bluuebunny/crossref_metadata_2025 huggingface dataset:
MAXIMIZING WORKPLACE EFFICIENCY AND COLLABORATION: THE IMPACT OF COFFEE BREAKS ON PRODUCTIVITY AND TEAM DYNAMICS
Authors: Maspul Kurniawan Arif
Published: February 2024

This study investigates the impact of specialty coffee on workplace coffee breaks, with a focus on worldwide trends and its unique influence in Saudi Arabia. Specialty coffee has grown in popularity around the world due to its outstanding quality, precise sourcing, and distinct flavor profiles. With the emergence of specialty coffee, coffee breaks have been transformed into chances for increasing work productivity and establishing great team environments. Specialty coffee boosts employee happiness, contentment, and engagement by giving a more sensory experience. Its precise sourcing and roasting techniques can also improve cognitive function and focus, resulting in increased productivity at work. Furthermore, the emphasis in specialty coffee on sustainability and social responsibility connects with employees, instilling a feeling of purpose and pride. Practical strategies for implementing specialty coffee into office coffee breaks are reviewed, including ethical sourcing, variety, employee education, and community support. The findings emphasize the significance of embracing specialty coffee as a global trend and capitalizing on its potential to generate significant and delightful coffee break experiences in a variety of workplace cultures, including Saudi Arabia.
Rancang Bangun Information Board Berbasis Cloud Digital Signage Platform
Authors: Suatkab Syukri Gazali , Tupan Hendrik K. , Pessireron Marcus F.
Published: February 2024

Informasi merupakan suatu hal yang sangat penting, baik bagi individu maupun perusahaan atau organisasi. Sayangnya, dalam lingkup tertentu, penyampaian informasi masih dilakukan secara konvensional yaitu melalui pesan menggunakan aplikasi media sosial seperti whatapp serta menggunakan papan pengumuman dengan media kertas. Hal tersebut menjadi kurang atraktif dan menarik. Selain itu informasi yang diperbarui juga terbatas oleh tempat dan waktu sehingga tidak bisa diperbarui dari manapun atau kapanpun. Untuk mengatasi hal tersebut maka perlu adanya media informasi digital yang dapat digunakan untuk mentransformasi layanan informasi model lama. Untuk itu maka dibangun sistem penyampaian informasi digital (digital signage) menggunakan platform yodeck dan mikrokomputer Raspberry Pi yang dimanfaatkan sebagai player dan penghubung dengan platform. Hasilnya pengelolaan dan pembaruan konten dapat dilakukan dari mana saja dan kapan saja. Berdasarkan hasil implementasi digital signage di jurusan Teknik Elektro Politeknik Negeri Ambon, penggunaan Raspberry Pi sebagai media player sangat memudahkan pengelolaan layout dan juga konten, berikutnya integrasi layanan berbasis cloud memungkinkan pengelolaannya bisa dilakukan dimanapun dan kapan pun. Selain itu, tersedianya widget yang beragam memudahkan administrator konten untuk menyesuaikan informasi yang dibutuhkan dengan rancangan desain antarmuka yang sangat menarik, seperti Calendar Events Feed, Rich Text, WikiQuotes, Grafana, Web Pages, serta add-in online lainnya yang dapat diakses secara real-time.
Evaluasi Kinerja Lalu Lintas Simpang Empat Tak Bersinyal Tidak Simetris dan Pengaruh Tak Simetris Jl Slamet Riyadi - Panjaitan 1 dan Panjaitan 2 Kota Ambon.
Authors: Maitimu Anthoneta
Published: February 2024

Masalah yang sering dijumpai dalam transportasi perkotaan adalah kemacetan lalu lintas baik pada ruas jalan maupun pada simpang. Persimpangan sebagai salah satu tempat pertemuan ruas- ruas jalan dan berfungsi sebagai tempat kendaraan malakukan perubahan arah pergerakan. Namun daerah tingkat pergerakan yang beragam dari berbagai jenis kendaraan mengakibatkan tundaan perjalanan yang cukup besar pada simpang jalan slamet riyadi - jalan panjaitan satu dan dua menunjukan kondisi arus lalu lintas yang cukup padat sehingga sering terjadi konflik lalu lintas pada persimpangan oleh karena itu perlunya dipikirkan pemecahan masalah pada persimpangan ini tujuan penelitian ini untuk mengevaluasi tingkat kinerja simpang operasional simpang tak bersinyal saat ini pada simpang empat. Metode perhitungan menggunakan metode manual kapasitas jalan Indonesia (MKJI 1997) tingkat kinerja operasional simpang sudah tidak dapat melayani dengan baik. survey distrubusi arus lalu lintas dilakukan dengan interval waktu 5 menit untuk menentukan periode jam puncak. Berdasarkan hasil survey dan perhitungan diperoleh jam puncak pada hari senin tgl 11 bulan july tahun 2022 pukul 10:00 – 11:00. hasil evaluasi kinerja simpang kondisi saat ini kurang efektif lagi dalam memberikan pelayanan yang baik, dengan jumlah arus lalu lintas yang masuk pada persimpangan 5856 SMP/Jam dan kapasitas 4964 SMP/Jam dan derajat kejenuhan 1,18, maka tundaan lalu lintas yang terjadi 31,40 detik/SMP dan peluang antrian antara 114,07 %,serta tingkat pelayanan E.
ANALISA SISTEM DRAINASE JALAN DALAM UPAYA PENANGGULANGAN GENANGAN DI KAWASAN JALAN MERPATI KELURAHAN RIJALI KOTA AMBON
Authors: Manabung Arnold Axel , Talakua Elisabeth , Istia Penina
Published: February 2024

Permasalahan yang terjadi pada sistem drainase Jalan Merpati, Kelurahan Rijali adalah selalu mengalami banjir pada saat hujan dengan intensitas tinggi. Pada beberapa drainase air selalu meluap keluar dari dalam dan membuat ruas jalan di genangi air. Faktor yang mempengaruhi yaitu dengan adanya endapan lumpur atau sampah pada dasar drainase. Tujuan dari penelitian ini untuk menganalisis debit aliran pada saluran drainase dan dan dari kapasitas penampang saluran drainase yang terdapat di kawasan Jalan Merpati Kelurahan Rijali, kemudian membandingkan antara debit rencana (Qrencana) dengan debit yang dialirkan oleh saluran (Qsaluran). Penelitian ini adalah jenis penelitian kualitatif dengan menggunakan teknik pengumpulan data, observasi, dokumentasi, dan studi literatur. analisis data yang digunakan adalah Analisis hidrologi berupa analisis frekuensi curah hujan,   koefisien aliran permukaan, analisis waktu konsentrasi, analisis intensitas curah hujan dan analisis debit rencana. Analisis hidrolika berupa analisis kapasitas penampang saluran drainase dan evaluasi debit saluran dengan debit rencana. Dari hasil perhitungan debit kapasitas dam debit rencana 10 tahun, ternyata debit kapasitas ketiga drainase pada pada lokasi penelitian yaitu Jalan Merpati, Kelurahan Rijali diperoleh Qsaluran< Qrencana. Perlu perubahan dimensi penampang pada drainase pada kawasan Jalan Merpati, Kelurahan Rijali sehingga bisa menampung air hujan pada kawasan tersebut sehingga kawasan tersebut tidak lagi banjir pada saat hujan lebat dalam waktu yang lama.
Unpacking Public Perceptions of Qris with Twitter Data: A Vader And LDA Methodology
Authors: Ulya Dzakiya Ishmatul , Kunaefi Anang , Rolliawati Dwi , Nugroho Bayu Adhi
Published: February 2024

QRIS, a mobile payment transaction system standardized by Bank Indonesia, has become the subject of extensive public discourse on Twitter. Employing VADER for sentiment analysis and LDA for topic modeling, this study aims to capture the nuanced perspectives of the Indonesian public toward QRIS. Our methodology includes real human validation for tweets that have been initially labeled by VADER. Our unique contributions lie in employing a mixed-methods approach for comprehensive sentiment and topic analysis, as well as making our dataset publicly available for future research. We achieve a sentiment labeling accuracy of 81.66%, uncovering that 67% of the sentiment towards QRIS is positive, 28.2% negative, and 4.17% neutral. Positive tweets mostly cover six dominant topics with a value of 0.488037, whereas negative sentiments are concentrated around three dominant topics with a   value of 0.383938. These findings not only affirm the generally positive public response towards QRIS but also highlight areas requiring attention for its continued success. Our study translates these insights into actionable recommendations, aiming to provide a multidimensional understanding that stakeholders can leverage for system enhancement. This study serves as a foundation for future works in sentiment analysis and public opinion mining related to financial technologies, particularly in the Indonesian context.
Effects of FeNi3/SiO2 /GO nanoparticles on the mechanical and durability properties of concrete
Authors: Shandiz Afshin Charani , Honarbakhsh Amin , Zhiani Rahele , Amarloo Fatemeh
Published: February 2024

Recent research in the construction industry supports the idea that nanomaterials can partially replace cement. A recently suggested material as a suitable substitute for cement in concrete is graphene oxide nanocomposite. As a result, in this laboratory study, FeNi3/SiO2/GO nanoparticles [NFSG] and SiO2 nanoparticles [NS] partially replace cement by 1, 2, and 3% by mass after their synthesis and confirmation by FT-IR, SEM and TEM analyses and their impact on the mechanical and durability characteristics of the specimens at ages 7, 28, and 90 days were examined. The findings imply that the designs with the highest mechanical properties tests produced the best results. These designs used 2% of NFSG and 2% of NS substituting cement. After 28 days, NFSG-containing concrete increased compressive strength by 15% and splitting tensile strength by 13%. FTIR spectra demonstrated that specimen containing 2% of NFSG produced more C-S-H [calcium silicate hydrate] gel, improving the microstructure of concrete and subsequently its properties.
Strength and Fatigue Analysis of LNG Cylinder Frame on Heavy Truck
Authors: Zhang Yu , Xu Honghai
Published: February 2024

The LNG cylinder frame is one of the most important components of the LNG fuel device on heavy trucks. Under emergency braking, sharp turning, and actual road impact loads, the cylinder frame is vulnerable to static strength damage and fatigue damage caused by insufficient fatigue strength, which affects the safe operation of heavy trucks. Hypermesh is used to process the grid, Nastran is used to conduct static strength analysis, and Ncode is used to conduct fatigue analysis. The maximum stress value, maximum displacement value, fatigue damage value, and other data of the cylinder frame under different working conditions are obtained. The safety and structural weaknesses of the cylinder frame are analyzed, and an improvement scheme is proposed and verified through finite element analysis. The results show that the static strength safety factor of the improved cylinder frame is increased by 113%, and the maximum fatigue damage values at 8000 km and 16000 km are decreased by 53.5% and 27.9%, respectively.
Simulation of the Relationship Between Die-Cutting Moving Platform and Crankshaft Motion
Authors: Zhou Yunfei , Cheng Bin , Yang Hongguang , Wang Cheng
Published: February 2024

This article introduces the simulation analysis of the motion characteristics of the die-cutting moving platform system. By establishing a three-dimensional model of the die-cutting moving platform, simulate and analyze the operating characteristics of the die-cutting machine, and grasp the basic characteristics of the moving platform movement. This article simulates the relationship curves between the displacement of the moving platform system and the crankshaft angle, the speed of the moving platform and the crankshaft angle, and the acceleration of the moving platform and the crankshaft angle, and analyzes the characteristics of each motion stage. Combining simulation calculations and mathematical models of a moving platform system can intuitively and accurately analyze and judge the motion characteristics and laws of the moving platform. By analyzing the motion characteristics and laws of the die-cutting moving platform, reference can be provided for the design, manufacturing, and optimization improvement of die-cutting machines.
Spatial-Temporal Evolution Characteristics and Influencing Factors of Vegetation Coverage in Tianjin Binhai International Airport
Authors: Ti Yue , Fan Ruiyan , Xu Ziyi , Yin Ying
Published: February 2024

Fractional vegetation coverage (FVC) is an important parameter of regional ecological environment quality. Taking Tianjin Binhai International Airport as the research center, Dongli District and Hedong District are selected as the research area, based on the Landsat remote sensing images from 2000 to 2019, and combined with the pixel dichotomy model to calculate FVC. Using linear regression and F-test to analyze the temporal and spatial evolution trend of FVC, using the coefficient of variation to analyze the fluctuation of FVC, the geographic detector model is used to explore the climatic factors (annual average temperature, annual precipitation), economic factors (population density, GDP) and human activity factors (take-off and landing sorties and passenger flow) to explain the strength of FVC. The result shows that the annual average FVC in the study area shows a downward trend as a whole from 2000 to 2019, and there were differences in the changing trends of different grades of FVC. The FVC in the study area fluctuates stably as a whole, and the vegetation coverage of Tianjin Binhai International Airport is low and the stability is poor. There are significant differences in the explanatory power of each influencing factor for FVC in the study area. The research results are of great significance to the environmental protection of airports and the sustainable development of airports.
Multi-Objective Optimization of Building Integrated Energy System Considering Demand Response and User Comfort
Authors: Zhou Xiangyu , Qin Zhenyi , Wang Weishuai , Chi Qingqing , Li Mengwen
Published: February 2024

The building itself has a certain thermal inertia, which makes the energy supply process of the energy system flexible. At the same time, the comfort of the user should be ensured in the process of building energy supply adjustment. To solve the above problems, this paper proposes a considering demand response (DR) and user comfort of building integrated energy system (BIES) multi-objective optimization method. Firstly, a typical BIES model and a device power model are constructed. Secondly, according to the price elasticity matrix and building thermal inertia, the price-type and regulation-type DR models are constructed. Then, according to the economic, environmental protection, and comfort requirements of the BIES, considering the constraints of power balance, equipment operation, DR, and so on, the BIES optimal scheduling model is established. The multi-objective gray wolf optimizer (MOGWO) algorithm is optimized by chaos operator and t distribution. The model is solved and the optimized algorithm is to obtain the Pareto optimal solution set, using the VIKOR method for the optimal decision solution set. Finally, the BIES in a building is used as an example for analysis, and the results show that the proposed method can effectively balance the efficiency of system operation, environmental protection, and energy efficiency.
Research on Hydrogeology and Water Resources Evaluation Based on Big Data Technology
Authors: Xu Gaofeng , Sun Jie
Published: February 2024

With the development of science and technology, the amount of hydrological information data has undergone tremendous growth. How to fully utilize these large-scale data to support decision-making and water resource evaluation is currently a problem faced by scientists and society. In the traditional process of water resource allocation, the calculation of reservoir water balance results in a huge amount of abandoned water, resulting in the waste of a large amount of available water resources. By training Big data, the model self-learning can quickly analyze the characteristics of the river water level discharge relationship, fit the water level discharge relationship curve, and obtain the water balance, which reduces the number of flow measurements required to fit the water level discharge relationship curve by traditional methods, thus reducing errors, improving accuracy, and reducing time and economic costs.
Prediction of Pore Water Pressure of Iron Concentrate Using Phase Space Reconstruction Long Short-Term Memory
Authors: Li Senyuan , Zhou Hang , Zhang Jianwei , Liu Jian
Published: February 2024

Ship shaking can cause cargo PWP (pore water pressure) increasing, the prediction of PWP is helpful for navigation safety. This paper presents a machine learning method for PWP time series prediction learning. Source data of iron concentrate are collected from scaled model test, they are used to train a time series prediction model and test the accuracy and effective of our method. The proposed method is based on PSR (phase space reconstruction) and LSTM (Long Short-Term Memory) Network. A input matrix is constructed by phase space reconstruction technology and the prediction model can be learned by a specific Long Short-Term Memory Network. The single-step pore water pressure prediction model is achieved, when MSE loss function value is minimum, the R value 0.98 is maximum is better than the baseline R value 0.93. This result suggests that this PSR-LSTM is more effective than LSTM, it can be a complement for physical test and numerical simulation.
Rice Yield Prediction Based on Deep Learning
Authors: Chang Xuning
Published: February 2024

As the global population continues to grow at an unprecedented rate, the demand for food production has become increasingly pressing. In order to meet this demand, precision agriculture has emerged as a critical approach to optimize crop yield and minimize resource waste. This paper provides a comprehensive overview of precision agriculture and its significance in modern agriculture. Furthermore, the paper presents a novel approach to predicting rice yield using deep learning models, specifically the LSTM and GRU models. The effectiveness of these models is demonstrated through extensive experimentation and analysis, which shows that they are highly successful in accurately predicting rice yield. The results of this study have significant implications for the future of agriculture, as they provide a powerful tool for farmers to optimize their crop yield and improve their overall efficiency. Overall, this paper highlights the importance of precision agriculture and the potential of deep learning models in predicting crop yield.
Analysis of Automotive Thermal Management System Using One-Dimensional Simulation
Authors: Zhao Hongxia , Lv Jiangyi , Liu Minjie , Zhao Chang
Published: February 2024

This article takes the cooling system of a certain vehicle as the model and applies simulation tools to establish its cooling system and front cabin air side model. It inputs boundary conditions such as the flow resistance characteristics of each component. Then, it completes the steady-state simulation calculation of the vehicle system under different working conditions and optimizes the design of the original cooling system model. Calculating through simulation, we obtain the flow rate, pressure distribution, and temperature rise of the system and various components. We predict and evaluate the working capacity of the cooling system and propose improvement suggestions based on the calculation and analysis results. This plays an important guiding role in the structural design and testing of the cooling system, greatly reducing research and development time and reducing research and development costs. The calculation results show that the flow rate of each component in the rated point, heating test condition, and idle condition of the original plan has decreased compared to a certain model on the same platform under the same working condition. The temperature difference between the radiator and the flow rate of the oil cooler does not meet the specification requirements. It is recommended to continue optimizing the design.
A Rolling Bearing Degradation Index Construction Method Based on Deep Residual Networks
Authors: Hu Yuanhan , Pan Yuna , Xie Kun , Ma Xianghua
Published: February 2024

The evaluation of performance degradation in rolling bearings is a crucial technology for active maintenance. As the traditional construction method of rolling bearing degradation index is heavily dependent on manual screening features, this paper proposes an end-to-end construction method of degradation index based on Deep Residual Networks (DRN). In this method, two nodes are established in the Softmax output layer of DRN, which respectively represent the probability of a normal state and the probability of a failure state. The training sample is taken as the normalized amplitude spectrum of the normal state. The performance degradation index of the rolling bearing is constructed by taking into account the output probability of the normal node of the sample to be evaluated. The method’s effectiveness and superiority are confirmed through the use of various experimental data sets, when compared to other indexes.
Study on PM 2.5 Concentration Prediction Model Based on Bagging-Gradient Boosting Decision Tree
Authors: Hu Xueka , Shi Jiahao , Liang Riliu
Published: February 2024

To accurately predict PM 2.5 concentration and provide a reference for early warning and control of PM 2.5 pollution, the PM 2.5 concentration prediction model based on the Bagging-Gradient Boosting Decision Tree (GBDT) is proposed. Pearson correlation coefficient and distance correlation coefficient are used for feature selection by analyzing the linear and nonlinear correlations between PM 2.5 and relevant initial feature variables. The bagging algorithm is used to construct multiple new samples with bootstrap sampling and GBDT is used to train the new samples to obtain weak models. The mean value method is used to assemble the weak models into the final strong model and obtain the final prediction results. The results show that for the Bagging-GBDT model, the RMSE is 4.83, the goodness of fit R2 is 0.94, the predicted value can fit the actual value well, and about 80% prediction error is between [-5, +5]. It can be concluded that the Bagging-GBDT model can predict PM 2.5 concentration accurately and the error between the predicted value and the actual value is acceptable. Otherwise, compared with some machine learning models, this model has better performance, higher accuracy, better stability, and better fitting effects.
Numerical Prediction of Pressure Fluctuation Included by Propeller on Hull Surface
Authors: Zhong Yan , Feng Haijun , Qiu Yun , Li Guoping , Chen Changsheng
Published: February 2024

In this paper, the DDES delayed separated vortex model is used to simulate the propeller excitation force of a pod, and the three-dimensional vortex structure characteristics and the propeller induced excitation force characteristics under the coupling effect of the hull pod are obtained. The calculation results show that the main characteristic frequencies of the pressure fluctuation on the surface of the pod are axial frequency and blade frequency, and there are four times of axial frequency at some measuring points. The leading edge of the davit and the propeller jet will have a strong interference effect, resulting in high blade frequency amplitude at the blade radius of the leading edge of the davit. The optimization of the davit structure is an effective way to reduce the induced excitation force of the pod propeller.
Positive Solution of Moving Platform Position Based on Bat-Iterative Algorithm
Authors: Jia Lishan , Xu Haijun
Published: February 2024

To address the forward position problem of a 6-DOF moving platform, a Bat-iterative method leveraging the Bat algorithm was proposed as a solution. By combining the Bat algorithm with the traditional Newton-Raphson iterative algorithm, the convergence speed and accuracy of the algorithm can be improved while the convergence and global search ability are guaranteed. The concrete implementation process of the algorithm is given, and the corresponding positive solution problem of 6-DOF parallel mechanism is solved by using the algorithm, and the corresponding operation example is given. At the same time, the inverse solution method is used to obtain the data set for error analysis and comparison. In summary, the comparison results demonstrate that the Bat-iterative algorithm offers notable benefits such as fast computation speed and high precision. As a result, it proves to be well-suited for practical engineering applications, meeting the necessary requirements effectively.
Improved Glass Composition Analysis and Identification of Cultural Heritage with Limited Data Using Data Augmentation and CatBoost
Authors: Hu Xianmei , Zhang Jinyu , Wang Ziyang , Zhao Jiahui
Published: February 2024

Glass artifacts play a significant role in cultural heritage, offering valuable insights into ancient craftsmanship and cultural exchange. However, accurately analyzing and identifying ancient glass objects presents challenges due to limited data. This study aims to enhance the analysis and identification of glass compositions in cultural heritage by employing data augmentation techniques and the CatBoost prediction model. Firstly, data augmentation techniques are applied to expand the limited dataset, increasing sample quantity and diversity to improve the model’s generalization capability. The TOPSIS method is employed to comprehensively evaluate different augmentation factors and select the most suitable ones. Subsequently, the CatBoost prediction model is utilized, and the model parameters are optimized using a random search method to further enhance predictive performance. Experimental research on ancient glass artifacts validates the effectiveness and feasibility of the proposed methods. The final model demonstrates high predictive performance and a good fit on the training set, cross-validation set, and test set. For example, when predicting the sodium oxide content before weathering in glass artifacts, the average R-squared(R2) reaches 0.998, and the Mean Squared Error(MSE) is 0.003. These results signify the accurate prediction of glass artifact compositions and the model’s stable predictive capabilities across different datasets. Utilizing the predicted chemical composition, the identification of glass artifacts achieves a classification accuracy of 100%, indicating the excellence of the model. In conclusion, this study presents an improved approach for analyzing and identifying glass compositions by overcoming the limitations posed by limited data through data augmentation and the CatBoost model. These advancements provide valuable tools and methods for preserving and researching cultural heritage, contributing to the progress of ancient civilization studies and technological development.
Mathematical Modeling for Compositional Analysis and Identification of Ancient Glass
Authors: Cao Xin
Published: February 2024

This article aims to establish an interpretable machine-learning classification model and use various SPSSPRO algorithms for computational analysis. Ancient glass is highly susceptible to weathering, which in turn leads to changes in its chemical composition. This article is based on this and studies the correlation between various variables, the classification rules of high potassium glass and lead barium glass, the analysis of weathering components, and the identification of categories. This provides relevant references and a basis for relevant departments to identify ancient glass and protect glass relics.
Control Method and Model of Constant Cutting Depth for Cutting Low Stiffness Parts
Authors: Sheng Zhichao , Jin Xin , Gao Ruilin , Guo Jiajing , Li Chaojiang
Published: February 2024

During the cutting process of low stiffness parts, deformation is prone to occur, making it difficult to ensure the dimensional accuracy and surface roughness of the parts. The machining of the neck of the dynamically tuned gyroscope’s flexible joint is taken as an example. Based on the optimization of cutting parameters using a cutting parameter - surface roughness neural network model, which is used to control the surface roughness of the part, a constant cutting depth control method is explored and a mathematical model is established to address the problem of cutting depth’s dynamic changes caused by low or variable stiffness of the part structure, which affects dimensional accuracy. Then a model foundation for dimensional accuracy control and process optimization of low or variable stiffness parts is established.
A New Method for Improving the Accuracy of Word Segmentation in Modern Chinese Texts
Authors: Zhang Yan
Published: February 2024

Chinese does not adopt the form of word segmentation in writing like English. The role of words in NLP is enormous and can have a significant impact on subsequent tasks. Presently, NLP research in China mainly focuses on modern Chinese, leaving a gap in studying the pre modern Chinese stage during the late Qing Dynasty to early Republic. Many texts from this time were in traditional paper books with varying preservation conditions, making it hard to obtain a representative dataset, limiting in-depth research. Most texts haven’t undergone digital processing, lacking segmentation or annotation. This poses great challenges for researchers. Researchers must design word segmentation algorithms from scratch, increasing difficulty and workload. By using N-gram to extract bigram and trigram fragments, and combining with 100 Year Chinese New Words and Phrases Dictionary and other books, this paper constructs a Chinese wordlist at the end of the Qing Dynasty to the beginning of the Republic of China. 10000 sentences were randomly selected from the corpus constructed in this article and manually segmented and annotated. The experimental results show that adding the wordlist constructed in this article has indeed improved the accuracy of word segmentation for most of these 10000 sentences. Specifically, the three software (CoreNLP, FudanNLP, and Jieba) show a certain degree of performance improvement when using the wordlist. For HanLP, the use of wordlist in this set of data did not bring significant performance improvement, or even a slight decline to some extent.
ContextualHomeLLM: A Context-Aware Large Language Model for Smart Homes
Authors: Duan Hucai , Li Jun , Li Peng
Published: February 2024

ContextualHomeLLM is a state-of-the-art Large Language Model (LLM) specifically designed to enhance user interactions and smart home management. Leveraging the power of Transformer architecture, this model is trained to understand, interpret, and respond to user queries, commands, and contextual cues within the smart home ecosystem. By integrating advanced contextual understanding, personalized recommendations, and real-time control, ContextualHomeLLM offers an innovative approach to seamless smart home control and assistance.
Research on Chinese Animal Disease Text Named Entity Recognition Based on Data Augmentation
Authors: Wang Ling , Zhao Liang
Published: February 2024

Animal disease-related information serves as an important reference. This paper focuses on the study of Named Entity Recognition (NER) in animal disease texts using a dataset constructed from animal disease books. However, the dataset exhibits imbalanced distribution of different types of entities, which affects the learning effectiveness of the models. In this method, firstly, a small amount of data was enhanced based on the template data augmentation method, and then the overall data was enhanced based on the improved EDA method. On the enhanced dataset, the accuracy of NER based on the BiLSTM network and CRF model increased by 3%. The recall rate saw a significant improvement of 17%, and the F1 value increased by 10%. The experimental findings suggest that the data augmentation technique presented in this paper can improve the model’s learning effectiveness on the dataset related to livestock and poultry diseases.
Analyzing commercial grape farm efficiency in Armavir region (Armenia) by using two-stage empirical approach
Authors: Asatryan Hovhannes , Aleksanyan Vardan , Asatryan Samvel , Manucharyan Meri
Published: February 2024

The purpose of this paper is to provide an empirical assessment of the economic efficiency of grape-producing farms in Armenia. Upon reviewing various field-related studies the frontier analysis was singled out as a methodological base of this study. More specifically two-stage empirical analysis was performed, which includes the measurement of efficiency levels of grape farms by implementing the DEA technique and then assessing the determinants of obtained efficiency scores by performing Tobit modeling. To obtain necessary data, 365 grape farms from the Armavir region were surveyed. The main findings of this paper suggest that the average efficiency score for grape farms is 0.72, and there is room for improvement in the economic performance of farms with 28%. The main determinants of farm efficiency were cultivated grape varieties, farm size, and selling prices of grapes. The obtained results mainly support the findings of similar studies carried out for various viticulture regions across the world. This study provides some methodology bases for further expansion of similar studies both in terms of including the other Armenian viticulture regions and different years to explore the changes in the efficiency of grape farms over time. This article provides a base of knowledge for policymakers, scholars, researchers, investors, and credit companies for their decision-making processes and other purposes.
Enhancing Students’ Narrative Writing Skills through Folktale Films
Authors: Agustin Dery Tria , Yana Pramugara Robby
Published: February 2024

This research aimed to improve the writing skills of ninth-grade students at a junior high school in Yogyakarta, Indonesia. The study used a Classroom Action Research (CAR) design, incorporating folktale films as a learning tool. Twenty-eight students (Class A) participated, with collaboration from an English teacher. Data were collected through observations, interviews, and tests, employing a triangulation method. The research consisted of two cycles, following the action research phases: plan, action, observation, and reflection. Results showed a significant enhancement in students' writing skills with the use of folktale films. These films increased confidence and participation in English writing, leading to effective narrative text creation. The students actively engaged in lessons, positively impacting their overall writing abilities, as observed and reflected in improved test scores. The paper concludes with practical implications based on the study's findings.
Choosing to Stay: Unpacking Immobility Amidst Adversity in Migration Studies
Authors: Olumba Ezenwa E.
Published: February 2024

Current migration studies inadequately explore the staying behaviour and experiences of those in conflict or disaster-stricken regions, especially those who choose voluntary immobility. This paper introduces the ‘Resilience-Accessibility Framework’, derived from existing frameworks and a qualitative study in a conflict-affected region. This framework serves as an analytical tool for exploring the staying behaviour of individuals or community members who choose to stay put amidst adversities. Additionally, it broadens the scope of (im) mobility categories to include a wider range of migratory experiences. By introducing this framework for studying immobility, this paper enriches academic discourse and offers vital insights for policymaking.
Understanding Creativity
Authors: Lambert Philip
Published: February 2024

Creativity has become highly valued in all aspects of life. Several decades ago the debate about creativity centered on whether creativity could be enhanced, or if it was something you were born with. Now researchers seem to be consistently proclaiming that it can. But the results are far from uniform. Even the programs with the most consistent record fail far too often to instill confidence, and other, often very popular programs, have a dismal record. From Creative Problem Solving to the Purdue Creative Thinking program, and from de Bono Thinking to Synectics and TRIZ. Which has the best record? Why? Why are they not more consistent? Are there other approaches that might improve these creative cognition enhancement approaches? This review uncovered those questions, and while it doesn’t propose to present answers, it does attempt to point the way for future research to shed a little more light on the mysteries of creativity. It also proposes that all of these fragmented results may make a little more sense – and may begin to look like pieces of one whole, rather than discrete, conflicting data points – under the light of a Complexity Theory of Creativity.
La obesidad y los edulcorantes. ¿Qué nos dicen los modelos animales sobre el consumo crónico de edulcorantes?
Authors: Mendoza Pérez Samuel , García Gómez Rolando Salvador , Durán Domínguez de Bazúa María del Carmen
Published: February 2024

El exceso de masa y la obesidad son enfermedades de etiología multifactorial que han incrementado su prevalencia a nivel mundial. En las últimas décadas la industria alimentaria ha utilizado a los edulcorantes artificiales para sustituir a los hidratos de carbono simples de sus formulaciones. Sin embargo existen aún dudas sobre los efectos del consumo a largo plazo de estos aditivos alimentarios. Diversas investigaciones han puesto en duda la aseveración de que los edulcorantes artificiales son metabólicamente inertes. Los modelos animales permiten estudiar el efecto crónico de diversas sustancias debido a que su esperanza de vida es mucho más pequeña que la humana. En la presente investigación se evaluó el efecto del consumo crónico de edulcorantes nutritivos y no nutritivos durante 480 días sobre la ganancia de masa corporal y los patrones de ingesta de alimento, bebida y energía utilizando como modelo animal ratas macho y hembra recién destetadas de la estirpe Wistar. El consumo crónico de edulcorantes no nutritivos no alteró la ganancia de masa. Sin embargo, sí se vieron afectados los patrones de ingesta de alimento y bebida. Probablemente no se vio afectada la ganancia de masa porque los edulcorantes no nutritivos se dieron junto con una dieta balanceada. El modelo animal permitió evaluar el efecto de consumir durante lo equivalente a 50 años humanos con solamente 480 días de evaluación.
Pulque: contenido probiótico y potencial en la industria biotecnológica
Authors: Rodríguez Juárez Fernanda A. , Urbina Carrasco Héctor S. , Zapata Hernández Alembert
Published: February 2024

El pulque es una bebida tradicional mexicana que antiguamente era consumida por sus propiedades medicinales y su contenido alcohólico. Diversos estudios han caracterizado los microorganismos que este brebaje contiene, principalmente bacterias ácido lácticas (BAL) y levaduras. Estos microorganismos son los que proporcionan las características sensoriales propias a la bebida. A través de diferentes pruebas de laboratorio, se pueden identificar aquellas cepas con potencial probiótico, las cuales ofrecen numerosos beneficios a quienes lo consumen. Dichos microorganismos también producen sustancias de interés biotecnológico, principalmente relacionados con la mejora de la salud humana.
México: un ejemplo sobre la estrecha relación de los medios de comunicación, el estado y el sistema capitalista
Authors: Aguilar Morales Juana Andrea
Published: February 2024

En la actualidad, el sistema capitalista tiene injerencia en todas las áreas de la vida cotidiana, incluso en cómo se maneja la información que los medios de comunicación difunden a la sociedad día a día. A través de ellos, se revela la estrecha relación de dependencia directa entre el Estado y el sistema capitalista para poder seguir reproduciendo su ideal de subyugación al proletariado en la sociedad moderna. Si bien Marx es uno de los exponentes más importantes en torno a la crítica del capitalismo, Althusser complementa cómo el sistema capitalista aborda todas las instituciones para poder obtener su cometido de dominación de las masas por medio del desarrollo de una ideología que le convenga tanto al capitalista como al Estado y que se reproduzca continuamente en uno de los aparatos ideológicos más influyentes: los medios de comunicación. Esta relación permite entender cómo los medios de comunicación están al servicio tanto del Estado como del sistema capitalista para poder seguir sometiendo a la sociedad a creer lo que ambos entes decidan sobre una situación determinada.
Transdisciplinariedad: nuevo derrotero en el conocimiento científico
Authors: Linares Fleites Gladys
Published: February 2024

Este artículo tiene como objetivo mostrar, con una visión general, cómo se fueron formando las disciplinas en los diferentes momentos históricos de la humanidad y cómo en esos hitos se fueron conformando las temáticas disciplinarias. Se expone cómo esas temáticas desarrollaron sus contenidos, cómo evolucionaron las estructuras científicas y cómo surgieron sus clasificaciones, ya como ciencias o cómo disciplinas, y también cómo, ante la complejidad de los estudios científicos, surgieron nuevas asociaciones disciplinarias en sus concepciones multidisciplinaria, pluridisciplinaria, interdisciplinaria y transdisciplinaria, para dar una interpretación holística e integral a la nueva concepción del conocimiento científico.
No hay mal que dure 100 años, ni una era que lo resista: sobre la eliminación del término esquizofrenia
Authors: Audiffred Jaramillo Ricardo Ignacio
Published: February 2024

La esquizofrenia es definida como un trastorno mental grave y discapacitante. Su etiología es desconocida y en años recientes ha recibido diversas denominaciones que la reclasifican como una enfermedad neuropsiquiátrica, del neurodesarrollo, o como una disfunción que circunscribe diferentes tipos de desórdenes. El objetivo principal del presente trabajo fue realizar una revisión bibliográfica sobre la esquizofrenia, el estigma asociado a esta enfermedad y las alternativas para erradicar el uso clínico de este término. Se utilizó un diseño de investigación bibliográfico amplio para recolectar las diversas posturas científicas sobre la utilización del término esquizofrenia. De lo anterior se puede concluir que la esquizofrenia ha inducido una serie de prejuicios sobre las personas que padecen esta enfermedad. Se debe considerar la abolición de un término que describe etimológicamente una imprecisión y que está llena de prejuicios, concepto que no ha cambiado en más de 110 años.
Tristeza microbiana: implicación de la microbiota intestinal en el desarrollo del Trastorno Depresivo Mayor
Authors: Coss Orozco Aleida M. , Pérez González Alejandra P. , Torres Pineda Lizeth
Published: February 2024

El Trastorno Depresivo Mayor (TDM) es un desorden mental con alta prevalencia en la población mundial, que se caracteriza por sentimientos de tristeza profunda y otros síntomas inhabilitantes, que pueden derivar incluso en la muerte. Debido al complejo origen de esta enfermedad, la investigación desarrollada en el tema ha sido abordada a partir de varios enfoques. En los últimos años el eje intestino-cerebro ha ganado especial relevancia en el tema ya que la evidencia recopilada hasta el momento indica que una alteración en la composición del microbioma intestinal puede conllevar al desarrollo de esta enfermedad neuropsiquiátrica. El presente trabajo pretende dar una visión general sobre lo que se conoce actualmente en relación al eje intestino-cerebro y el rol que desempeña el microbioma intestinal en el desarrollo del TDM y el tratamiento de esta.
Analizando distintos tipos de mascarillas usadas en la protección contra el virus Sars-Cov-2: una perspectiva ambiental y biotecnológica
Authors: Romero Balboa Osorio Adriana , Lagunes Carvajal Edvin
Published: February 2024

El virus SARS-CoV-2 ha obligado a la población mundial a hacer uso de distintas prácticas de prevención para así evitar el contagio de la enfermedad COVID-19, una de estas prácticas es el uso de mascarilla facial, sin embargo esto se ha traducido en un daño ambiental muy grande debido a que las personas no sabe con exactitud qué mascarilla usar ni cual es tiempo idóneo de utilización. Debido a ello, en el presente artículo se abordarán los distintos tipos de mascarillas, así como los distintos protocolos que el sector sanitario ha desarrollado para el uso correcto de mascarillas y el manejo correcto de los desechos. De igual forma se pondrán en evidencia las distintas alternativas que el sector biotecnológico ha propuesto para disminuir el daño ambiental y salvaguardar la salud pública.
plantas endémicas comestibles de temporada de Santa Ana Teloxtoc
Authors: Lozano Estrada Alondra , Roa Gómez Ulises , Rivera Carrasco Jesús
Published: February 2024

En este trabajo se documentan los usos, características y relevancia de las plantas endémicas comestibles de temporada de Santa Ana Teloxtoc, localidad perteneciente al Municipio de Tehuacán del Estado de Puebla y ubicada dentro de la Reserva de la Biosfera Tehuacán-Cuicatlán (RBTC)
Se presenta información de 40 especies endémicas útiles procedentes de las áreas naturales la zona, así como su disponibilidad temporal, formas de recolección, aprovechamiento integral de la especie y los principales usos reconocidos por la población de la zona: alimenticio y medicinal. Así también se presenta un análisis valorativo de las especies en los aspectos cultural y sostenible de la localidad.
Resistencia a antibióticos betalactámicos: situación actual y nuevas estrategias.
Authors: Estrada Calles Diana Michelle , Rodríguez Gamboa María Fernanda , Velázquez Álvarez Eilynn Alejandra
Published: February 2024

La resistencia bacteriana a los antibióticos betalactámicos, representa hoy en día y para el futuro cercano una problemática a nivel mundial, por la aparición de cada vez más mecanismos implicados a dicha resistencia en microorganismos de interés clínico como lo son Escherichia coli, Pseudomonas aeruginosa y muchos más. Algunos de estos mecanismos se encuentran ampliamente entendidos, sin embargo, otros requieren aún del estudio de sus funciones, pero sobre todo del desarrollo de métodos para evadirlos. El objetivo del presente artículo es revisar los mecanismos de resistencia de las bacterias ante los antibióticos betalactámicos y el registro existente sobre sus implicaciones alrededor del mundo, así como las perspectivas que se tienen a futuro. Además de la problemática de la resistencia, en los recientes años se atraviesan por nuevos retos como la transmisión de enterobacterias entre dueños y mascotas o las infecciones intrahospitalarias crecientes de bacterias resistentes a los betalactámicos, siendo estos los antibióticos de primera línea para recetar en cuidados intensivos. Actualmente, se están llevando a cabo estrategias clave para contrarrestar la situación, tales como un mejor manejo de la terapia antimicrobiana, el desarrollo de nuevos tratamientos a partir de diferentes enfoques como las combinaciones de betalactámicos con inhibidores de betalactamasas o innovadores usos de la biología sintética, acompañados por la mejora de los perfiles genéticos para la detección adecuada de los genes de resistencia implicados.
El concepto del desarrollo sustentable
Authors: Ayala esquivel Brandon Daniel , Cabrera Tapia Carlos Federico
Published: February 2024

Es muy relevante que la sociedad avance hacia un futuro en donde el respeto al medio ambiente forme parte del paradigma del funcionamiento de los procesos sociales e industriales; pues tomar conciencia ambiental es la única forma en la que se puede asegurar que los recursos naturales no se vean en peligro de escasez y así comprometer el funcionamiento adecuado de los ecosistemas, lo que afecta seriamente al desarrollo de la vida en el planeta.
MATERIALES DIDÁCTICOS PARA ENSEÑAR MATEMÁTICAS A ESTUDIANTES CON DISCAPACIDAD VISUAL
Authors: Perucini Marijose , Juárez-Ruiz Estela , Flores-Medrano Eric
Published: February 2024

En México la formación del docente es de gran importancia para atender diversas dificultades que se pueden presentar en el aula de clases, como lo son la diversidad e inclusión educativa. Desafortunadamente, dicha formación es insuficiente para atender estos problemas por diversas razones, particularmente a la hora de enseñar matemáticas a estudiantes con discapacidad visual. Es habitual que los profesores desconozcan los diferentes materiales didácticos que están a su alcance para ayudarles en la inclusión en el aula de matemáticas. Por ello, en este trabajo, se presentan tres recursos manipulativos que el profesor puede emplear para enseñar matemáticas a alumnos con esta discapacidad.