant channels (filters 75–96.9% of channels) with a 1.65–5.1% increase in decoding accuracy, but it can also achieve a satisfactory level of decoding accuracy in the group analysis by employing only a few (2–15) common EEG electrodes, even for different participants. The proposed channel optimization algorithm can realize better universality for EEG decoding, which can reduce the burden of EEG data acquisition and enhance the real-world application of EEG-based brain–computer interface (BCI).
First Report of Rose Bent Neck Caused by Sclerotinia sclerotiorum on Commercial Cut Roses (Rosa hybrida L.)

Cut roses are highly valuable ornamentals and their profitability depends on the flower postharvest performance. Bent neck symptoms in roses make them unmarketable and are typically related to physiological disorders, bacteria accumulation in the vase solution, and Botrytis cinerea infection. Unusual bent neck symptoms were observed in 4.7% of ‘Orange Crush’ roses from two commercial shipments, resulting in complete flower collapse. This research was aimed to determine the causal agent of the bent neck symptoms. Following incubation in a humid chamber, symptomatic roses evolved in water-soaked lesions with the presence of white mycelium and sclerotia development. Fungal isolations and molecular characterization were performed and Sclerotinia sclerotiorum was identified as the causal agent of rose bent neck. Therefore, when bent neck symptoms are observed, S. sclerotiorum incidence should be considered to avoid possible outbreaks.
The Practice of Religious Plurality in The Indonesian National Army

This paper discusses the practice of religious plurality within the Indonesian Armed Forces. To support the main task of soldiers and the success of the task, they are equipped with faith and purity, good moral values and noble character. Religion has a significant role in supporting military tasks. Data collection techniques in this study used observation then, followed by interviews. Forms behaviour The TNI AD in maintaining harmony between members of different religions includes anjangsana, working together to achieve common goals in religion, sympathy and empathy, tolerance and mutual respect. Adaptation conducted interfaith religious packed reasonably. Goal TNI AD attachment is the goal achieved that is harmony and tolerance Inter-religion. Function Integration TNI AD is carried out by issuing governing policies about members of TNI AD, which religious Islam, Christian, Hindu and Buddhist for holding religious ceremonies simultaneously on the day and at the time same. That is day Friday o'clock 18.30 WIB. The system of Latent Maintenance, which the Indonesian Army maintains, improves individual motivation and the cultural patterns that create and maintain the motivation.
Access Characteristic Guided Partition for Nand Flash-Based High-Density SSDs

nand flash-based solid-state drives (SSDs) are a kind of widely adopted storage. However, state-of-the-art works presented that the SSD always suffers from significant read performance degradation. One of the most critical reasons is access interference between read and write operations. This is because the read and write latency gaps are more pronounced for the latest nand flash in SSDs. In this article, an interference reduction scheme is proposed to improve performance. This is motivated by the observation from several server workloads, where read and write operations can be easily separated based on access characteristics. Considering that SSDs are always organized with many parallel units (PUs), the basic idea of this work is to partition the PUs of the SSD into different areas and place data in the corresponding area according to access characteristics. Then, the interference can be optimized by issuing read and write requests to the different areas. To realize the above design, several approaches are proposed: first, an access characteristic-based data placement and migration method is proposed for read and write request separation. Second, to further adapt the parallel requirement for different workloads, a workload-based partitioning scheme is proposed to determine the number of PUs for read and write areas. Finally, based on partitioned SSD, a hot-data driven wear-leveling method is further proposed to balance the wearing of PUs in read and write areas. Experimental results show that partitioned SSD can significantly improve the read performance and wear leveling of partitioned SSD can guarantee performance and lifetime.
Gaussian Solutions to the Lagrangian Variational Problem in Stochastic Mechanics

Nous presentons une etude qualitative de l'evolution temporelle des solutions gaussiennes pour les equations generales qui resolvent le probleme variationnel de la Mecanique Stochastique. Nous donnons quelques resultats sur la stabilite asymptotique des solutions de l'equation de Schrodinger pour des perturbations dissipatives. Nous decrivons aussi, au moyen de calculs numeriques, le phenomene de l'accroissement de la rotation
Improved YOLOX method for small target smoking detection algorithm

Smoking is prohibited in many places. In order to detect smoking behaviour and make accurate judgments in a timely manner, machine vision technology is used to carry out research on the detection of small targets of cigarette sticks to improve the problem of difficult and inaccurate recognition of small targets in current detection algorithms and to improve the accuracy of cigarette sticks being recognized. In this study, we propose an improved method to detect smoking behaviour of Yolox based on the attention mechanism, in view of the fact that cigarette sticks occupy a very small part of the image and the presence of hand occlusion. The Attention mechanism module is added to the feature extraction network to focus on local information. Meanwhile, the use of the deep network is increased by adding a scale to focus attention within the target region; and the loss function is optimally replaced and the GIoU loss function is chosen to solve the drawback problem of IoU; experimental results show that the improved Yolox-c algorithm mAP reaches 95.96%, compared with Yolox and Yolov5 mAP, which are improved by 5.87% and 8.85%, respectively.