Miracle-dz/UniFAR-FTUs huggingface dataset:
Sentiment Analysis On Movie Streaming Services On Twitter Using LDA and SVM Methods

Many online platforms for movie streaming have emerged nowadays in Indonesia with the development of technology. Streaming platforms that are widely used by the public are Netflix, Disney+, HBO Go, WeTV, Vidio. A lot of comparisons between streaming platforms have become a topic of discussion on social media. The opinions expressed by users of the streaming platform greatly affect other users who want to watch the movie. The transmission of opinions from users becomes positive and negative comments that are received by the public and spread widely on social media. Opinions that contain both positive and negative comments become a problem and can affect other users who want to watch movies through streaming platforms. The opinions of users about the streaming platform can be analyzed through sentiment analysis. At the stage of data collection using scrapy framework tools with Python, as much as 1,500 lines of text are preprocessed. LDA method to present topics that contain representative words. Classification using the Support Vector Machine (SVM) gets more positive comments than negative comments. The test results obtained an accuracy of 0.82, recall of 0.8, F1 score of 0.79, and precision of 0.8.
Physicochemical, techno-functional and antioxidant properties of Pleurotus spp. powders

Edible mushrooms are considered an important source of nutritional and functional components; therefore, they have been proposed as promissory ingredients for foods. The aim of this study was to evaluate the physicochemical, techno-functional, and antioxidant properties of two Pleurotus spp. powders ( P . ostreatus and P . pulmonarius ). Regarding physicochemical properties, Pleurotus spp. powders showed (p<0.05) pH values near to neutrality in comparison to soy protein (control)
Research Article: Communication Challenges for Complex Policy Issues: An Illustration with Multimedia Radon Mitigation

Communication challenges of environmental management are magnified for uncertain policy options and trade-offs involving complex issues. A novel risk-trading option authorized by Congress for setting standards for radon levels in drinking water illustrates interactions and gaps among scholarly advice, practitioner behavior, and citizen responses, as revealed in utility-customer focus groups. The aim of the focus groups was to identify citizen-preferred options (including any not yet suggested by policy makers) and difficulties in presenting needed background information so that policy preferences are valid and reliable if elicited in the future. This commentary covers such topics as effects of knowledge, risk comparisons and information framing, values clarification, presentation of policy options and evaluation, and their implications for risk communication and policy development.
Model-based Runtime Veriﬁcation Framework for Self-optimizing Systems 1

This paper describes a novel on-line model checking approach oﬀered as service of a real-time operating system (RTOS). The veriﬁcation system is intended especially for self-optimizing component-based real-time systems where self-optimization is performed by dynamically exchanging components. The veriﬁcation is performed at the level of (RT-UML) models. The properties to be checked are expressed by RT-OCL terms where the underlying temporal logic is restricted to either time-annotated ACTL or LTL formulae. The on-line model checking runs interleaved with the execution of the component to be checked in a pipelined manner. The technique applied is based on on-the-ﬂy model checking. More speciﬁcally for ACTL formulae this means on-the-ﬂy solution of the NHORNSAT problem while in the case of LTL the emptiness checking method is applied.
Effect of Utilizing a Sleep Guidline on Sleep Pattern among Third Trimester Pregnant Women

: The aim of this study was to evaluat the effect of utilizing guideline on sleep pattern in third trimester pregnant women. A Quasi-Experimentaldesign wasutilaized. This study was conducted at the Antenatal clinic at the Obstetrics and Gynecology center in Mansura city over a period of eight months from the beginning of July 2016 to the end of Feb 2016. A purposive sample was used to select the study (n=80). Two tools were used for data collection; the first tool wasa Structured Interview schedule. It consisted of four parts to measure the following items; general characteristics, the past and present reproductive history, the minor discomforts during third trimester and daily lifestyle of the subject. Tool two was Pittsburgh Sleep Quality Index (PSQI). The PSQI is composed of 19 items that are used to assessthe sleep quality. Findings: According to Pittsburgh Sleep Quality Index (PSQI) there was a highly statistically significant difference in subjects' sleep patterns between pre and post-interventionscors. However, their utilization of sleep medication was almost the same before and after the intervention. The findings of this study suggested a statistically significant improvement in the subjects sleep pattern after implementation of the guideline in comparison to before. Recommendations: Simple handouts as booklets and brochures about sleeping pattern and its importance should be prepared and distributed at antenatal clinics. Sleep guidelines should be integrated into maternity courses curriculum for nursing students. Sleep enhancing educational session should be applied at the maternity hospitals and centers.
Analysis of the Second Language Learning and Teaching through Cognitive Constructivism

: Learning of the language starts from the childhood but the acquisition of first language and the learning of the second language is different. The first language acquisition is easier than the second language as we are always in contact with the first language. The second language needs effort forits accommodation, assimilation, and application.The cognitivism and constructivism theories of Jean Piaget and Jerome Bruner laid stress on the facilitation of the learning by the processing of the existing knowledge and the construction of the new information. The cognitivism and the constructivism approaches enhance the acquisition of the second language. It is not only the linguistics namely lexical, morphology, syntax, phonetics that helps in the learning of the second language, but the involvement of the sociocultural aspect also plays an important role for the application of the language in the real-lifesituations. This article focuses on the analysis of the learning and teaching of the second language through the cognitive constructivism strategy. The cognitive constructivism strategy motivates the learner to construct the new knowledge based on their prior information and their sociocultural environment. This strategy helps the learner to retain the new knowledge and to apply this newly acquired information in the real-life situations.
Simplified estimation of seismic moment from seismograms

abstract This study proposes a method to estimate the seismic moment of regional and local earthquakes based on simple measurements made directly on Wood-Anderson seismograms. The method parallels the routine estimation of local magnitude in observatory work. The relation used is log M o = a + b log ( C × D × Δ p ) where C is the maximum peak-to-peak amplitude read on a Wood-Anderson seismogram, D is the duration between the S arrival and the onset with amplitude C / d , Δ is epicentral distance, and a, b, p , and d are constants. The form of the logarithmic term is suggested by the analytical expression for moment (Keilis-Borok, 1960). Least-squares fits were made to data from 73 Wood-Anderson records of 16 central California earthquakes with seismic moments already evaluated independently from spectral analysis or broadband displacement records. The values p = 1, d , = 3 proved appropriate and subsequent regression yielded log M o = ( 16.74 ± 0.20 ) + ( 1.22 ± 0.14 ) log ( C × D × Δ ) where M o is dyne-cm, C in millimeters, D in seconds, and Δ in kilometers. The corresponding moment-magnitude relation is log M o = ( 17.92 ± 1.02 ) + ( 1.11 ± 0.15 ) M L , for 3 ≦ M L ≦ 6.2. The latter fit is close to an earlier empirical result (Johnson and McEvilly, 1974) for central California based on fewer cases and a different range of magnitude (2.4 ≦ M L ≦ 5.1).
HashRand: Efficient Asynchronous Random Beacon without Threshold Cryptographic Setup

—Regular access to unpredictable and bias-resistant randomness is important for applications such as blockchains, voting, and secure distributed computing. Distributed random beacon protocols address this need by distributing trust across multiple nodes, with the majority of them assumed to be honest. These protocols have found applications in blockchain technology, leading to the proposal of several distributed random beacon protocols, with some already implemented. However, many current random beacon systems rely on threshold cryptographic setups or exhibit high computational costs, while others assume partial or bounded synchronous networks. To overcome these limitations, we propose HashRand, a computation and communication-efficient asynchronous random beacon protocol that uses a secure Hash function to generate beacons and pairwise secure channels. HashRand has a per-node communication complexity of O ( λn log( n )) bits per beacon. The computational efficiency of HashRand is attributed to the two orders of magnitude lower time of a one-way Hash computation compared to discrete log exponentiation. Interestingly, besides reduced overhead, HashRand achieves Post-Quantum security by leveraging the secure Hash function against quantum adversaries, setting it apart from other random beacon protocols that use discrete log cryptography. In a geo-distributed testbed of n = 160 nodes, HashRand produces 1 beacon every second, which is at least 4x higher than Spurt. We also demonstrate the practical utility of HashRand by implementing a Post-Quantum secure Asynchronous SMR protocol, which has a response rate of over 122k txns per second over a WAN at n = 40 nodes.
Pituitary Tumors: A 7-Year Retrospective Analysis of Outcome Following Neuronavigation Guided Trans-Nasal, Trans-Sphenoidal Microscope Aided Excision

: This is a 7-year retrospective analysis with the primary objective of noting the incidence of pituitary tumor recurrence after transnasal trans-sphenoidal approach using neuronavigation and operating microscope under a single operating unit. The secondary objective was to identify the type of tumor with highest secretory over activity and operative complications. The follow up period ranged between one to seven years. The result of this analysis indicates that the tumor size ranged between 5.7 X 5.7 mm to 42 X 24.5 mm. Headache was the commonest presenting symptom in 84.7% cases. The incidence of functioning adenomas in this series was 64.4% with prolactin being the dominant over secretory hormone in 47.4% cases. We noted an overall recurrence rate of 20.3%. The most important complication was a CSF leak noted in 13 patients (22.0%). CSF leak was fully cured in all patients by using a lumbar drainage catheter and/or placement of fat at the leakage site. There was only one mortality is this series.
Regulated necrosis pathways: a potential target for ischemic stroke

Abstract Globally, ischemic stroke causes millions of deaths per year. The outcomes of ischemic stroke are largely determined by the amount of ischemia-related and reperfusion-related neuronal death in the infarct region. In the infarct region, cell injuries follow either the regulated pathway involving precise signaling cascades, such as apoptosis and autophagy, or the nonregulated pathway, which is uncontrolled by any molecularly defined effector mechanisms such as necrosis. However, numerous studies have recently found that a certain type of necrosis can be regulated and potentially modified by drugs and is nonapoptotic; this type of necrosis is referred to as regulated necrosis. Depending on the signaling pathway, various elements of regulated necrosis contribute to the development of ischemic stroke, such as necroptosis, pyroptosis, ferroptosis, pathanatos, mitochondrial permeability transition pore-mediated necrosis and oncosis. In this review, we aim to summarize the underlying molecular mechanisms of regulated necrosis in ischemic stroke and explore the crosstalk and interplay among the diverse types of regulated necrosis. We believe that targeting these regulated necrosis pathways both pharmacologically and genetically in ischemia-induced neuronal death and protection could be an efficient strategy to increase neuronal survival and regeneration in ischemic stroke.
A Review of Land Data Assimilation System

The improvement and development of atmospheric and oceanic data assimilation system promotes the study of land data assimilation system (LDAS). In the beginning of 21st century, with the formation of the North American Land Data Assimilation System(NLDAS) and the Global Land Data Assimilation System(GLDAS), the study that utilizes satellite and radar data to assimilate soil moisture, surface temperature and energy flux has being carried on. At the same time, the land data assimilation has been the hotspot of the study in land surface process and hydrology process. In this paper, the main framework of land data assimilation system is summarized in detail. The North American Land Data Assimilation System (NLDAS) and Global Land Data Assimilation System (GLDAS), European Land Data Assimilation System (ELDAS) and West China Land Data Assimilation System (WCLDAS) are introduced. At last, some problems that need to be resolved in the study of land data assimilation system are pointed out.
Unraveling the Unusual Subgenomic Organization in the Neopolyploid Free-Living Flatworm Macrostomum lignano

Abstract Whole genome duplication (WGD) is an evolutionary event resulting in a redundancy of genetic material. Different mechanisms of WGD, allo- or autopolyploidization, lead to distinct evolutionary trajectories of newly formed polyploids. Genome studies on such species are important for understanding the early stages of genome evolution. However, assembling neopolyploid is a challenging task due to the presence of 2 homologous (or homeologous) chromosome sets and therefore the existence of the extended paralogous regions in its genome. Post-WGD evolution of polyploids includes cytogenetic diploidization leading to the formation of species, whose polyploid origin might be hidden by disomic inheritance. Earlier we uncovered the hidden polyploid origin of the free-living flatworms of the genus Macrostomum (Macrostomum lignano, M. janickei, and M. mirumnovem). Cytogenetic diploidization in these species is accompanied by intensive chromosomal rearrangements including chromosomes fusions. In this study, we unravel the M. lignano genome organization through generation and sequencing of 2 sublines of the commonly used inbred line of M. lignano (called DV1) differing only in a copy number of the largest chromosome (MLI1). Using nontrivial assembly free comparative analysis of their genomes, we deciphered DNA sequences belonging to MLI1 and validated them by sequencing the pool of microdissected MLI1. Here we presented the uncommon mechanism of genome rediplodization of M. lignano, which consists of (i) presence of 3 subgenomes, which emerged via formation of large fused chromosomes and its variants, and (ii) sustaining their heterozygosity through inter- and intrachromosomal rearrangements.
EphA2 as a phase separation protein associated with ferroptosis and immune cell infiltration in colorectal cancer

Colorectal cancer is one of the most common malignant tumors in the digestive system, and its high incidence and metastasis rate make it a terrible killer that threatens human health. In-depth exploration of the targets affecting the progression of colorectal cancer cells and the development of specific targeted drugs for them are of great significance for the prognosis of colorectal cancer patients. Erythropoietin-producing hepatocellular A2 (EphA2) is a member of the Eph subfamily with tyrosine kinase activity, plays a key role in the regulation of signaling pathways related to the malignant phenotype of various tumor cells, but its specific regulatory mechanism in colorectal cancer needs to be further clarified. Here, we found that EphA2 was abnormally highly expressed in colorectal cancer and that patients with colorectal cancer with high EphA2 expression had a worse prognosis. We also found that EphA2 can form liquid-liquid phase separation condensates on cell membrane, which can be disrupted by ALW-II-41-27, an inhibitor of EphA2. In addition, we found that EphA2 expression in colorectal cancer was positively correlated with the expression of ferroptosis-related genes and the infiltration of multiple immune cells. These findings suggest that EphA2 is a novel membrane protein with phase separation ability and is associated with ferroptosis and immune cell infiltration, which further suggests that malignant progression of colorectal cancer may be inhibited by suppressing the phase separation ability of EphA2.
The Variation and Influencing Factors of Discharge into the Sea from Wanquan River in Tropical Island

The discharge into the sea is an important component of river basin water cycle,identifying the change process and influencing factors of discharge into the sea is of great significance for the basin and delta wetland ecological security safety.Based on the measured data of precipitation and hydrological data at Jiaji Station which is the main controlling station on the river.The characteristics of discharge into the sea and its influencing factors of Wanquan River Basin in the past 52years(1956-2007)have been analyzed by using cluster technique method,GIS technology and other statistical methods.The research shows that the precipitation and runoff series exhibited a declining tendency and the runoff decreases obviously.Runoff coefficient series shows a drop change point around 2003.A regression equation based on the data of precipitation and runoff in 1956-1976 is obtained.By using this equation the impact of human activities on runoff can be quantified.The calculated results show that the land cover change is the important cause of runoff decrease after 2003.Changes in vegetation structure resulting in water conservation ecological function decline because of the destruction of mountain rainforest and illegal-planted economic forests in the basin.Prohibit felling rainforests and preventing planting commercial forests are critical to the maintenance of the island's ecological security.
Intelligent machines work in unstructured environments by differential neuromorphic computing

Efficient operation of intelligent machines in the real world requires methods that allow them to understand and predict the uncertainties presented by the unstructured environments with good accuracy, scalability and generalization, similar to humans. Current methods rely on pretrained networks instead of continuously learning from the dynamic signal properties of working environments and suffer inherent limitations, such as data-hungry procedures, and limited generalization capabilities. Herein, we present a memristor-based differential neuromorphic computing, perceptual signal processing and learning method for intelligent machines. The main features of environmental information such as amplification (>720%) and adaptation (<50%) of mechanical stimuli encoded in memristors, are extracted to obtain human-like processing in unstructured environments. The developed method takes advantage of the intrinsic multi-state property of memristors and exhibits good scalability and generalization, as confirmed by validation in two different application scenarios: object grasping and autonomous driving. In the former, a robot hand experimentally realizes safe and stable grasping through fast learning (in ~1 ms) the unknown object features (e.g., sharp corner and smooth surface) with a single memristor. In the latter, the decision-making information of 10 unstructured environments in autonomous driving (e.g., overtaking cars, pedestrians) is accurately (94%) extracted with a 40*25 memristor array. By mimicking the intrinsic nature of human low-level perception mechanisms, the electronic memristive neuromorphic circuit-based method, presented here shows the potential for adapting to diverse sensing technologies and helping intelligent machines generate smart high-level decisions in the real world.
TAPA-CS: Enabling Scalable Accelerator Design on Distributed HBM-FPGAs

Despite the increasing adoption of Field-Programmable Gate Arrays (FPGAs) in compute clouds, there remains a significant gap in programming tools and abstractions which can leverage network-connected, cloud-scale, multi-die FPGAs to generate accelerators with high frequency and throughput. To this end, we propose TAPA-CS, a task-parallel dataflow programming framework which automatically partitions and compiles a large design across a cluster of FPGAs with no additional user effort while achieving high frequency and throughput. TAPA-CS has three main contributions. First, it is an open-source framework which allows users to leverage virtually"unlimited"accelerator fabric, high-bandwidth memory (HBM), and on-chip memory, by abstracting away the underlying hardware. This reduces the user's programming burden to a logical one, enabling software developers and researchers with limited FPGA domain knowledge to deploy larger designs than possible earlier. Second, given as input a large design, TAPA-CS automatically partitions the design to map to multiple FPGAs, while ensuring congestion control, resource balancing, and overlapping of communication and computation. Third, TAPA-CS couples coarse-grained floorplanning with automated interconnect pipelining at the inter- and intra-FPGA levels to ensure high frequency. We have tested TAPA-CS on our multi-FPGA testbed where the FPGAs communicate through a high-speed 100Gbps Ethernet infrastructure. We have evaluated the performance and scalability of our tool on designs, including systolic-array based convolutional neural networks (CNNs), graph processing workloads such as page rank, stencil applications like the Dilate kernel, and K-nearest neighbors (KNN). TAPA-CS has the potential to accelerate development of increasingly complex and large designs on the low power and reconfigurable FPGAs.
Deep Learning based CNN Model for Classification and Detection of Individuals Wearing Face Mask

In response to the global COVID-19 pandemic, there has been a critical demand for protective measures, with face masks emerging as a primary safeguard. The approach involves a two-fold strategy: first, recognizing the presence of a face by detecting faces, and second, identifying masks on those faces. This project utilizes deep learning to create a model that can detect face masks in real-time streaming video as well as images. Face detection, a facet of object detection, finds applications in diverse fields such as security, biometrics, and law enforcement. Various detector systems worldwide have been developed and implemented, with convolutional neural networks chosen for their superior performance accuracy and speed in object detection. Experimental results attest to the model's excellent accuracy on test data. The primary focus of this research is to enhance security, particularly in sensitive areas. The research paper proposes a rapid image pre-processing method with masks centred on faces. Employing feature extraction and Convolutional Neural Network, the system classifies and detects individuals wearing masks. The research unfolds in three stages: image pre-processing, image cropping, and image classification, collectively contributing to the identification of masked faces. Continuous surveillance through webcams or CCTV cameras ensures constant monitoring, triggering a security alert if a person is detected without a mask.