bluuebunny/crossref_metadata_2025 huggingface dataset:
IMAGING OF RHINO-ORBITO-CEREBRAL MUCORMYCOSIS A PROSPECTIVE OBSERVATIONAL STUDY IN THE SETTING OF COVID 19 PANDEMIC IN A TERTIARYCARE CENTRE IN AP, INDIA
Authors: Sathishkumar P. , Sindhura K. , Sudha Rani Bomidi , Bujjibabu P.
Published: February 2022

Background: Rhino-orbito-cerebral mucormycosis (ROCM) is a potentially fatal fungal infection that commonly affects diabetic and other
immunocompromised patients. Necrotizing and angioinvasive features of this class of pathogenic fungi facilitate spread from sinuses into orbit and
brain with devastating consequences. Early diagnosis and timely intervention is key to successful treatment
Objective: To interpret the Imaging ndings of all patients presented with ROCM at various stages on CT and MRI .
Materials and methods: This prospective observational descriptive study was conducted in the Department of Radiodiagnosis, Andhra Medical
College, King George Hospital, Visakhapatnam, India from April 2021 to August 2021 for 5 months. Reviewed 100 patients of adult age group
with strong clinical complaints suggestive of ROCM predominantly by MRI and also by CT
Results: We presented 100 cases of ROCM to emphasize effectiveness of magnetic resonance imaging (MRI) in diagnosis of this potentially fatal
form of mucormycosis.. CT and MR imaging of 100 patients showed predominantly pan-sinus involvement (67%). Extension to the orbit and face
(66%) preceded involvement of the deep skull base (62%) and brain (40%). Bone erosion was seen less often (40%), with rest (60%) of the patients
showing extra sinus extension across grossly intact appearing bones on imaging.
Conclusion: CT and MRI show a spectrum of ndings in rhinocerebral mucormycosis. Imaging plays a major role in assessing the extent of
involvement and complications. DWI may add specicity to the diagnosis by showing restricted diffusion in the path of fungal invasion. Thus
Magnetic resonance imaging is highly useful imaging modality for the diagnosis of ROCM and for staging of the disease.
Improved Spike-based Brain-Machine Interface Using Bayesian Adaptive Kernel Smoother and Deep Learning
Authors: Ahmadi Nur , Adiono Trio , Purwarianti Ayu , Constandinou Timothy , Bouganis Christos-Savvas
Published: February 2022

Multiunit activity (MUA) has been proposed to mitigate the robustness issue faced by single-unit activity (SUA)-based brain-machine interfaces (BMIs). Most MUA-based BMIs still employ a binning method for estimating firing rates and linear decoder for decoding behavioural parameters. The limitations of binning and linear decoder lead to suboptimal performance of MUA-based BMIs. To address this issue, we propose a method which consists of Bayesian adaptive kernel smoother (BAKS) as the firing rate estimation algorithm and deep learning, particularly quasi-recurrent neural network (QRNN), as the decoding algorithm. We evaluated the proposed method for reconstructing (offline) hand kinematics from intracortical neural data chronically recorded from the primary motor cortex of two non-human primates. Extensive empirical results across recording sessions and subjects showed that the proposed method consistently outperforms other combinations of firing rate estimation algorithm and decoding algorithm. Overall results suggest the effectiveness of the proposed method for improving the decoding performance of MUA-based BMIs.
Ground-based Remote Sensing of Total Columnar CO2, CH4, and CO using EM27/SUN FTIR spectrometer at a suburban location in India and validation of Sentinel-5p/TROPOMI
Authors: Sagar Vijay Kumar , P Mahesh , D.V. Mahalakshmi , K.S. Rajan , M.V.R Sesha Sai , Hase Frank , Dubravica Darko , Sha Mahesh Kumar
Published: February 2022

Greenhouse gasses (GHGs) play an important role in controlling local air pollution as well as climate change. In the present study, we retrieved column-averaged dry-air (X) mole fractions of carbon dioxide (CO2), methane (CH4), and carbon monoxide (CO) using a ground-based EM27/SUN Fourier Transform Infrared Spectrometer (FTIR). The EM27/SUN spectrometers are widely in use in the COllaborative Carbon Column Observing Network (COCCON). The PROFFAST software provided by COCCON has been used to analyze the measured atmospheric solar absorption spectra. In this paper, the diurnal variation and the time series of daily averaged XCO2, XCH4, and XCO covering the period December 2020 to May 2021 are analyzed. The maximum values of XCO2, XCH4, and XCO are observed to be 420.57 ppm, 1.93 ppm, and 170.40 ppb respectively. Less diurnal (XCO2 ~0.44 ppm; XCH4=0.004 ppm, and XCO=4.84 ppb) but clear seasonal changes are observed during the study period. The XCH4 and XCO from the Sentinel-5Precursor (S5P)/TROPOspheric Monitoring Instrument (TROPOMI) are compared against the EM27/SUN retrievals. The correlation coefficient ‘r’ between the EM27/SUN retrieved XCH4 and XCO against S5P/TROPOMI are 0.75 and 0.94 respectively.
Performance Evaluation of ANFIS Network in Determination of Inverse Kinematic Equations for a 4DOF Robotic Arm
Authors: Udosen David
Published: February 2022

The paper evaluates the ability of the Adaptive Neuro-Fuzzy Inference System (ANFIS) Network to develop its own set of inverse kinematics (IK) equations when trained with forward kinematics data. The forward kinematics equation is developed using the Denavit-Hartenberg (D-H) approach while the inverse kinematics equations (which is used to test the ANFIS Network) is developed analytically using geometry. This evaluation is carried out on a four degree of freedom (4DOF) robotic arm.
Interpolation of Dispersion Relations and Group Index in Photonic Crystal Waveguides using Artificial Neural Network
Authors: Pavan Vadapalli Durga Rama , Vangety Nikhil , Dey Koustav , Sharma B Umamaheswara , Roy Sourabh
Published: February 2022

Designing dispersion free photonic crystal structures
requires lot of computational time. Often, these structures are designed by
solving the conventional Maxwell’s equations. Different computational
techniques are available for solving such coupled equations and obtaining the
eigen frequencies of the system. However, these methods are time consuming and
limit the designing of dispersion free structures. On the other side, Machine
learning and deep learning are providing the assistance to the researchers in
finding the solutions for various complex, time consuming and tedious problems.
In the field of dispersion free structure, researchers are choosing machine
learning for designing, developing and analyzing various structures. Here, in
this paper, we made an attempt to adopt machine learning for predicting the
dispersion values and group indices of a lattice shifted photonic crystal
waveguide. Conventional methods are used to generate the eigen frequencies,
group indices and wave vector points of the structure. These data sets are used
for training the machine by artificial neural network. The model is trained and
optimized to predict the dispersion parameters and group indices with applied
lattice shift. Repeated random sub-sampling cross validation is used for
testing the performance of the model. To the best of our knowledge, we made a
first attempt to study a lattice shifted photonic crystal waveguide using
machine learning. This work will be exciting and may lead to develop a
connection between tailored waveguide structures and machine learning.
DeepMuCS: A Framework for Mono- & Co-culture Microscopic Image Analysis: From Generation to Segmentation
Authors: Khalid Nabeel , Koochali Mohammadmahdi , Rajashekhar Vikas , Munir Mohsin , Edlund Christoffer , Jackson Timothy , Trygg Johan , Sjögren Rickard , Dengel Andreas , Ahmed Sheraz
Published: February 2022

Discrimination between cell types in the co-culture environment with multiple cell lines can assist in examining the interaction between different cell populations. Identifying different cell cultures along with segmentation in co-culture is essential for understanding the cellular mechanisms associated with disease states. Extracting the information from the co-culture models can help in quantifying the sub-population response to treatment conditions. In the past, there exists minimal progress related to cell-type aware segmentation in the monoculture and no development whatsoever for the co-culture. The introduction of the LIVECell dataset has provided us with the opportunity to perform experiments for cell-type aware segmentation. However, it is composed of microscopic images in a monoculture environment. In this paper, we have proposed a pipeline for coculture microscopic images data generation, where each image can contain multiple cell cultures. In addition, we have proposed a pipeline for culture-dependent cell segmentation in monoculture and co-culture microscopic images. Based on extensive evaluation, it was revealed that it is possible to achieve good quality cell-type aware segmentation in mono- and co-culture microscopic images.
Maxwell equations derived from (Coulomb’s Law + velocity), Maxwell-type Gravity derived from (Newton Law + velocity), Spin-Electromagnetism derived from (Coulomb’ Law + spin) --- by Universal Mathematical Field Theory (UMFT)
Authors: peng hui
Published: February 2022

A Universal Mathematical Field Theory (UMFT) is established, which states that the combination of the operations of both gradient and divergence of vector fields, such as electric field and velocity field, create the curl of an axial vector field, such as magnetic field. Utilizing UMFT, we mathematically: (1) derive the Extended-Maxwell equations and the Lorentz force from Coulomb’s law and the velocity of the source; (2) establish Maxwell-type gravitational equations and Lorentz-type gravitational force (Gravito-EM) from Newton’s law and velocity of gravitational source; (3) establish Classical-Spin-Electromagnetism (Spin-EM) from the Coulomb’s law and the spin of the spin angular velocity; (4) predicate the Spin related force. For a source moving with non-spatially-varying velocity the Extended-Maxwell equations reduce to Maxwell equations, which justifies UMFT and shows that the experiments-based Maxwell equations have mathematical origin. This derivation mathematically explains how a moving electric charge creates magnetic field, and shows that there is no magnetic monopole charge. UMFT shows that mathematical identities lead to physical dualities including duality between EM and Gravito-EM. The concepts, effects and phenomena of EM may be directly converted to that of gravity. The Gravito-EM are employed to study the accelerating universe, rotation curve and gravitation waves. The Gravito-EM can be quantized, along the line of quantizing EM, and unified with EM force. We derive, for the first time, the Spin-Lorentz-type force and Lagrangian-Lorentz-type force. If experimentally proved, the Spin-related force may be the 5th force. UMFT provides mathematical origins of physical dualities between Extended EM, Gravito-EM and Spin-EM.
KitBit: A New AI Model for Solving Intelligence Tests and Numerical Series
Authors: Gilpérez Aguilar José Manuel , Corsino Victor , Herrera Luis
Published: February 2022

The resolution of intelligence tests, in particular numerical sequences, has been of great interest in the evaluation of AI systems. We present a new computational model called KitBit that uses a reduced set of algorithms and their combinations to build a predictive model that finds the underlying pattern in numerical sequences, such as those included in IQ tests and others of much greater complexity. We present the fundamentals of the model and its application in different cases. First, the system is tested on a set of number series used in IQ tests collected from various sources. Next, our model is successfully applied on the sequences used to evaluate the models reported in the literature. In both cases, the system is capable of solving these types of problems in less than a second using standard computing power. Finally, KitBit's algorithms have been applied for the first time to the complete set of entire sequences of the well-known OEIS database. We find a pattern in the form of a list of algorithms and predict the following terms in the largest number of series to date. These results demonstrate the potential of KitBit to solve complex problems that could be represented numerically.
KitBit: An AI Cognitive Model for Solving Intelligence Test and Numerical Series
Authors: Gilpérez Aguilar José Manuel , Corsino Victor , Herrera Luis
Published: February 2022

The resolution of intelligence tests and in particular the numerical sequences have been analyzed through differentcognitive models and other approaches. In this article we present a new artificial intelligence computational model called KitBit, whichaims to mimic some of the reasoning process that humans use to solve problems. KitBit uses a reduced set of actions and theircombinations to build a predictive model that finds the underlying pattern of different numerical sequences, such as those included inintelligence tests and other much more complex. The system is capable of solving those problems in less than a second with standardcomputational power. The KitBit algorithms have been applied in the OEIS numerical sequence database, reaching the highest numberof series solved to date. Likewise, it is capable of solving the intelligence tests reported by previous models, according to the literature.In this article we expose the fundamentals of the system and its application in finding the patterns of numerical series in general, andmore specifically in cases where these series are part of intelligent tests, even though KitBit has demonstrated its ability to solve othertypes of Intelligence Quotient (IQ) problems, which will be addressed in later publications.
MAXVAR-based Distributed Correlation Estimation in a Wireless Sensor Network
Authors: Hovine Charles , Bertrand Alexander
Published: February 2022

The performance of most array signal processing tasks relies on the presence of correlation between sensor signals. In a wireless sensor network, where sensor nodes are spread out over a relatively large area, it is useful to identify nodes observing similar sensor signals and hence common phenomenons, for example to partition the network according to the observed latent signals and corresponding correlation structure. This can be achieved via the so-called MAXVAR formulation of generalized canonical correlation analysis, which finds a low-dimensional subspace that highlights correlated signal components between multiple nodes' observed signal subspaces. The classical procedure for computing the solutions of MAXVAR consists in performing a generalized eigenvalue decomposition after collecting all the sensors' signals at a fusion center. However, this typically incurs high communication and computational costs. In this paper, we describe a low communication and computational cost distributed algorithm that computes the solutions of MAXVAR without aggregating the nodes' observations at a central location. We show how a subset of those solutions can be used locally by each node to estimate the global correlation structure across all nodes in the network, thereby allowing any node to evaluate the presence of correlated signals at any other node, even if no direct link is shared. We prove the convergence of the algorithm and validate our method for estimating the correlation structure via simulations.
Data Summarization in Internet of Things
Authors: Deevi Sri Aditya , B. S. Manoj
Published: February 2022

With recent advances in the field of IoT (Internet of Things), the quantity of data being generated by various sensors and Internet users has increased dramatically which in turn has skyrocketed the need for efficient data compression methods. Data summarization is an efficient and effective technique for data compression that can generate a brief and succinct summary from typically larger quantities of data in an intelligent and highly useful manner, which can be done at various levels of abstraction. The impact of using such a technique in large IoT networks can be significantly advantageous in terms of reduction in the processing time, overall computation, data storage-transmission requirements, energy consumption and possible workload on IoT users. In this work, a review of existing methods for summarization techniques at various levels of abstraction of typical IoT networks are discussed. The levels of categorization that are considered are Low-level and High-level. Under each abstraction level, various techniques are further classified while briefly describing their essential characters.
Deep Neural Network: an Alternative to Traditional Channel Estimators in Massive MIMO Systems
Authors: Melgar Antonio , de la Fuente Alejandro , Carro-Calvo Leopoldo , Barquero-Pérez Óscar , Morgado Eduardo
Published: February 2022

Fifth-generation (5G) requires a highly accurate
estimate of the channel state information (CSI) to exploit the
benefits of massive multiple-input-multiple-output (MaMIMO)
systems. 5G systems use pilot sequences to estimate channel behaviour using traditional methods like least squares (LS),
or minimum mean square error (MMSE) estimation. However,
traditional methods do not always obtain reliable estimations: LS
exhibits a poor estimation when inadequate channel conditions
(i.e., low-signal-to-noise ratio (SNR) region) and MMSE requires
prior statistical knowledge of the channel and noise (complex to
implement in practice). We present a deep learning framework
based on deep neural networks (DNNs) for 5G MaMIMO channel
estimation. After a first preliminary model with which we verify
the good estimation capacity of our DNN-based approach, we
propose two different models, which differ in the information
processed by the DNN and benefit from lower computational
complexity or greater flexibility for any reference signal pattern,
respectively. The results show that, compared to the LS-based
channel estimation, the DNN approach decreases the mean square
error (MSE) and the system’s spectral efficiency (SE) increases,
especially in the low-SNR region. Our approach provides results
close to optimal MMSE estimation but benefits from not requiring any prior channel statistics information.
"IT-librarians": searching ways of innovation, labor mobility, or change of professional principles development?
Authors: Matvienko Oksana , Tsyvin Michael
Published: February 2022

The article is devoted to identifying trends in scientific thought regarding the role and functions of the library in the digital society, as well as the considerations of domestic scientists regarding IT technologies in library education.
The views of national scholars on the content of the IT education of librarians are analyzed, the proposals on their preparation with the focus on future activity not in libraries and possible functions of the library as a "forge frame" for IT companies are emphasized.
The term "Cybrarians" used in foreign publications is emphasized.
It is concluded that the desire to provide the future library specialist with all the digital competences in full, which in practice is often accompanied by unsystematic, formal filling of the curricula of IT disciplines without a scientifically methodically justified level and depth of their presentation to students.
The current situation is characterized by the spontaneity of innovations, which are justified by the terms "innovation", "mobility of the specialist in the labor market" (outside library institutions), theses about the "archaic" of the library and the unpopularity of the profession among modern entrants.
The content of the librarian's IT education in modern conditions should be aimed at the free use of modern technologies, the ability to set tasks before the IT specialists and the systematic formation of social and pedagogical communicative competences in the field of IT technologies, which corresponds to the axiology of library activity and the needs of the state and the individual overcoming digital inequality.
Prediksi Mahasiswa Berpotensi Drop Out Dengan Metode Iteratif Dichotomiser 3 (ID3)
Authors: Irmayanti Dede , Muhyidin Yusuf , Nurjaman Dede Arif
Published: February 2022

Pendidikan adalah proses mencari ilmu pengetahuan yang didapatkan dalam proses belajar mengajar selama masa pendidikan yang ditempuh. Tingginya tingkat keberhasilan mahasiswa dan rendahnya tingkat kegagalan mahasiswa merupakan cermin kualitas dari suatu perguruan tinggi. Banyaknya jumlah mahasiswa yang gagal dalam menyelesaikan pendidikan dapat berpengaruh terhadap nilai dari perguruan tinggi tersebut sehingga perlu dilakukan pencegahan sedini mungkin dengan melakukan prediksi terhadap mahasiswa yang berpotensi Drop out. Salah satu cara yang dapat digunakan adalah dengan menggunakan metode data mining klasifikasi. Metode yang digunakan pada penelitian ini adalah Knowlede Discovery in Database (KDD), proses pengolahan datanya menggunakan algortima id3 aplikasi yang digunakan adalah Orange. Jumlah data yang digunakan pada penelitian ini sebanyak 476 mahasiswa Sekolah Tinggi Teknologi Wastukancana Purwakarta angkatan tahun 2013 dan 577 mahasiswa angkatan 2017 sebagai bahan untuk melakukan prediksi dengan atribut yang dinilai adalah nilai IPS semester 1-4 dan Total SKS. Hasil perhitungan dievaluasi akurasinya dengan menggunakan confusion matrix. Penelitian ini menghasilkan decision tree yang digunakan untuk menentukan mahasiswa yang berpotensi Drop out dengan node akar adalah IPS4. Jumlah actual Drop out, predicted Drop out sebanyak 150 data, Jumlah actual Drop out, predicted Tidak sebanyak 55 data, Jumlah actual Tidak, predicted Drop out sebanyak 24 data, dan Jumlah actual Tidak, predicted Tidak sebanyak 238 data. Nilai akurasi perhitungannya sebesar 83,1%, presisi 86,2% dan recall 73,2%.
Analisis Forensik Digital Pada Aplikasi Instant Messaging Di Smartphone Berbasis Android Untuk Bukti Digital
Authors: Qibriya Maghvirna Rafika Dhewi , Ambarwati Awalludiyah , Susilo Kunto Eko
Published: February 2022

Digital forensik merupakan pengembangan dari ilmu forensik yang khusus digunakan untuk mengungkap suatu kasus kejahatan berbasis digital termasuk kasus cyber crime (kejahatan siber). Akvititas kriminal di dunia siber yang cukup meresahkan banyak pihak adalah kasus penipuan yang dilancarkan melalui aplikasi instant messenger (pesan instan). Pada penelitian ini akan dilakukan analisa kasus cyber crime pada aplikasi WhatsApp messenger dan Telegram messenger yang dioperasikan pada prangkat mobile dengan sistem operasi android menggunakan guideline dari National Institute of Standards and Technology (NIST) SP 80-100 Rev. 1. Dilakukan sebuah eksperimen dengan variasi skenario penggunaan normal tanpa ada modifikasi apapun dan melakukan penghapusan pada beberapa pesan sebagai indikasi tindakan anti forensik. Data dari setiap eksperimen akan diakuisisi menggunakan tools MOBILedit Forensic Express dan dianalisis dengan tools FTK Imager dan Autopsy. Berdasarkan dari hasil analisa pada kedua aplikasi instant messenger, hanya aplikasi WhatsApp messenger yang dapat memberikan bukti digital yang valid. Karakteristik bukti digital dari WhatsApp berdasarkan dengan struktur pesan adalah key_remote_jid, key_id, data, timestamp, dan received_timestamp. Sedangkan untuk Telegram messenger tidak dapat memberikan bukti digital lantaran tidak ditemukannya data penting pada seluruh direktori aplikasi ini. Dari sisi keamaan data aplikasi WhatsApp messenger memiliki tingkat kerentanan lebih tinggi karena kemudahan dalam melakukan praktik forensik, Sedangkan untuk tingkat keamanan pada aplikasi Telegram messenger dinilai lebih unggul karena tidak banyak data penting yang bisa didapat dan dianalisis. Tingkat sekuritas yang tinggi juga berakibat pada rumitnya tindakan forensik dalam pengungkapan sebuah kasus kejahatan.
Deteksi Wajah Berbasis Facial Landmark Menggunakan OpenCV Dan Dlib
Authors: Sejati RR Puji Hajar , Mardhiyyah Rodhiyah
Published: February 2022

Computer science and information technology have advanced in a variety of sectors that were previously unachievable due to constraints such as hardware. Computer vision can be used to recognize an object using computer science. Objects can be recognized by taking or recording photos or videos and then processing them using specific tools and methodologies. The goal of the facial landmark-based face detection research using OpenCV and Dlib is to perform face detection in people so that it can be used for a variety of purposes in the future. The strategy employed in this study was the usage of facial landmarks using OpenCV and Dlib to improve face detection accuracy. Face detection has been effectively carried out based on facial landmark points, according to the findings of testing the entire system. Face landmark-based face detection is more accurate using the OpenCV Dlib, which can be seen during processing in the OpenCV Dlib, which can precision photos based on facial movements.
DETERMINAN KESEJAHTERAAN PELAKU UMKM KERAJINAN DI KOTA DENPASAR
Authors: I Gde Wedana Arjawa dan  I Nyoman Senimantara
Published: February 2022

Tujuan pembangunan ekonomi adalah untuk meningkatkan kesejahteraan masyarakat. Pertumbuhan ekonomi nasional sangat ditentukan oleh dinamika perekonomian daerah, sedangkan perekonomian daerah pada umumnya ditopang oleh kegiatan ekonomi bersakala UMKM dan salah satunya adalah sektor kerajinan. Pemberdayaan UMKM ditujukan untuk membuat kehidupan pelaku UMKM dapat hidup sejahtera. Untuk dapat mewujudkan kehidupan yang sejahtera, pelaku UMKM kerajinan di Kota Denpasar mempunyai banyak keterbatasan sehingga usaha ini belum mampu untuk berkembang secara optimal terlebih ditengah pandemi covid-19 yang melanda saat ini. Dari studi pustaka, diketahui bahwa peran pemerinatah,  modal sosial, dan kinerja usaha berpengaruh terhadap kesejahteraan pelaku usaha. Tujuan dari penelitian ini adalah untuk menganalisis (1) pengaruh kinerja keuangan dan belanja modal terhadap kinerja perekonomian; (2) pengaruh kinerja keuangan, belanja modal dan kinerja perekonomian terhadap kesejahteraan masyarakat; dan (3) menganalisis pengaruh tak langsung kinerja keuangan dan belanja modal terhadap kesejahteraan masyarakat melalui kinerja perekonomian pada kabupaten kota di provinsi Bali. Penelitian ini dilakukan terhadap 97 sampel dan pengumpulan data dilakukan melalui kuesioner. Analisis data dilakukan dengan metode SEM-PLS. Hasil penelitian dan analisis data menunjukkan bahwa (1) peran pemerintah berpengaruh positif dan tidak signifikan, sedangkan modal sosial berpengaruh positif signifikan terhadap kinerja usaha; (2) peran pemerintah, modal sosial, dan kinerja usaha berpengaruh positif dan signifikan terhadap kesejahteraan pelaku usaha dan (3) peran pemerintah tidak berpengaruh tak langsung sedangkan modal social berpengaruh tak langsung terhadap kesejahteraan pelaku usaha melalui kinerja usaha.Peran pemerintah memegang peranan yang penting dalam pemberdayaan UMKM. Peran pemerintah belum mampu meningkatkan kinerja usaha namun mampu meningkatkan kesejahteraan pelaku usaha. Modal social mampu meningkatkatkan kinerja usaha dan kesejahteraan pelaku usaha dan kinerja usaha juga mampu memediasi hubungan modal social terhadap kesejahteraan pelaku UMKM di Kota Denpasar.
Negative Impact of COVID 19 on Physical, Mental and Socio-Economic Condition among General Patients
Authors: Amin Dr. S. M. Ruhul , Razzaque Dr. Abdur , Asraf Dr. Md. Moniruzzaman , Kabir Dr. Md. Rashadul
Published: February 2022

Covid-19 is the name of a serious pandemics in the current world. Although this disease is responsible for very limited symptoms and complications like severe acute respiratory syndrome, fever, headache, diarrhea, malaise and weakness but its probability of affecting more people is very high. For this reason, its psychological and socio-economic impact demanded more attention of the world community. We have very limited research-based information regarding this issue. The aim of this study was to evaluate the negative impact of Covid 19 on physical, mental and socio-economic condition among general non-Covid patients. This was a prospective survey-based study which was conducted in the Department of Medicine, Shaheed Ziaur Rahman Medical College, Bogura, Bangladesh during the period from July 2020 to December 2020. In total 128 patients with several health problems, physically or virtually attended the OPD of the mentioned hospital were enrolled as the study population. A pre-designed questionnaire was used in patent data collection. All data were processed, analyzed and disseminated by MS Office and SPSS version as per need. In analyzing the negative impact on physical health of participants we observed, 10.94%, 8.59%, 7.03%, 5.47% and 3.13% patients were with feeling of physical fatigue, gaining extra body-weight, insomnia, general weakness and having chronic disease respectively. In this current study, in analyzing the negative impact on mental health of participants we observed feeling of suffocation, feeling of exhausted, fear of falling ill and anxiety about future were found as some major negative mental impacts of Covid 19 on the respondents which was among 11.72%, 10.94%, 8.59% and 7.81% participants respectively. As negative impact on social life of participants due to Covid 19 continuing remote socialization, intolerance to others, random commitment violation and ended social life were found among 8.59%, 3.91%, 3.13% and 1.56% participants ...............
Analisis Harga Kebutuhan Pokok Dampak Covid-19 Perspektif Imam Yahya Bin Umar
Authors: Harsela Chiska Nova , Fauziyah Fa’iqotul
Published: February 2022

Unit Simpan Pinjam merupakan unit usaha yang paling besar menyerap modal usaha koperasi. Namun permasalahan yang terjadi yaitu pada penyusunan laporan keuangan koperasi masih terdapat kekurangan dan ketidaksesuaian dengan pedoman yang telah dibuat oleh Pemerintah yaitu Peraturan Menteri Koperasi dan UMKM No.13/Per/M.KUKM/IX/2015 tentang pedoman akuntansi usaha simpan pinjam koperasi. Penelitian ini bertujuan agar kita dapat memahami penyebab yang memicu terjadinya kenaikan harga bahan pokok di pasaran semenjak terjadinya pandemi covid19 dengan merujuk pada persepektif Imam Yahya Bin Umar sebagai ahli ekonomi islam yang pemikirannya berfokus pada sistem pasar. Penelitian ini menggunakan metode kualitatif dengan mencari dari beberapa referensi dan literature review yang mendukung materi kajian ilmiah, Hasil dari penelitian ini ialah : Dalam rangka memitigasi dampak COVID-19 pada perekonomian dan mencegah terjadinya kenaikan harga pada kebutuhan pokok atau terjadinya inflasi, Pemerintah telah mengumuman stimulus fiskal jilid I, II, dan III. Laporan keuangan yang telah disajikan oleh KPPP JABAR yaitu Neraca dan PHU keseluruhan telah disajikan cukup baik. Laporan keuangan KPPP JABAR yang sudah disajikan masih belum sesuai dengan komponen laporan keuangan menurut pedoman akuntansi simpan pinjam. Kesesuaian Laporan Keuangan Koperasi terhadap Permen No. 13 tahun 2015 jika dalam bentuk persentase sebesar 18,42%.
PENERAPAN MODEL DISCOVERY LEARNING DALAM MENINGKATKAN HASIL BELAJAR KIMIA SISWA KELAS XI IPA MATERI LARUTAN ASAM-BASA
Authors: Fatma Fatma , Marhadi Muh Alim , Rudi La
Published: February 2022

Telah dilakukan penelitian Penerapan Model Discovery Learning Dalam Meningkatkan Hasil Belajar Siswa Kelas XI IPA1 di SMA Negeri 1 Kusambi Pada Materi Larutan Asam-Basa. Penelitian ini bertujuan untuk mengetahu hasil belajar siswa , peningkatan hasil belajar siswa (N-gain) dan mengetahui respon siswa terhadap pembelajaran dengan menggunakan model discovery learning pada mata pelajaran Kimia materi larutan asam basa. Sampel dari penelitian adalah siswa kelas X1IPA1 yang diambil dengan menggunakan teknik random sampling. Penelitian ini menggunakan metode Pre Experimental Design dengan menggunakan one group pretest-posttest design. Kelas yang menjadi sampel diberikan pre-test dan post-test untuk materi larutan asam basa menggunakan instrument tes berbentuk pilihan ganda dengan jumalah 20 butir soal, data aktivitas guru dan siswa selama proses pembelajaran diambil dengan menggunakan lembar observasi dan data respon siswa diambil dengan lembar angket. Hasil analisis nilai pre-test diperoleh data nilai rata-rata sebesar 25,16. Hasil analisis untuk nilai post-test diperoleh nilai rata-rata sebesar 78,55, nilai tersebut lebih tinggi dibandingkan nilai pre-test dan telah mencapai nilai KKM. Nilai rata-rata N-gain pada kelas XI IPA1 sebesar 0,71 yang menunjukan bahwa efektivitas pembelajaran termasuk dalam kategori tinggi. Hasil analisis angket respon siswa yaitu 62,4%, data ini mnunjukan bahawa Respon siswa terhadap pembelajaran dengan menggunakan model discovery learning termasuk dalam kategori tinggi.
Efektivitas Model Pembelajaran Discovery Learning Untuk Meningkatkan Hasil Belajar Kimia Siswa Pada Materi Pokok Asam Basa Kelas XI IPA di SMA Negeri 1 loghia
Authors: Azhara Fatimah , Dahlan Dahlan , Tewa Yuniati
Published: February 2022

Penelitian ini bertujuan untuk mengetahui peningkatan hasil belajar kimia siswa kelas XI IPA 3 setelah diajar menggunakan model pembelajaran discovery learning, dan untuk mengetahui keefektifan model pembelajaran discovery learning dalam meningkatkan hasil belajar siswa, serta untuk mengetahui respon siswa yang diajarkan dengan menggunakan model pembelajaran discovery learning pada materi pokok Asam Basa. Penelitian ini dilaksanakan pada semester Genap Tahun Ajaran 2019/2020. Penelitian ini merupakan Pra-Eksperimen dengan One group Pretest Postest Design. Sampel dalam penelitian ini sebanyak 29 orang siswa kelas XI IPA 3 SMA Negeri 1 Loghia. Instrumen penelitian berupa soal pilihan ganda berjumlah 20 butir soal dan angket respon siswa. Hasil penelitian menunjukkan bahwa rata-rata hasil belajar siswa kelas XI IPA 3 setelah penerapan pembelajaran discovery learning sebesar 79,31. Penerapan model pembelajaran discovery learning dalam proses pembelajarn cukup efektif dengan nilai rata-rata N-gain sebesar 0,6829 masuk dalam kategori sedang. Dengan respon siswa yang diajarkan menggunakan model pembelajaran discovery learning tergolong dalam kategori sangat baik sebesar 83,62 %.
ANALISIS KETERAMPILAN BERPIKIR KRITIS SISWA PADA MATERI PERKEMBANGAN MODEL ATOM MELALUI PEMBELAJARAN BERBASIS MASALAH (PBL)
Authors: Afriyanto Afriyanto , Haetami Aceng , Marhadi Muh. Alim
Published: February 2022

Research has been carried out that aims to analyze the critical thinking skills of students  and  find  out  the  most  dominant  indicators  of  critical  thinking  skills  of students  after  the  implementation  of  the  Problem  Based  Learning  model.  This research was conducted in class X IPA SMA Negeri 1 Wawonii Utara. The sample of  this  study  was  21  students  of  class  X  science.  This  research  method  uses quantitative descriptive. The instruments used in this study are description tests and observation sheets. The results of data analysis show that the achievement of  students'  critical  thinking  skills  in  general  has  been  well  achieved.  The  most dominant  indicators  of  students'  critical  thinking  skills  in  the  high,  medium  and low  groups  are  the  same,  namely  the  interpretation  indicators  and  analysis indicators.
PENGEMBANGAN MEDIA PEMBELAJARAN VIRTUAL LAB DALAM PRAKTIKUM LAJU REAKSI
Authors: Tirmizi Atna , Rahmanpiu Rahmanpiu
Published: February 2022

Telah dilakukan penelitian Pengembangan Media Pembelajaran Virtual Lab dalam Praktikum Laju Reaksi di SMA Negeri 02 Bombana. Penelitian ini bertujuan untuk mendeskripsikan kevalidan, tanggapan guru dan siswa dalam praktikum Laju Reaksi yang dikembangkan. Metode penelitian yang digunakan adalah R&D (Research and Development) dan Model pengembangan yang digunakan adalah model pengembangan 4D yang merupakan kepanjangan dari define, design, development and disseminate, tetapi tidak sampai pada tahap disseminate hanya sampai development. Kevalidan virtual lab hasil pengembangan diukur berdasarkan hasil validasi ahli. Tanggapan guru dan siswa diukur berdasarkan penilaian guru dan respon siswa terhadap produk yang dikembangkan. Hasil penelitian menunjukkan bahwa rata-rata penilaian ahli materi sebesar 2,91 (kriteria sangat baik) dan rata-rata penilaian ahli media sebesar 2,83 (kriteria sangat baik). Tingkat keberterimaan virtual laboratory oleh siswa mencapai kriteria sangat mendukung sebesar 90% (uji coba skala terbatas). Sedangkan pada tingkat keberterimaan virtual laboratory oleh guru mencapai kriteria mendukung sebesar 50% (uji coba skala terbatas). Rata-rata skor tiap butir tanggapan siswa maupun guru mencapai kriteria sangat mendukung. Berdasarkan validasi ahli, tanggapan guru dan siswa, maka virtual laboratory layak digunakan sebagai media pembelajaran dalam praktikum laju reaksi.
PENGEMBANGAN LEMBAR KERJA PESERTA DIDIK (LKPD) BERBASIS PENDEKATAN SAINTIFIK PADA MATERI LARUTAN PENYANGGA DI KELAS XI IPA SMA NEGERI 2 BAUBAU
Authors: Nasfa Nasfa , Marhadi Muhammad Alim , Rahman Abraham
Published: February 2022

Penelitian ini bertujuan untuk mengembangkan Lembar Kerja Peserta Didik (LKPD) berbasis pendekatan saintifik pada materi larutan penyangga dan mengetahui respon/tanggapan guru dan peserta didik terhadap LKPD berbasis pendekatan saintifik pada materi larutan penyagga. Jenis penelitian yang dilakukan oleh peneliti adalah penelitian dan pengembangan (Research and Development) dengan menggunakan model 4-D yaitu pendefenisian (define), perancangan (design), pengembangan (development), dan tahap penyebaran (dessiminate). Instrumen yang digunakan berupa lembar penilaian/validasi isi dan tanggapan/respon guru dan peserta didik. Selanjutnya, data kedua terkait dengan angket yang berkaitan dengan pengimplementasian LKPD tersebut. Hasil dari angket tersebut adalah sebagai berikut: (1) LKPD berbasis pendekatan saintifik pada materi larutan penyangga yang dihasilkan melalui validasi oleh validator memperoleh persentase rata-rata sebesar 94,55% dengan kriteria sangat layak. (2) Praktikalitas dari guru kimia memiliki kategori nilai praktikalitas 87,98% (sangat praktis) dan berdasarkan data angket tanggapan guru terhadap LKPD memperoleh respon sangat posotif dengan presentase rata-rata 87,5% dengan kategori sangat setuju. (3) angket respon peserta didik memperoleh respon positif dengan persentase yang diperoleh yaitu desain LKPD 88,97% sangat layak, segi tampilan 88,62% sangat layak, materi 86,29% sangat layak, bahasa 89,98% sangat layak, dan saintifik 87,18% sangat layak.
PENGEMBANGAN MEDIA PEMBELAJARAN KIMIA MENGGUNAKAN LABORATORIUM VIRTUAL BERBASIS SMARTPHONE ANDROID
Authors: Fatahu Fatahu , Walukou Maryce Agusthinus , Mulyana Wa Ode , Mandasari Ekacahyana
Published: February 2022

Pembelajaran kimia memiliki kegiatan pembelajaran teori dan praktikum. Hasil wawancara dengan Kepala Madrasah Aliyah Negeri 1 Kendari bahwa siswa kurang memiliki kesiapan sebelum memasuki laboratorium dan keterbatasan alat dan bahan praktikum. Tujuan penelitian ini adalah sebagai alternatif solusi pada keterbatasan sumber daya pembelajaran di sekolah/madrasah yaitu kemudahan melakukan praktikum tanpa terikat waktu maupun kelas konvensional di laboratorium yang juga terbatas alat dan bahan praktikum. Penelitian ini dilaksanakan di Madarasah Aliyah Negeri 1 Kendari. Metode penelitian yang digunakan adalah Research and Development (R & D): (1) potensi dan masalah; (2) pengumpulan data; (3) desain produk; (4) validasi desain produk; (5) revisi desain produk; (6) uji coba produk terbatas. Aplikasi virtual lab diuji cobakan kepada 20 siswa kelas XI jurusan IPA untuk dilihat aktivitas dan respon siswa. Hasil penelitian menunjukkan 85% siswa “sangat mendukung” dan 15% “mendukung” terhadap media pembelajaran berupa aplikasi virtual lab.
Exogenous Shocks and Teachers’ Motivation to Learn: Pandemic and Professional Development in the United States
Authors: West Justin , Stanley Ann Marie , Appova Aina
Published: February 2022

Abstract
In this article, we examine how the COVID-19 pandemic, an exogenous shock to the United States education system, shaped teachers’ readiness and willingness to engage in professional development (PD). We borrow the concept of exogenous shocks from economics and sociology to illustrate how education practice can be driven as much by factors outside the field (e.g., viral outbreaks) as by those within it (e.g., policy and scholarship). Using the four substantive domains in Appova and Arbaugh’s (2018) framework on teachers' motivation to learn in PD—teacher education and PD, educational psychology, andragogy and adult learning, and policy and accountability—we argue that teacher motivation, rather than mere PD structure or content, is the true linchpin of teacher learning. In that light, we describe some of the pandemic’s demotivational effects on teachers’ learning in the U.S. and offer a roadmap for scholars to center motivation in future PD research. We outline several pathways of inquiry, including a renewed focus on links between teacher motivation and PD effectiveness, the generation and application of new measures and models of teachers’ motivation to learn, and the use of PD as an instrument for teacher resilience and efficacy after an exogenous shock.

Keywords: professional development, teacher learning, teacher motivation, COVID-19, pandemic
Islamic Microfinance Institutions and Empowering Women-Based MSMEs in an Effort to Reduce Poverty
Authors: Maulidia Sofi , Nur Mawardi
Published: February 2022

Poverty is a problem that has been rooted in society. One of the efforts to decrease a poverty is empower MSME through Microfinance Institutions because they can directly reach the grass root. This study aims to find out how the pattern and role of women-based MSME empowerment in poverty decrease efforts carried out by KSPPS Baytul Ikhtiar. The research method used is a qualitative method. The results of this study indicate that KSPPS Baytul Ikhtiar adopted a pattern of empowerment of the Grameen Bank which was modified in such a way with sharia principles. In addition, this study also shows that there are 4 main roles of KSPPS Baytul Ikhtiar in poverty alleviation efforts, providing access to capital, providing access to assistance, empowering women and her family.
Dukungan Sosial Pada Mahasiswa yang Terkena PHK di Masa Pandemi Covid-19 dan Pengaruhnya pada Minat dan Motivasi Berwirausaha
Authors: Leksono Ari Wahyu , Saputra Samin , Vhalery Rendika
Published: February 2022

Keadaan global saat ini masih dalam suasana pandemi covid-19. Terhitung sejak tanggal 02 oktober 2021, situasi covid-19 di Indonesia yaitu pasien yang positif sebanyak 4.218.142 orang, pasien yang sembuh sebanyak 4.042.215 orang, dan pasien yang meninggal sebanyak 142.115 orang. Kejadian ini terus menimbulkan banyak permasalahan, salah satunya yaitu pengangguran. Karyawan yang terkena PHK terdiri dari berbagai golongan masyarakat, salah satunya adalah mahasiswa. Mahasiswa di kelas khusus karyawan (kelas ekstensi) yang terkena PHK di kampus saat ini cukup banyak. Melalui wawancara kepada perwakilan mahasiswa yang di PHK, disimpulkan bahwa mereka mengalami stres akibat kejadian ini. Untuk menghindari stres atau sifat negatif berlebihan pada individu, diperlukan dukungan sosial kepada individu. Mahasiswa yang terkena PHK dan mendapatkan dukungan sosial lebih mudah untuk melangkah maju dan mencari solusi atas permasalahan ini. Dukungan sosial dapat dipengaruhi dan mempengaruhi bidang kewirausahaan. Tidak hanya itu, dukungan sosial juga dapat mempengaruhi minat berwirausaha dan motivasi berwirausaha. Untuk membuktikan statement tersebut, penelitian ini bertujuan untuk mengetahui pengaruh dukungan sosial terhadap minat berwirausaha mahasiswa yang terkena PHK di masa pandemi covid-19 dan pengaruh dukungan sosial terhadap motivasi berwirausaha mahasiswa yang terkena PHK di masa pandemi covid-19. Penelitian ini merupakan penelitian deskriptif dan asosiatif dengan pendekatan kuantitatif. Penelitian diawali dengan uji deskriptif untuk mengambarkan data penelitian secara rinci lalu dilanjutkan dengan uji asosiatif. Partisipan dalam penelitian ini adalah mahasiswa yang terkena PHK di Masa Pandemi Covid-19. Jumlah mahasiswa yang ikut menjadi partisipan dalam penelitian adalah 207 mahasiswa yang terdiri dari 105 perempuan (50,7%) dan 102 laki-laki (49,3%). Hasil analisis deskriptif menunjukkan bahwa dukungan sosial mahasiswa didominasi oleh mahasiswa yang memiliki dukungan sosial rendah. Dimensi dukungan sosial tertinggi adalah dimensi keluarga. Selain itu, pengaruh dukungan sosial terhadap minat berwirausaha dan motivasi berwirausaha menunjukkan adanya pengaruh.
Effects of Quizlet-Based Learning Activities on American High School Students’ Beliefs and Confidence in Learning Chinese as a Foreign Language
Authors: Wang Lih-Ching Chen , Lam Eddie , Hu Zhenzhen
Published: February 2022

Though it is not easy for Western learners to master, the Chinese language has gain its popularity in the United States in recent years. Modern digital instructional technologies can address some issues in learning difficulties of the language. This study examined the effects of Quizlet-based learning activities on the attitudes, beliefs, and confidence of urban American high school students (N = 56) in learning Chinese as a second language. Results of the mixed-design ANOVA indicated that students in the experimental group reported a significantly (p < .05) more positive attitude toward learning Chinese as a second language than the control group. Though both groups expressed less confidence in their ability in reading, listening, speaking, and learning Chines vocabularies, the experimental group lost a lesser degree of confidence in those areas. It is concluded that these Quizlet-based learning activities had a significantly positive effect on students’ beliefs and confidence in learning Chinese. Future studies should include a larger sample size that covers each grade level of the high school, as well as using other gamification-oriented learning tools to compare their effectiveness on students’ confidence in learning Chinese.
Participation Rate of Fifth Graders During COVID-19 Emergency: Synchronous Versus Asynchronous Learning Activities
Authors: Bacon Stephanie , Liu Leping
Published: February 2022

The COVID-19 pandemic has influenced teaching and learning in dramatic ways. Educators have made significant efforts to facilitate learning in dynamically changing formats, and students have experienced a very difficult time to learn in non-traditional environments and settings. This study focuses on participation rates of 5th grade students on a variety of learning activities or assignments in Language Arts and Social Studies that occurred over a three-month period in which the school pivoted from full remote learning to a hybrid model. Results from a non-parametric analysis on 42 learning activities indicate that students’ participation rates on synchronous assignments are higher than that on asynchronous assignments. Implications for increased attention to instructional design as they relate to technology integration and the unique circumstances of remote learning are discussed.
The Impact of Media Coverage on Obesity
Authors: Bernard Séverine , Cesar Ténissia , Pietrus Alain
Published: February 2022

In this paper, we develop a deterministic compartmental model for the obesity dynamics. Contrary to other contributions on this subject we explore the impact of the media on the spreading of this phenomenon in a constant population. Stability analysis shows that the disease-free equilibrium point is globally asymptotically stable when the number of reproduction is less than unity. We also show that the endemic equilibrium point when it exists is globally asymptotically stable under some conditions.