bluuebunny/crossref_metadata_2025 huggingface dataset:
Design and Implementation of Artificial Intelligence-based Real-time Pothole Detection for IoT Smart Infrastructure
Authors: Sudibyo Rahardhita Widyatra , Alimudin Akhmad
Published: August 2024

The Internet of Things (IoT) has been extensively deployed for Smart Cities due to its ability to process many different and heterogeneous end systems. The IoT innovation encourages artificial intelligence applications to process data. In Smart City infrastructure, the road is a critical component of transportation infrastructure that supports the economic, social, and cultural things of community life and various aspects of community life. Road conditions affect a variety of community activities. Good roads enhance comfort and support local businesses. However, many roads remain in bad condition, such as potholes. Various methods have been attempted to identify potholes, especially the two-dimensional imaging method. This paper proposes the real-time Artificial Intelligence detection of potholes using the Convolutional Neural Network (CNN), which leverages the Edge Tensor Processing Unit (TPU) with the MobileNet SSD v2. The system was set up on a Jetson Nano with a few extras, including a camera and GPS, to support the IoT infrastructure. Evaluation for the model consists of device implementation, model evaluation, GPS position deviation, and on-road implementation. The effectiveness is confirmed through experiments using a system test-bed that generates ideal mAP off 0.22 and recall values.
Sentiment Analysis on TikTok Shop Reviews Using Long Short-Term Memory Method to Find Business Opportunity
Authors: Tri Yunanda Cahyarini Maulida , Hanafi Muhammad , Pradnya Dhuhita Windha Mega
Published: August 2024

During the world-changing year of covid 19, social media commerce grew fast. The prolonged use of social media encourages users to make online purchases via social media. TikTok, the most downloaded social media app, offers its users a social media commerce experience, TikTok Shop. The TikTok shop provided a new option for business expansion. Business owners may optimize the potential use of TikTok shops by learning more about TikTok Shop. The purpose of this study is to use sentiment analysis to evaluate the business potential of TikTok Shop. The data from Google Play reviews is analysed using the LSTM algorithm. Based on the results of research conducted using a confusion matrix, the LSTM algorithm method using word2vec has an accuracy of 74%. This study found that the business prospects of TikTok shops may be challenging.
Sentiment Analysis on the Impact of MBKM on Student Organizations Using Supervised Learning with Smote to Handle Data Imbalance
Authors: Cahyaningrum Lailatul , Luthfiarta Ardytha , Rahayu Mufida
Published: August 2024

Recently, there has been a decline in student interest in joining organizations. One of the causes is the MBKM program "Merdeka Belajar Kampus Merdeka". With this program from the government, more and more students are interested in entering because it is considered more profitable. Responses regarding this were conveyed by students through questionnaires, Twitter crawling, and YouTube comments. The data obtained was 1,770 (negative, positive, and neutral labeling) using Sastrawi, Nazief & Adriani, and Arifin Setiono stemming. There is an imbalance of data in labeling, so it is necessary to do SMOTE to balance the data. The algorithms used in the research focus on modeling the Naïve Bayes Classifier, Support Vector Machine, and Decision Tree with the split random method, with the best results using Support Vector Machine. Of the three algorithms, the highest results were obtained from the results of Arifin Setiono's data setmming, using a Support Vector Machine with 91% accuracy, obtained from 90% training data and 10% testing.
Implementation Of Fuzzy Logic to Identify Accident Categories In SMS-Based Two-Wheeled Vehicles
Authors: Fahruzi Akhmad , Muharror Aunurrohman
Published: August 2024

Two-wheeled vehicle is the most popular means of transportation in Indonesia. As a result, it would cause several issues. One of them is an increased possibility of an accident to happen. In the event of an accident, quick aid from the public to the victim can reduce the risk of severe injury suffered by him. The person who provides aid to the injured victim may ask for money from the victim's family whose amount is not proportionate with the severity of the accident. In light of this, a system has been devised to identify and categorize the different types of accidents and send the formation to a family phone number registered electronically. The accident level is categorized using the Sugeno-type fuzzy logic method. The parameters used to differentiate the accident categories are speed, slope, and duration of vehicle braking time. The information is then sent to the registered phone via SMS that contains the accident category and the coordinates of the accident location provided by the GPS Neo 6 module. The algorithm is based on the vehicle's tilt angles, which range from 45(to the right) and -45(to the left). The fuzzy logic then determines the category, which processes and produces the accident category based on the speed and vehicle braking duration parameters. The proposed algorithm in this research will be experimented with using a real motorbike. Based on the experimental results, it has been found that the performance of the fuzzy logic method has an accuracy of 88.89% when determining the category of accident (light or heavy) and the time taken to send the information to the family member via SMS is quite fast.
Classification of Depression Expressions on Twitter Using Ensemble Learning with Word2Vec
Authors: Adi Nugraha Muhammad Reza , Sibaroni Yuliant
Published: August 2024

One of the mental health disorders experienced by people is depression. Depression is a mental disorder characterized by feelings of sadness, loss of interest or pleasure in daily activities, and decreased cognitive function that can affect social life, work, and general physical health. Early detection is needed to prevent the occurrence of bad risks. One of the early detections can be done through social media. This is because social media is one of the tools used to channel expression. This research uses data taken from Twitter social media to create a machine learning model. Before model building, data pre-processing will be carried out using Word2Vec to convert text into a continuous vector representation. The algorithm used is ensemble learning by combining five algorithms: Logistic Regression, Decision Tree, K-Nearest Neighbor, Artificial Neural Network, and Support Vector Machine. The results show that different Word2Vec architectures can give the model another performance. Ensemble Learning can improve the performance of using a single model. The best results were obtained by using a data ratio of 90:10 using the Skip-gram architecture to get an accuracy value and f1-score of 94%.
Analytical Comparison of Lung Cancer Classification Using K-Nearest Neighbor and Naïve Bayes Algorithms
Authors: Darmayanti Yunisa , Marisa Fitri , Yuniar Rahman Aviv
Published: August 2024

Lung cancer stands as a significant global contributor to human mortality, constituting 25% of all cancer-related deaths in 2021. Its elusive nature, often devoid of early symptoms in a quarter of diagnosed cases, poses a challenge for timely detection. Unlike some other cancers, lung cancer remains hidden from the naked eye, with its symptoms often masquerading as those of other ailments like bronchitis, asthma, or persistent coughs. Early diagnosis is pivotal for effective treatment and increased survival rates. In light of the pressing nature of the situation, this study investigates the prediction of lung cancer by using data mining tools. It is essential to conduct data mining, which is a process that involves searching for patterns and trends inside vast data repositories to discover valuable insights. Within this context, classification emerges as a fundamental aspect that discerns objects based on their distinctive characteristics. A comparative study is undertaken to address the complexities associated with lung cancer classification, focusing on the K-Nearest Neighbor (KNN) and Naïve Bayes Classifier (NBC) algorithms. Through the utilization of a dataset that contains one thousand instances and twenty-four criteria, the purpose of this study is to determine which algorithm is preferable in the categorization of lung cancer. Upon analysis, the study yields noteworthy results. The KNN algorithm exhibits an accuracy rate of 98.34%, surpassing the NBC algorithm's accuracy of 89.37%. Consequently, this research concludes that, in lung cancer classification, the KNN algorithm outperforms the Naïve Bayes algorithm. These findings promise to enhance the efficacy of early lung cancer detection, potentially saving numerous lives through improved classification methods.
Effect of Using GLCM and LBP+HOG Feature Extraction on SVM Method in Classification of Human Skin Disease Type
Authors: Eka Khoirunisa Friska , Charibaldi Novrido
Published: August 2024

Skin diseases have been ranked third out of ten diseases suffered by outpatients in many hospitals in Indonesia. The public often underestimates these diseases because they are considered not to cause death. In general, dermatologists diagnose skin diseases using the biopsy process, but the biopsy process is quite expensive and can cause injury to the skin. Each skin disease has different texture and shape characteristics, so classification can be used to distinguish the type of skin disease. This study compares LBP+HOG and GLCM feature extraction with the SVM classification method to determine the best feature extraction in skin disease classification. This research compares GLCM and LBP+HOG feature extraction using the SVM method. GLCM is used to measure the relationship between pixel intensities in the image, while LBP+HOG combines information about the texture and shape of the image. The test results show that the GLCM feature extraction method with SVM classification achieves an accuracy of 74%. In this test, the parameters C=100 and the features used are homogeneity, contrast, energy, correlation, ASM, and dissimilarity. Meanwhile, extraction with LBP+HOG resulted in an accuracy of 68%.
Implementation of Artificial Neural Network in Predicting CPO Prices Using Backpropagation
Authors: Rofi Halmi Muhmmad , Amanda Putri Raissa
Published: August 2024

This research examines the development of a forecasting model for Crude Palm Oil (CPO) prices using artificial neural network algorithms, particularly the backpropagation algorithm. CPO, as Indonesia's main export commodity, has significant economic impacts and affects the income of oil palm farmers. Data on CPO prices taken from CIF Rotterdam from January 2019 to December 2023 were used in this study. The research method involved several stages, including data collection, pre-processing, model design, and model implementation using Python programming. The results of training the model using the backpropagation algorithm showed an error value of 0.537829578 after 1000 epochs, while evaluation using Mean Squared Error (MSE) showed an MSE value of 0.022709 during the training process and 0.017604 during the testing process. The model also produced predictions for CPO prices in the next three months: 932.578 for the first month, 949.568 for the second month, and 774.855 for the third month. These findings indicate that the developed model can predict future CPO prices with adequate accuracy, which can assist companies in making better financial decisions and managing risks associated with CPO price fluctuations.
Sequelas Pós-COVID em profissionais de enfermagem
Authors: Silva Pâmela Maria Vieira da , Silvério Viviane Aparecida , Guerra Carlos Henrique Wernersbach , Gomes Vaneusa Maria , Silveira Isabela Benevenuto Freitas da , Ferreira Vitória Cristina Tavares de Sales , Arcanjo Bruna Luiza Ferreira , Silveira Rafaela Benevenuto Freitas da , Soares Ana Cristina Rodrigues
Published: August 2024

Objetivo: Avaliar o impacto da pós-Covid, nos profissionais de enfermagem que atuaram na linha de frente ao combate ao SARS-CoV-2, em uma cidade do estado de Minas Gerais. Métodos: Trata-se de um estudo observacional, transversal, de caráter descritivo e analítico. Os dados foram coletados com profissionais que atuaram na linha de frente do combate à Covid-19 na cidade, através de formulário eletrônico no Google Forms. Resultados: Os relatos revelam um quadro de fadiga física e mental, medo constante, tristeza e angústia provenientes do cenário pandêmico. A vivência de perdas, tanto no âmbito profissional quanto pessoal, deixou marcas profundas, desencadeando estresse pós-traumático, ansiedade e síndrome do pânico em alguns casos. Conclusão: No aspecto físico, destacam-se sequelas como anosmia e ageusia, sintomas característicos que podem persistir após a resolução da infecção aguda. Além disso, relatou-se também a diminuição da concentração e da capacidade cognitiva, indicando um comprometimento neurológico pós-infecção.
Individualized Care Through Treatment Pathways: Isn’t This an Oxymoron?
Authors: Page Ray
Published: August 2024

Developing individualized care from precision medicine through treatment pathways is not an oxymoronic concept. We can achieve congruent solutions if the objectives of precision medicine and treatment pathways are aligned. Therefore, the successful amalgamation of these two methods to direct optimal treatment choices for patients will require a quid pro quo relationship.
SOME PROBLEMS OF THE INSTITUTE OF WITNESS IMMUNITY IN CIVIL PROCEEDINGS
Authors: Ланина В.С.
Published: August 2024

В статье рассматриваются вопросы функционирования свидетель- ского иммунитета в гражданском процессе. Актуальность темы исследования опре- делена тем, что в настоящее время наблюдается недостаточная разработанность осо- бенностей свидетельского иммунитета как в нормах Гражданского процес суального кодекса Российской Федерации, так и в имеющихся теоретических работах уче- ных-правоведов. В статье решаются следующие исследовательские задачи: опреде- лить понятие свидетельского иммунитета; исследовать классификации свидетельского иммунитета в гражданском судопроизводстве и предложить авторскую вариацию свидетельского иммунитета; рассмотреть субъектный состав лиц, наделенных правом отказа от дачи свидетельских показаний. Автором обозначено, что существующий круг лиц, обладающих правом свидетельского иммунитета, требует корректировки. В статье сделан акцент на отсутствии категории «пределы свидетельского иммуни- тета», которая служит неким измерением действия свидетельского иммунитета в каж- дом конкретном случае. Предлагаются рекомендации по защите прав и интересов свидетелей при реализации института свидетельского иммунитета в гражданском судопроизводстве.
STUDY OF THE CURRENT PIPE MARKET IN THE RUSSIAN FEDERATION AND PROSPECTS FOR ITS DEVELOPMENT
Authors: Крылов А.Н. , Мозговой А.И.
Published: August 2024

В статье представлен анализ современного рынка трубопроката, его особенности и структура, исследованы проблемы рынка, перспективы текущего и среднесрочного периодов. Объектом исследования выступает производственно-хо- зяйственная деятельность холдинговой компании «Королевский трубный завод», работающей на рынке трубопроката в сегменте электросварных, водогазопровод- ных, профильных труб строительного назначения. Целью данного исследования является анализ трубного рынка и его перспектив для анализируемой компании, а также формирование направлений совершенствования ее деятельности в усло- виях нестабильной конъюнктуры трубного рынка Российской Федерации. В работе иссле дованы особенности рынка трубопроката, путем экспертного опроса выявлены его проблемы и угрозы, определены кратко- и среднесрочные перспективы, а также сформулированы направления совершенствования деятельности исследуемой компании.
CONCEPT FOR THE DEVELOPMENT OF TECHNOLOGICAL INNOVATIONS OF HIGH-TECH INDUSTRIAL ENTERPRISES
Authors: Гулиев Э.А.
Published: August 2024

В последнее время предприятия и организации, использующие высокие технологии, выступают гарантом устойчивого развития национальных эко- номик. Это обусловлено увеличением доли рынка высокотехнологичной продукции. Предприятия, производящие высокотехнологичную инновационную продукцию спо- собствуют значительным изменениям в структуре экономики. Высокотехнологичные предприятия достигают существенных успехов, внедряя инновационные технологии в производство и управление. Это важный фактор, влияющий на экономический рост. В данной статье выполнен анализ современного состояния предприятий, функцио- нирующих с использованием технологических инноваций, проблемы, перспективы и пути повышения конкурентоспособности.
Forecasting Day-Ahead Electricity Prices using Technical Prediction Methods
Authors: Rozhkov V.A. , Batuchtin A.G.
Published: August 2024

This paper examines specific features of electricity as a commodity and analyzes the subsequent difficulties arising when accurately forecasting the clearing wholesale electricity price. Statistical methods (different kinds of linear regression), machine learning algorithms (random forest, support vector machines, etc.) and deep learning models (perceptrons, recurrent neural networks) are applied for forecasting the supplier’s clearing electricity price for the 2nd price zone of the Russian wholesale electricity and capacity market. The forecasting results are evaluated using statistical error metrics such as R2, MSE, MAE, and others. The complexities arising from the volatile and nonlinear nature of electricity prices, as well as the challenges in comparing prediction models due to diverse datasets and evaluation metrics are addressed. The need to establish an open platform for exchanging forecasting methods and datasets, including electricity price and auxiliary features, is substantiated. The open platform will also facilitate cooperation among researchers worldwide to evaluate and enhance the accuracy and competitiveness of short-term electricity price forecasting methods.
Methodical approaches to determination of insecticidal substances (imidacloprid, and tetramethrin in the presence of piperonyl butoxide) in an aerosol medium
Authors: Носикова Л.А. , Кочетов А.Н. , Матвеев А.А.
Published: August 2024

Рассмотрено определение имидаклоприда методом обращенно-фазовой высокоэффективной жидкостной хроматографии (ОФ ВЭЖХ) в изократическом режиме и тетраметрина методом газожидкостной хроматографии (ГЖХ). Совместному определению методом ВЭЖХ представителей неоникотиноидов (имидаклоприд) и пиретроидов (тетраметрин) мешает добавка синергиста пиперонилбутоксида. Попытка разделения пиперонилбутоксида (ППБ) и тетраметрина с использованием различных типов неподвижных фаз методом ОФ ВЭЖХ при градиентном элюировании с использованием в качестве подвижной фазы систем на основе ацетонитрила и воды не увенчалась успехом. Разделение этих компонентов было осуществлено методом ГЖХ с использованием капиллярной колонки и пламенно-ионизационного детектирования, при этом предел определения составляет 0,005 мг/мл для ППБ и 0,05 мг/мл для тетраметрина. Порог определения имидаклоприда методом ВЭЖХ составляет 0,001 мг/мл (λ = 280 нм). Стоит отметить, что для проведения корректного определения содержания действующих веществ в аэрозольных средствах при отсутствии необходимого штатного переходника-адаптера понадобится провести большее число (минимум 3–5) пробоотборов из разных баллонов с целью исключения грубых промахов. Суммарная погрешность определения субстанций и синергиста в аэрозольном средстве составила 12%.

Describes the definition of imidacloprid by the method RP HPLC in isocratic mode and tetrametrin by GC. Joint determination by HPLC of representatives of neonicotinoids (imidacloprid) and pyrethroids (tetramethrin) prevents additive synergist piperonyl butoxide. Attempted separation of piperonyl butoxide (PPB) and tetramethrin using different types of stationary phases by the method RP HPLC with gradient elution using as mobile phase systems based on acetonitrile and water were not successful. Separation and detection of these components was carried out by GC using a capillary trivial column and flameionization detection the limit of detection is 0.005 mg/ml to PPB and 0.05 mg/ml for tetramethrin. The threshold determination of imidacloprid by HPLC method is 0.001 mg/ml (λ = 280 nm). Was used the simplest options of evacuation means of aerosol packaging, as well as hydrocarbon propellant from the sample. Revealed a large spread of analytical results depending on the degree of filling of the container during the evacuation in a glassreceiver and a relatively smaller variation in mechanical leakage of the aerosol containers. It should be noted that for the correct determination of the content of active substances in aerosol means in the absence of the required standard adapter adapter, you will need to spend more (at least 3-5) of sampling from different cylinders to avoid gross blunders and improvements of the statistical characteristics. The total error of the determination of an analyte in the aerosol medium was 12%.
The role of emotional intelligence in interpersonal conflicts management in professional environment
Authors: Givargizova N. A.
Published: August 2024

The article studies complex interplay of emotional intelligence (hereafter – EI) and its key role in managing interpersonal conflict in professional settings. The study elucidates how EI subtle components such as self-awareness, empathy, self-regulation, and social skills play an important role in deciphering and overcoming the emotional complexities inherent in professional conflicts. Through methodical research, the quintessential role of EI in creating a harmonious workplace has been revealed, where conflicts are not only effectively resolved but also transformed into opportunities for growth. At the same time, the critical role of empathy in understanding and appreciating emotional states of others has been emphasized, thus fostering more inclusive and empathic communication. The practice segment of the study offers a number of strategies and training programs aimed at developing EI in professionals. These techniques, ranging from mindfulness meditation to empathy mapping workshops and emotional intelligence training, offer actionable ways to increase emotional competence in a variety of professional situations. The article concludes by discussing practical applicability of these ideas in a variety of professional settings, suggesting directions for future research, including the study of EI in different cultural contexts and technology integration into EI trai ning. This comprehensive study not only contributes to the academic discourse on EI, but also serves as a beacon for organizations and individuals seeking to navigate the emotional landscape of today’s professional environments.
Biocatalytic Generation of Trifluoromethyl Radicals by Nonheme Iron Enzymes for Enantioselective Alkene Difunctionalization
Authors: Zhang James , Huls Anthony , Paris Jared , Guo Yisong , Huang Xiongyi
Published: August 2024

The trifluoromethyl (–CF3) group represents a highly prevalent functionality in pharmaceuticals. Over the past few decades, significant advances have been made in the development of synthetic methods for trifluoromethylation. In contrast, there are currently no metalloenzymes known to catalyze the formation of C(sp3)‒CF3 bonds. In this work, we demonstrate that a nonheme iron enzyme, hydroxymandelate synthase from Amycolatopsis orientalis (AoHMS), is capable of generating CF3 radicals from hypervalent iodine(III) reagents and directing them for enantioselective alkene trifluoromethyl azidation. A high-throughput screening (HTS) platform based on Staudinger ligation was established, enabling the rapid evaluation of AoHMS variants for this abiological transformation. The final opti-mized variant accepts a range of alkene substrates, producing the trifluoromethyl azidation products in up to 73% yield and 96:4 enanti-omeric ratio (e.r.). The biocatalytic platform can be further extended to alkene pentafluoroethyl azidation and diazidation by altering the iodine(III) reagent. In addition, anion competition experiments provide insights into the radical rebound process for this abiological transformation. This study not only expands the catalytic repertoire of metalloenzymes for radical transformations but also creates a new enzymatic space for organofluorine synthesis.
Lattice Models in Molecular Thermodynamics: Merging the Configurational and Translational Entropies
Authors: Åstrand Per-Olof , de Miguel Rodrigo
Published: August 2024

Lattice models are a central idea in statistical thermodynamics, as they allow for the introduction of a configurational entropy by counting the multiplicity of placing indistinguishable particles on a lattice. In this work we use a lattice model to show that the configurational entropy needs to be merged with the molecular translational entropy in order to have a consistent model. This is achieved by replacing the volume of a lattice site with a quantum volume (i.e., the cube of the thermal wavelength). This modified lattice model allows us to derive a new equation of state, referred to as the Bragg-Williams equation state, from which we may also derive a generalized version of the van der Waals equation of state. In contrast to the standard van der Waals equation of state, the heat capacity of the new models has temperature dependence.
Recent progress in modeling and simulation of biomolecular crowding and condensation inside cells
Authors: Mathur Apoorva , Ghosh Rikhia , Nunes-Alves Ariane
Published: August 2024

Macromolecular crowding in the cellular cytoplasm can potentially impact diffusion rates of proteins, their intrinsic structural stability, binding of proteins to their corresponding partners as well as biomolecular organization and phase separation. While such intracellular crowding can have a large impact on biomolecular structure and function, the molecular mechanisms and driving forces that determine the effect of crowding on dynamics and conformations of macromolecules are so far not well understood. At a molecular level, computational methods can provide a unique lens to investigate the effect of macromolecular crowding on biomolecular behavior, providing us with a resolution that is challenging to reach with experimental techniques alone. In this review, we focus on the various physics-based and data-driven computational methods developed in the last few years to investigate macromolecular crowding and intracellular protein condensation. We review recent progress in modeling and simulation of biomolecular systems of varying sizes, ranging from single protein molecules to the entire cellular cytoplasm. We further discuss the effects of macromolecular crowding on different phenomena, such as diffusion, protein-ligand binding, and their mechanical and viscoelastic properties, such as surface tension of condensates. Finally, we discuss some of the outstanding challenges that we anticipate the community addressing in the next few years in order to investigate biological phenomena in model cellular environments by reproducing in-vivo conditions as accurately as possible.
A Heavy Solution for Molecular Thermal Management: Phonon Transport Suppression with Heavy Atoms
Authors: Bro-Jørgensen William , Bay-Smidt Andreas Juul , Donadio Davide , Solomon Gemma C.
Published: August 2024

Thermal management in molecular systems presents challenges that require a deeper understanding of phonon transport, an essential aspect of heat conduction in single molecule junctions. Our work introduces the use of heavy atoms as a strategy for suppressing phonon transport in organic molecules. Starting with a 1D force-constant model and density functional theory calculations of model chemical systems, we illustrate how increasing the mass of a central atom affects the phonon transmission and conductance. Following this, we turn our attention to the chemically accessible systems of metallapolyynes and extended metal atom chains (EMACs). Our findings suggest that several of the studied EMACs exhibit thermal conductance either near or below a recently proposed threshold of 10 pW/K – a crucial step towards reaching high thermoelec- tric figure of merits. Specifically, we predict that the molecule MoMoNi(npo)4 (NCS)2 has a thermal conductance of just 8.3 pW/K at 300 K. Our results demonstrate that conceptually simple chemical modifications can markedly reduce the thermal conductance of single molecules; these results both deepens our understanding of the mechanisms driving single-molecule phonon thermal conductance and suggest a path towards using single molecules as thermoelectric materials.
Estimating methane emission durations using continuous monitoring systems
Authors: Daniels William , Jia Meng , Hammerling Dorit
Published: August 2024

We propose a method for estimating the duration of methane emissions on oil and gas sites, referred to as the Probabilistic Duration Model (PDM), that uses concentration data from continuous monitoring systems (CMS). The PDM probabilistically addresses a key limitation of CMS: non-detect times, or the times when wind blows emitted methane away from the CMS sensors (resulting in no detections). Output from the PDM can be used to bound the duration of emissions detected by snapshot measurement technologies, such as plane or satellites, that have limited ability to characterize emission duration due to the typically low temporal frequency (e.g. quarterly) at which they observe a given source. Linear regression indicates that the PDM has a bias of -4.9% (R^2 = 0.80) when evaluated on blinded controlled releases at the Methane Emissions Technology Evaluation Center (METEC), with 86.8% of estimates within a factor of 2x error from the true duration. We apply the PDM to a typical production site in the Appalachian Basin and use it to bound the duration of snapshot measurements. We find that failing to account for CMS non-detect times results in underestimated emission durations of up to a factor of 65x (6,400%) on this site.
Ion-mediated crosslinking of hyaluronic acid into hydrogels without chemical modification
Authors: Prakash Gayatri , Clasky Aaron , Gadani Kunal , Nazeri Mohammad , Gu Frank
Published: August 2024

Hyaluronic acid (HA) is a biomedically relevant polymer widely explored as a component of hydrogels. The prevailing approaches for crosslinking HA into hydrogels require chemically modifying the polymer, which can increase processing steps and complicate biocompatibility. Herein, we demonstrate an alternative approach to crosslink HA that eliminates the need for chemical modifications by leveraging the interactions between metal cations and the negatively charged, ionizable functional groups on HA. We demonstrate that HA can be crosslinked with the bivalent metal cations Mn(II), Fe(II), Co(II), Ni(II), Cu(II), Zn(II), Pd(II), and notably Mg(II). Using Mg(II) as a model, we show that ion-HA hydrogel rheological properties can be tuned by altering the HA molecular weight and concentrations of ion, NaOH and HA. Mg(II)-HA hydrogels showed the potential for self-healing and stimulus response. Our findings lay the groundwork for developing a new class of HA-based hydrogels for use in biomedical applications and beyond.
Penerapan Bauran Pemasaran 4P pada Astiga Leather Tahun 2024
Authors: Khairat Nadiatul , Widaningsih Sri
Published: August 2024

Banyak sekali berbagai kebijakan yang diterapkan oleh perusahaan dalam meningkatkan penjualannya dan menarik minat konsumen untuk membeli suatu produk yang ditawarkan oleh produsen, berbagai strategi dilakukan oleh perusahaan agar dapat bertahan di tengah persaingan yang tajam. Salah satunya strategi bauran pemasaran. Astiga Leather merupakan salah satu perusahaan yang menggunakan strategi bauran pemasaran 4P untuk mendukung peningkatan penjualan produk yang dibeli konsumen. Tujuan dari penelitian ini adalah untuk mengetahui penerapan bauran pemasaran 4P (Product, Price, Place, Promotion) pada Astiga Leather dan untuk mengetahui hasil evaluasi penerapan bauran pemasaran 4P Astiga Leather. Penelitian ini merupakan penelitian yang menggunakan metode deskriptif-kualitatif yang didukung dengan data berupa hasil observasi dan wawancara dengan narasumber yang bersangkutan. Jumlah narasumber terdiri dari 2 orang, pemilik usaha/chief executive offcer (CEO) dan chief operating officer (COO) Astiga Leather. Hasil penelitian menunjukkan bahwa secara keseluruhan, Astiga Leather sudah menerapkan strategi bauran pemasaran 4P (Product, Price, Place/Distribution Channels, Promotion) dengan baik.

There are so many strategies used by companies to increase their sales and attract consumers to buy a product offered by producers, various strategies are carried out by companies in order to survive in the midst of sharp competition. One of them is the marketing mix strategy. Astiga Leather is one of the companies that uses the 4P marketing mix strategy to support the increase in sales of products purchased by consumers. The purpose of this study is to determine the application of the 4P marketing mix (Product, Price, Place/Distribution Channels, Promotion) at Astiga Leather and to determine the results of evaluating the application of Astiga Leather's 4P marketing mix. This research uses descriptive-qualitative methods supported by data in the form of observation results and interviews with relevant sources. The number of sources consists of 2 people, namely the business owner/chief executive officer (CEO) and chief operating officer (COO) of Astiga Leather. The results showed that in general Astiga Leather has implemented the 4P marketing mix strategy (Product, Price, Place/Distribution Channels, Promotion) properly.
Kajian Mengenai Strategi Peningkatan Penjualan (Studi Kasus Perusahaan Ekspedisi Muatan Kapal Laut PT. Teduh Makmur Semarang)
Authors: Sudjanto . , Widjajanti Kesi
Published: August 2024

Analisis pertama dilakukan dalam rangka menghadapi persaingan dengan
mengembangkan kemampuan bersaing  PT. Teduh Makmur melalui perluasan izin usaha.

Meningkatkan status perusahaan dari EMKL menjadi perusahaan yang bergerak
di bidang jasa freight forwarder dan perluasan  lingkup  wilayah  kerja  sehingga
PT. Teduh Makmur mampu memberikan pelayanan one stop shipping kepada pelanggan. Terdapat beberapa faktor yang mempengaruhi terwujudnya perubahan PT. Teduh Makmur dari perusahaan EMKL menjadi freight forwarder
ANALISIS PENGARUH INDEKS HARGA SAHAM ASING DAN VARIABEL MAKROEKONOMI INDONESIA TERHADAP INDEKS HARGA SAHAM GABUNGAN (IHSG) DI BURSA EFEK INDONESIA (PERIODE JANUARI 2013 AGUSTUS 2015)
Authors: Triyono David , Indarto Indarto , Santoso Aprih
Published: August 2024

Kondisi perekonomian dunia saat ini tengah mengalami gejolak di bidang ekonomi. Pada pertengahan tahun 2015 beberapa negara mengalami krisis dan gejolak di bidang ekonomi diantaranya Yunani, China, Malaysia serta beberapa negara lainnya.Ekonomi dunia yang semakin terintegrasi akan berdampak kepada negara Indonesia tak terkecuali  ke industri pasar modal.

Tujuan dari penelitian ini yaitu untuk menganalisis pengaruh beberapa indeks saham asing dan indikator makro   ekonomi Indonesia terhadap kondisi Pasar Modal Indonesia (IHSG). Beberapa   indeks   saham   asing   yang   dipakai   dalam   penelitian   ini   yaitu indeks Dow Jones, indeks Shanghai (SSE), indeks Singapura (STI), nilai tukar USD/IDR, tingkat suku bunga dan Inflasi di Indonesia yang datanya diambil bulanan dari Januari 2013 sampai Agustus 2015.

Untuk mengetahui apakah beberapa indeks saham   asing dan   indikator   ekonomi   Indonesia mempunyai   pengaruh   positif   atau   negatif terhadap IHSG,   dalam penelitian ini menggunakan analisis regresi linier berganda.Hasil yang diperoleh dari penelitian ini menunjukkan bahwa variabel indeks Dow Jones,   indeks   Shanghai,   dan   indeks   STI   berpengaruh   positif   terhadap pergerakan   IHSG,   sedangkan   variabel   kurs USD/IDR, suku bunga dan inflasi berpengaruh negatif terhadap pergerakan IHSG.
ANALISA PENGARUH KOMPETENSI PROFESIONAL DAN BURNOUT KERJA TERHADAP PRESTASI KERJA DENGAN PERCEIVED ORGANIZATIONAL OF SUPPORT SEBAGAI VARIABEL MODERATING (Studi Kasus di PT. NI Semarang)
Authors: Hapsari Maria Hyacintha , Nurhayati Tatiek
Published: August 2024

Penelitian ini menganalisis pengaruh kompetensi profesional dan burnout kerja terhdapa prestasi kerja dengan perceived organizational of support sebagai variabel moderting. Penelitian ini bertujuan: (1) Untuk menganalisis pengaruh kompetensi profesional terhadap prestasi kerja; (2) Untuk menganalisis pengaruh burnout terhadap prestasi kerja; (3) Untuk Menganalisis pengaruh kompetensi terhadap prestasi kerja dengan dimoderasi oleh perceived organizational of support; (4) Untuk Menganalisis pengaruh burnout terhadap prestasi kerja dengan dimoderasi oleh perceived organizational of support.

Teknik sampling yang digunakan adalah random sampling menggunakan perhitungan rumus slovin sehingga memperoleh 180 responden. Metode penelitian yang digunakan menggunakan MRA (moderated regresiion analysis). Hasil dari penelitian yang telah dilakukan diketahui bahwa 4 hipotesis diterima, yakni  kompetensi profesional berpengaruh positif dan signifikan terhadap prestasi kerja karyawan. Burnout kerja memberikan pengaruh negatif dan signfikan terhadap prestasi kerja karyawan.   Perceived organizational of support memoderasi hubungan kompetensi profesional terhadap prestasi kerja dengan sifat menguatkan. Perceived organizational of support memoderasi hubungan burnout   kerja terhadap prestasi kerja dengan sifat memperlemah.
Democracy and te Tiriti
Authors: Salmond Anne
Published: August 2024

Ko te wai e hora rā, ko Raukawa-moana. Ko te marae e takoto rā, ko te Whare Pī. Ko koutou āku rangatira kua pae nei i te pō nei, tēnakoutou, tënä koutou, tēnā tātou katoa. My thanks to the School of Government for their very kind invitation. I guess I ought to feel at home here in the shadow of Parliament, because, as they say, in politics it’s dog eat dog, whereas in academia it’s precisely the reverse. It’s a good recipe for humility, in any case.In this lecture in honour of Sir Frank Holmes, with his exceptional contributions to both academia and politics, I’d like to offer some thoughts, well researched I hope. It’s not a matter of ‘laying down the law’, but of sharing ideas about matters of national importance.
Terapi Puzzel Dengan Kemampuan Kognitif Pada Lansia Dirumah Pelayanan Sosial Pucang Gading Semarang
Authors: Herison Ryschy , Nurhidayati Tri , Hartiti Tri
Published: August 2024

Kondisi perubahan lansia pada umumnya mengalami kemunduran terutama pada fungsi kognitif. Terapi yang mampu meningkatkan fungsi kognitif lansia diantaranya berupa terapi non farmakologis yaitu terapi Puzzle. Studi kasus ini bertujuan untuk melakukan penerapan terapi puzzel pada lanjut usia dengan kemajuan fungsi kognitif lansia di Rumah Pelayanan Pucang Gading Semarang. Studi kasus ini dilakukan dengan metode deskriptif dengan menerapkan beberapa jurnal tentang Terapi Puzzle Wapuwan adalah sebuah permainan yang berupa potongan-potongan gambar wayang punakawan yang diacak menjadi suatu gambar yang utuh dalam waktu 20 menit selama 9x pertemuan dalam 3 minggu dengan kriteria inklusi : lansia dengan gangguan kognitif sedang (17 – 23), lansia berusia 65 – 75 dan kriteria eklusinya : lansia yang mengalami amnesia, lansia dengan gangguan pendengaran, lansia dengan depresi berat. Dari hasil permainan puzzle didapatkan bahwa dari hari pertama ke hari sembilan mengalami peningkatan sebesar 26 %  dengan hasil skor dari 23 menjadi 30 untuk subjek pertama kemudian untuk subjek kedua mengalami peningkatan dalam pengkajian MMSE yang awalnya 20 menjadi 27 didapatkan peningkatan dari hari pertama ke hari Sembilan sebesar 23 %. Kedua subjek mengalami peningkatan dari gangguan kognitif sedang dengan skor (17 – 23) meningkat menjadi normal (24 – 30). Dari hasil kedua subjek setelah diberikan terapi puzzle adanya peningkatan kemampuan kognitif dilihat dari meningkatnya skor mini mental state exam.
Aplikasi Terapi Musik Lullaby untuk Stabilisasi Hemodinamika pada Bayi Berat Lahir Rendah
Authors: Abidah Laili , Alfiyanti Dera , Samiasih Amin
Published: August 2024

Bayi berat lahir rendah (BBLR) adalah bayi lahir dengan berat badan <2500 gram yang berisiko mengalami ketidakstabilan suhu(hipotermi), sindrom aspirasi, ketidakstabilan berat badan, hal ini disebabkan karena adanya ketidakstabilan status hemodinamika yang mempengaruhi sirkulasi keseluruh organ. Terapi nonfarmakologis yang mampu menstabilkan hemodinamik pada BBLR yaitu terapi musik lullaby. Studi kasus ini bertujuan untuk melakukan penerapan terapi musik lullaby pada BBLR untuk menstabilkan hemodinamik di Rumah sakit Roemani Muhammadiyah Semarang. Studi kasus ini dilakukan dengan metode deskriptif dengan menerapkan beberapa jurnal mengenai terapi musik lullaby. Terapi musik lullaby adalah terapi mendengarkan musik pada bayi BBLR yang dapat meningkatkan relaksasi, mengurangi presepsi terhadap nyeri, dan memberikan stimulasi suara yang akan mempengaruhi fugsi fisiologi terutama bila bayi mendapatkan tindakan yang memberikan rasa nyeri, mendengarkan musik lullaby melalui speaker aktif selama 45 menit dengan durasi waktu 3 hari berturut – turut serta frekuensi desibel 60 – 70 dB. Hasil dari terapi musik lullaby didapatkan bahwa hari pertama sampai hari ketiga hemodinamika pada bayi mengalami kestabilan. Hemodinamika heart rate pada bayi 1 mengalami kenaikan yang signifikan yaitu dari rata – rata 128,6 menjadi 133,3, serta suhu rata – rata 36,5 menjadi 37,2 dan SpO2 dari rata – rata 95 menjadi 96,3, sedangkan pada bayi 2 heart rate rata – rata mengalami penurunan dari 126,3 menjadi 126, suhu mengalami peningkatan dari rata – rata 36,7 menjafi 37,0 dan SpO2 mengalami kenaikan dengan rata – rata 92 menjadi 93,3 kemudian pada bayi 3 hemodinamik heart rate mengalami kenaikan yang cukup signifikan yaitu dari rata – rata 124 menjadi 130,6, pada suu mengalami kenaikan dari 36,6 menjadi 37,1 dan pada SpO2 mengalami kenaikan dari rata – rata 94 menjadi 96,3. Heart rate dari kedua subjek mengalami kenaikan setelah diberikan terapi musik lullaby sedangkan heart rate pada 1 bayi mengalami penurunan, suhu dan SpO2 pada ketiga bayi mengalami kenaikan yang cukup signifikan dilihat dari rata – rata hemodinamik yang ada pada lembar observasi masing – masing subjek.
Penerapan teori Self-Care Orem dan Self-Transcendence Pamela pada klien dengan breast engorgement
Authors: Dhamanik Reina , Rachma Imami Nur , Budiati Tri
Published: August 2024

Penerapan Teori Self-Care Orem Dan Self-Transcendence Pamela Pada Klien Dengan Breast Engorgement. Perubahan fisik, emosional, kognitif merupakan salah satu periode paling sensitive dalam kehidupan ibu pasca melahirkan. Kondisi pembengkakan payudara (breast engorgement) menjadi permasalahan umum yang terjadi pada ibu postpartum di masa menyusui, namun jika penatalaksanaan kurang tepat dapat mengakibatkan kondisi ketidaknyaman pasca melahirkan hingga mengganggu kondisi psikologis, mulai dari muncul kecemasan hingga depresi. Pemberian penatalaksanaan non farmakologi yang ada telah dilakukan untuk kebermanfaatan bagi ibu secara mandiri dan tenaga kesehatan di dalam menurunkan resiko mastitis yang dialami ibu selama proses menyusui. Metode yang digunakan dalam case study ini dengan fokus penerapan teori self-care Dorothea Orem dan teori Self-Transcendence Pamela G. Reed yang bertujuan untuk mengajarkan kemandirian pada ibu yang dimulai dari fase taking hold sampai masa nifas untuk mencapai kesejahteraan (well-being) dengan kesadaran (vulnerability) menyusui dan mencukupi kebutuhan nutrisi bayi sehingga ibu mampu mengaplikasikan kemampuan diri dalam mengelola afek positif dan negatif pada kondisi pembengkakan payudara (breast engorgement).
PENGEMBANGAN BOARD GAME SNAKE-TRUE/FALSE BERBASIS ANDROID SEBAGAI PENUNJANG PEMROGRAMAN C++ DI SMKN 1 SURABAYA
Authors: Wahyudianto Bagus , Prapanca Aditya
Published: August 2024

Snake-True/False merupakan board game berbasis android yang dikembangakan menggunakan unity sebagaai game engine. Tujuan dari pengembangan Snake-True/False adalah sebagai media pembelajaran penunjang pelajaran pemrograman C++ untuk siswa kelas X RPL SMKN 1 Surabaya. Metode penelitian ini menggunakan ADDIE yang memiliki 5 tahap yaitu Analisis, Desain, Pengembangan, Implementasi dan, Evaluasi. HIgh-fidelity prototyping dipakai untuk perancangan desain pada tahap ADDIE untuk mempermudah pengembangan di unity. Hasil validasi oleh para ahli terhadap board game Snake-True/False mendapatkan persentase total sebesar 89% yang dikategorikan sangat layak untuk digunakan sebagai media pembelajaran penunjang pemrograman C++ khususnya materi perulangan dan array. Pengambilan data dari 36 siswa menggunakan eksperimen dengan desain One group Pretest Posttest mendapatkan peningkatan rata-rata nilai sebesar 28.6. Hasil dari angket kepuasan siswa yang menggunakan model End User Computing Satisfaction (EUCS) mendapatkan rata-rata 4,57 yang dikategorikan sangat tinggi.
MODUL PEMBELAJARAN BERORIENTASI APLIKASI SET.A.LIGHT 3D MATERI TEKNIK PENCAHAYAAN PADA MATA PELAJARAN DESAIN GRAFIS PERCETAKAN
Authors: Sholihin M David Irsyadus , Prismana I Gusti Lanang Eka
Published: August 2024

Desain Grafis Percetakan (DGP) adalah mata pelajaran penting yang harus dikuasai oleh peserta didik program keahlian multimedia. Teknik pencahayaan dalam pengambilan gambar adalah salah satu materi yang ada dalam DGP. Menurut hasil observasi siswa masih sulit untuk memahami materi dan sibuk dengan kegiatan mereka masing-masing, hal tersebut dikarenakan belum adanya bahan ajar dan media yang inovatif yang membahas mengenai teknik pencahayaan dalam pengambilan gambar. Oleh karena itu pengembangan modul pembelajaran berorientasi aplikasi set.a light 3D pada materi teknik pencahayaan dan didukung dengan teknologi Augmented Reality Video merupakan solusi yang cukup efektif dalam mengatasi permasalahan yang terjadi. Model pengembangan 4D diterapkan dalam penelitian ini, tahapan yang dilakukan terdiri dari define, design, develop, disseminate. Pada tahapan ini proses validasi modul pembelajaran diberikan oleh validator dari aspek materi dan media. Pendapat siswa terhadap modul didapatkan melalui angket respon siswa yang disebarkan setelah penggunaan modul. Selain itu uji t dilakukan guna membandingkan hasil belajar setelah dilakukan perlakuan dalam materi teknik pencahayaan. Validasi materi mendapatkan nilai 0,87 dan validasi media 0,95 dengan kategori validitas tinggi. Respon siswa mendapatkan nilai rata-rata 3,60 yang menunjukkan peserta didik memberikan respon positif terhadap media pembelajaran. hasil uji t menunjukan bahwa modul pembelajaran teknik pencahayaan dapat meningkatkan hasil belajar siswa dengan hasil T hitung > T tabel sebesar 51,857 > 2,03011. Dapat disimpulkan bahwa modul pembelajaran teknik pencahayaan valid dan berhasil memberikan peningkatan terhadap hasil belajar peserta didik.