Etimologi perkataan arkaik dalam bahasa Melayu: faktor dan kesan pewujudan kata

Peminjaman kata daripada bahasa rumpun lain telah menambahkan jumlah perbendaharaan Melayu. Pertambahan yang berlaku juga telah mewujudkan kesinoniman kata dan memberi nilai kepada penggunaan sesebuah kata. Walau bagaimanapun, peresapan kosa kata asing yang berterusan telah menyebabkan wujudnya perkataan arkaik. Pewujudan ini bukan hanya berlaku pada kosa kata asli Melayu malah terjadi pada kata yang dipinjam daripada rumpun bahasa lain. Oleh itu, kajian ini akan meneliti lima perkataan arkaik dalam bahasa Melayu dari sudut etimologi. Pemilihan data kajian dibuat berdasarkan penandaan simbol ‘ark’ yang merujuk kepada arkaik menerusi Kamus Dewan Perdana (2020). Selain itu, data terpilih juga dibuat berdasarkan kepada persamaan makna antara perkataan arkaik dengan perkataan pada masa kini. Pembuktian ini penting bagi mengenal pasti kemasukan atau penggunaan sesebuah kata dalam bahasa Melayu dan kemunculannya sebagai kata arkaik sebagaimana yang dicatatkan oleh pengkaji bahasa lain. Selain itu, faktor berlakunya fenomena ini turut dibincangkan dengan menggunakan kerangka pedoman etimologi yang dicadangkan oleh Collins (2003) yang diubah suai oleh Taufiq (2022). Hasil kajian menunjukkan bahawa kata arkaik terhasil menerusi penggantian kata yang lebih menyerlah penggunaannya dalam kalangan penutur bahasa. Selain itu, melalui penelitian kekerapan penggunaan serta kemunculannya menerusi manuskrip Melayu lama, beberapa perkataan yang dikaji juga tidak digunakan dengan meluas pada zamannya. Sekiranya terdapat dua perkataan yang sinonim, masyarakat Melayu lebih memilih perkataan yang difahami oleh masyarakat umum agar mudah untuk berkomunikasi, dan hal ini menyebabkan status perkataan yang dipinggirkan itu berubah menjadi perkataan arkaik

Multipath Delay Estimation by Jammed Pilot in OFDM System

This paper studies orthogonal frequency-division multiplexing (OFDM) system channel estimation problem in the interference environment and the channel delay estimation algorithm is proposed. The algorithm consists of the narrowband interference detection and suppression and channel time delay estimation. First of all, this paper studied the statistical characteristics of channel frequency domain response value at pilot tones, use double threshold consecutive mean excision (CME) algorithm, to detect the interference of pilot subcarriers and interference suppression. Then, the authors analyze the channel frequency response mathematical model and alternating notch periodogram (ANP) spectral estimation method is used to obtain the channel time delay estimation value. The simulation results show that the use of this improved channel estimation algorithm very close to the performance of the Expectation Maximization (EM) channel estimation algorithm with ideal channel delay for channel estimation algorithm performance and BER performance and the delay is known

Multiple mechanisms of curcumin targeting spinal cord injury

Spinal cord injury (SCI) is an irreversible disease process with a high disability and mortality rate. After primary spinal cord injury, the secondary injury may occur in sequence, which is composed of ischemia and hypoxia, excitotoxicity, calcium overload, oxidative stress and inflammation, resulting in massive death of parenchymal cells in the injured area, followed by the formation of syringomyelia. Effectively curbing the process of secondary injury can promote nerve repair and improve functional prognosis. As the main active ingredient in turmeric, curcumin can play an important role in reducing inflammation and oxidation, protecting the neurons, and ultimately reducing spinal cord injury. This article reviews the effects of curcumin on the repair of nerve injury, with emphasis on the various mechanisms by which curcumin promotes the treatment of spinal cord injury

The forming region and mechanical properties of SiO2-Al2O3-MgO glasses

International audienceThe glasses of 93.9% (xSiO(2)-yAl(2)O(3)-zMgO)-5% CaO-1% B2O3-0.1% Fe2O3 were prepared, and the relationship between mechanical properties and structural stability were characterized by means of Raman spectroscopy and optical band gap values. The glass forming region is found to be x = 50-70%, y = 10-25% and z = 15-32%. As x = 65%, y = 10% and z = 25% (SAM-4), the investigated glass possesses the optimum volume density, oxygen packing density, optical band gap, banding strength, compression strength and compression modulus, which are 2.517 g/cm(3), 77.047 mol/l, 3.56 eV, 77.04 MPa, 202.74 MPa and 106.70 GPa, respectively. Meanwhile, starting from the representative point of SAM-4 to radiate around, the volume density, oxygen density, Raman intensity and mechanical properties of the glasses are all decreasing constantly, and the optical band gap of the glasses is increasing on the contrary. Moreover, the optical band gap value and Raman spectroscopy of SAM-4 all prove that the number of oxygen bonds in the bridge reach the maximum and the highest structural stability is achieved, which further shows that it is an important reason why its mechanical properties is significantly improved

Mapping Tree Species Composition Using OHS-1 Hyperspectral Data and Deep Learning Algorithms in Changbai Mountains, Northeast China

The accurate characterization of tree species distribution in forest areas can help significantly reduce uncertainties in the estimation of ecosystem parameters and forest resources. Deep learning algorithms have become a hot topic in recent years, but they have so far not been applied to tree species classification. In this study, one-dimensional convolutional neural network (Conv1D), a popular deep learning algorithm, was proposed to automatically identify tree species using OHS-1 hyperspectral images. Additionally, the random forest (RF) classifier was applied to compare to the algorithm of deep learning. Based on our experiments, we drew three main conclusions: First, the OHS-1 hyperspectral images used in this study have high spatial resolution (10 m), which reduces the influence of mixed pixel effect and greatly improves the classification accuracy. Second, limited by the amount of sample data, Conv1D-based classifier does not need too many layers to achieve high classification accuracy. In addition, the size of the convolution kernel has a great influence on the classification accuracy. Finally, the accuracy of Conv1D (85.04%) is higher than that of RF model (80.61%). Especially for broadleaf species with similar spectral characteristics, such as Manchurian walnut and aspen, the accuracy of Conv1D-based classifier is significantly higher than RF classifier (87.15% and 71.77%, respectively). Thus, the Conv1D-based deep learning framework combined with hyperspectral imagery can efficiently improve the accuracy of tree species classification and has great application prospects in the future

Unraveling Morphology and Phase Control of NaLnF₄ Upconverting Nanocrystals

Near-infrared to visible upconversion NaLnF₄ (Ln = Pr to Lu and Y) nanocrystals hold great promise for use in biological labeling and imaging due to their intrinsic characteristics such as high chemical stability, nonblinking and sharp bandwidth luminescence, large Stokes shift, as well as appropriate and abundant energy states necessary for efficient energy transfer to achieve near-infrared to visible upconversion emission. However, there are still significant hurdles in the control of size, shape, and phase of NaLnF₄ nanocrystals due to limited understanding of their growth behavior and growth mechanism. Here we describe an approach to facilely control the shape and phase of upconversion NaLnF₄ nanocrystals. Besides the optimization of synthetic conditions such as organic surfactant and reaction temperature, we have developed a program, in which a correlation between the ionic radius of lanthanide ions and the shape/phase of NaLnF₄ nanocrystals is established, to precisely control the shape and phase of NaLnF₄ nanocrystals by precisely tuning the mean ionic radius of lanthanide ions through lanthanide doping. The availability of such upconverting nanocrystals with controlled size, shape, and phase provides a platform for applications ranging from biological imaging, biological sensing, and three-dimensional displays

Climate and land use controls on soil organic carbon in the loess plateau region of China.

The Loess Plateau of China has the highest soil erosion rate in the world where billion tons of soil is annually washed into Yellow River. In recent decades this region has experienced significant climate change and policy-driven land conversion. However, it has not yet been well investigated how these changes in climate and land use have affected soil organic carbon (SOC) storage on the Loess Plateau. By using the Dynamic Land Ecosystem Model (DLEM), we quantified the effects of climate and land use on SOC storage on the Loess Plateau in the context of multiple environmental factors during the period of 1961-2005. Our results show that SOC storage increased by 0.27 Pg C on the Loess Plateau as a result of multiple environmental factors during the study period. About 55% (0.14 Pg C) of the SOC increase was caused by land conversion from cropland to grassland/forest owing to the government efforts to reduce soil erosion and improve the ecological conditions in the region. Historical climate change reduced SOC by 0.05 Pg C (approximately 19% of the total change) primarily due to a significant climate warming and a slight reduction in precipitation. Our results imply that the implementation of "Grain for Green" policy may effectively enhance regional soil carbon storage and hence starve off further soil erosion on the Loess Plateau