Miracle-dz/UniFAR-FTUs huggingface dataset:
Emotion classification by removal of the overlap from incremental association language features

With the increased incidence of depressive disorders, many psychiatric websites have developed community-based services such as message boards, web forums and blogs for public access. Using machine learning approaches, we can identify user's emotions from such forum and blog posts to recognize the variance in depressive disorders automatically. The incremental association language feature is applied in this research to discover words with high information content in sentences. In past research, the overlap-category in building a feature has not been considered. Hence, this work makes a pioneering attempt to develop a model for emotion classification with overlap-category consideration. This research applies association rule mining to discover words appearing with high frequency in a sentence and to avoid a feature-overlap in categories simultaneously. The approach is named Association Language Features by Category (ALFC). The experimental results show that ALFC features have ability to distinguish between the various categories. The result has been compared with the approach of baseline and mutual information which use single words and correlation measures respectively.
Distribution and Clinicopathological Characteristics of Breast Cancer Molecular Subtypes in Turkish Women

Purpose: Today, racial/ethnic differences in the incidence and prognosis of breast cancer (BC) are a well-known fact. This study aimed to examine the distribution of BC molecular subtypes in Turkish women and their relationship with other prognostic clinicopathological variables. Methods: In our surgical oncology clinic, the database of 480 BC cases was retrospectively scanned between January 2008 and December 2020, and the demographic and histopathological results of the patients were recorded. Patients were classified into five main molecular subtypes. Survival curves were estimated using the Kaplan – Meier method. The relationship between categorical variables was analyzed using the chisquare test. Results: The mean age of the patients at the time of diagnosis was 54.5 years, 46.3% were premenopausal, the mean tumor size was 28.7 mm, most of them were T1 (54%), ER, PR, HER-2 positivity rates were 79.6%, 73.1%, 38.3%, respectively and Ki-67 index average was 31.6. The most common molecular subtype was Luminal B Her2B-(33.5%). During a mean follow-up period of 56.9 months, 5 and 10-year overall survival (OS) rates were 89.5%, 79.6%, respectively, and disease-free survival (DFS) rates were 86.9%, 70.5%, respectively. The recurrence rate was 12.3%, distribution by molecular subtypes was significant (p=0.02). Luminal A and Luminal B/Her2- were in relation with Lobular Carcinoma (p=0.005), low histological grade (p=0.00), small tumor size (p=0.00), absence of lymphovascular invasion (LVI) (p=0.00), breast conserving surgery (p=0.022), presence of menopause (p =0.005) and local disease (p =0.013). Conclusions: This study showed that there are differences in molecular subtyping for symptomatic BC in Turkish women.
Bulk Acceleration in Relativistic Jets and the Spectral Properties of Blazars

Models for the synchrotron and inverse Compton emission from relativistic jets with bulk acceleration are studied, under the assumption that the bulk velocity increases with increasing distance along the jet while the emission spectrum shifts to lower frequencies. The apparent simplicity of BL Lac spectra is interpreted as being due to the convoluted emission from a relativistic jet whose innermost regions at rest emit the highest frequencies, while outer regions, with increasing bulk velocity, emit lower frequencies. The observed broadband energy distributions strongly constrain the properties of such jets. The model predicts that rapid X-ray variability is associated with steep X-ray spectra, while objects with flat X-ray spectra are expected to be more variable at optical to radio frequencies. The absolute space density of radio-strong objects should be 0.01-0.05 of that of radio-weak objects with the same X-ray luminosity. 18 refs.
A dynamic theory of transverse freezing in the Sherrington-Kirkpatrick Ising model

The effect of a transverse field Gamma on spin-glass freezing in the Sherrington-Kirkpatrick version of the quantum Ising model is studied by using the thermo-field-dynamic (TFD) method (the real-time finite-temperature quantum-field theory) due to Takahashi and Umezawa as a substitute for the 'n-replica trick'. An exact effective Lagrangian for the average dynamic causal and response functions is derived by using the functional-integral approach. Furthermore, the properties of the Lagrangian are studied in the mean-field limit by considering the infinite-range random exchange. In this limit the self-consistent equations for the matrix components of the TFD causal Green function are derived with the effective thermal Hamiltonian containing the dynamic spin self-interaction. The static properties of this equation are studied above and below the freezing temperature Tc by extracting the time-delocalised parts of dynamic autocorrelations. The self-consistent equations for the spin-glass order parameter and local susceptibility are obtained. The classical ( Gamma to 0) and quantum (T to 0) limits are discussed. The crucial role of the choice of the thermal-state condition for the spin-glass problem and its striking similarity to the non-equilibrium formulation of the TFD are pointed out.
Experimental Determination Of RepresentativeElementary Volume Of Sands Using X-rayComputed Tomography

The concept of a representative elementary volume (REV) provides an effective means of developing macroscopic measures in the description of granular materials. However, due to the difficulties associated with the measurement and characterization of granular microstructure the existence and size of an REV has remained largely conjectural. This study presents a systematic method to examine the characteristics of the REV using X-ray computed tomography images. The 3-D images of Silica sand, and Ottawa sand have been characterized using advanced image processing techniques. The porosity variation of Silica sand and Ottawa sand showed three characteristic regions: an initial fluctuation region due to microscopic variations, a constant plateau region, and a region with a monotonic increase/decrease due to heterogeneity. The results show that for Silica sand composed mainly of elongated particles the REV is between 5 to 11 times of D50 and for Ottawa sand composed mainly of subrounded particles is between 9 to 16 times of D50.
Klasifikasi Sentimen Judul Berita Pemberitaan COVID-19 Tahun 2021 pada Media DetikHealth

Penelitian ini merupakan penelitian linguistik terapan yang mengombinasikan linguistik dan ilmu komputasi dan berfokus di bidang natural language processing (NLP). Fenomena yang dikaji adalah klasifikasi sentimen pada judul berita pemberitaan COVID-19 di media DetikHealth selama tahun 2021 sehingga orientasi penelitian ini adalah mengklasifikasikan sentimen pada fenomena tersebut. Pengumpulan data dilaksanakan dengan memanfaatkan fitur saring yang disediakan media tersebut dan analisis data dilakukan dalam dua tahap besar, yaitu text preprocessing dan klasifikasi sentimen. Algoritma yang diimplementasikan dalam penelitian ini adalah algoritma MultinomialNB yang merupakan bagian dari naïve bayes classifier. Hasil dari penelitian ini adalah diperolehnya tingkat akurasi prediksi sentimen sebesar 72.5%. Selain itu, uji coba dengan tanpa melakukan salah satu atau keseluruhan tahapan preprocessing data memberikan dampak terhadap tingkat akurasi mesin. Penurunan tingkat akurasi paling menonjol terlihat pada uji coba tanpa stemming. Uji coba tanpa stemming menunjukkan adanya pemahaman linguistik yang berbeda jika tahapan stemming dilakukan dan penurunan tingkat akurasi mesin. Temuan lain adalah label sentimen netral adalah label sentimen berita dengan prediksi benar tertinggi dan label positif adalah label yang relatif salah diprediksi mesin. Implikasi dari hal ini adalah label positif merupakan label yang berpotensi mengalami kekeliruan prediksi. Kata Kunci—klasifikasi sentimen, text preprocessing, NLP
Automatic Tracking of Surgical Instruments with a Continuum Laparoscope Using Data‐Driven Control in Robotic Surgery

In existing surgery process, surgeons need to manually adjust the laparoscopes to provide a better field of view (FOV) during operation, which may distract surgeons and slow down the surgery process. Herein, a data‐driven control method that uses a continuum laparoscope to adjust the FOV by tracking the surgical instruments is presented. A Koopman‐based system identification method is first applied to linearize the nonlinear system. Shifted Chebyshev polynomials are used to construct observation functions that transfer low‐dimension observations to high‐dimension ones. The Koopman operator is approximated using a finite‐dimensional estimation method. An optimal controller is further developed according to the trained linear dynamic model. Furthermore, a learning‐based pose estimation framework is designed to detect keypoints on surgical instruments and provides visual feedback for the control system. Compared with other detection methods, the proposed scheme achieves a higher detection precision and provides more optional keypoints for tracking. Simulation and experiments validate the feasibility of the proposed control method. Experimental results show that the proposed method can automatically adjust the field of continuum laparoscope by tracking surgical instruments in real time and satisfy the clinical requirements.
Printer banding estimation using the generalized spectrum

This paper compares multi-step algorithms for estimating banding arameters of a harmonic signature model. The algorithms are based on two different spectral measures, the power spectrum (PS) and the collapsed average (CA) of the generalized spectrum. The generalized spectrum has superior noise reduction properties and is applied for the first time to this application. Monte Carlo simulations compare estimation performances of profile (or coherent) averaging and non-coherent spatial averaging for estimating banding parameters in grain noise. Results demonstrate that profile averaging has superior noise reduction properties, but is less flexible in applications with irregular banding patterns. The PS-based methods result in lower fundamental frequency estimation error and greater peak height stability for low SNR values, with coherent averaging being significantly superior to non-coherent averaging. The CA has the potential of simplifying the detection of multiple simultaneous banding patterns because its peaks are related to intra-harmonic distances; however, good CA estimation performance requires sufficiently regular harmonic phase patterns for the banding harmonics so as not to undergo reduction along with the noise. In addition to the simulations, the algorithms are applied to samples from inkjet and laser printers to demonstrate the ability of the harmonic signature model in separating banding from grain and other image artifacts. Good results from experimental data are demonstrated based on visual inspection of examples where banding and grain have been separated.
Simple and effective method to quantify the optical performance of camera phones

A simple method based on binary line pair patterns to evaluate the image quality of camera phones is proposed in this paper, where four different spatial resolution line pairs are located at four different quadrants respectively. The value of Modulation Transfer Function (MTF) of the camera phones can be tested at four different spatial resolutions for the entire field of view (FOV) simultaneously. In addition, other key parameters of optical imaging quality criteria, such as image distortion, relative illumination can also be characterized in the same time. Moreover, the possible color moiré due to color aliasing from RGB channels can be detected and evaluated using the same test chart.
Klasifikasi Data Trafik Jaringan dengan Framework Big Data Analitik

Pada era Big Data perkembangan data menjadi sangat pesat berbagai teknologi menghasilkan data sangat cepat dengan berbagai format dan struktur data. Dengan masifnya data menjadi permasalahan dalam pengolahan dan analisis data untuk mendapatkan informasi terkait data tersebut. Masifnya data juga menjadi masalah dalam pengelolaan jaringan komputer. Dengan perkembangan teknologi jaringan yang mengarah ke virtualisasi jaringan dan semakin banyaknya penggunaan IoT menghasilkan data yang semakin beragam. Beragamnya data menimbulkan kesulitan dalam manajemen, monitoring dan keamanan jaringan. Data trafik jaringan yang dihasilkan berbagai perangkat memiliki struktur yang beragam dan jumlah data yang semakin besar menyulitkan mekanisme pemantauan dan pendeteksi serangan untuk menemukan pola serangan. Munculnya konsep Big Data Analitik menjadi satu solusi dalam manajemen data, Big data analitik adalah proses mendapatkan informasi yang bermanfaat lewat analisis berbagai jenis kumpulan data yang berukuran sangat besar. Pada penelitian ini menggunakan pendekatan big data analitik untuk melakukan klasifikasi pada trafik jaringan untuk mengelompokkan data normal atau yang diindikasikan serangan pada jaringan. Penelitian ini menggunakan Network Traffic Project dari kaggle. Spark dipilih sebagai framework big data analitik yang digunakan dalam proses klasifikasi trafik jaringan.
A Crowd-Sourcing Project to Understand, Prevent and Manage Incidences of Injury and Wounding to Astronauts and Off-Earth Colonists

Recent technical successes of the unmanned Mars 2020, Tianwen-1 and Hope Mars missions have further increased our hunger for space exploration and the possible colonisation of Mars is now firmly on the mid-term horizon. Furthermore, renewed commitment to settle on the Moon is anticipated within the next three years, led by NASA’s Artemis programme utilising the pan-space agency constructed lunar Gateway or Space X’s Starship system. These programmes will necessitate a larger number of astronauts spending longer periods in space and despite rigorous risk identification and mitigation procedures, injury is an inevitable consequence and management procedures will demand efficient and effective implementation. We have employed Cognitive Work Analysis to derive an abstraction hierarchy for reducing the potential for physical injury and managing the consequence of injury in space. We have used a crowd-sourcing approach to cluster factors and themes which may emanate from within or without habitat and consider solution management in the light of current and emerging technology. In addition, we also consider mental fitness as a confounder which may emerge during missions and propose methods for both measurement and management. Doi: 10.28991/HEF-2022-03-03-04 Full Text: PDF
A REVIEW OF ENTREPRENEURSHIP EDUCATION RESEARCH AND PRACTICE

Entrepreneurship has increasingly captured policymaker’s attention due to the need to promote economic development and job creation. Among the drivers of entrepreneurship, entrepreneurial education is of particular significance. This paper reviews entrepreneurship education from a research and practice perspective. Firstly, a discussion is held as to whether entrepreneurial talent is born or bred. Secondly, the different approaches to entrepreneurship education are revised, specifying their distinctive characteristics. This is followed by a review of research on the potential of entrepreneurship education to awaken individuals’ entrepreneurial intentions. Finally, a series of practical considerations aimed at improving entrepreneurship education programs are proposed. Ultimately, this paper contextualizes entrepreneurship education, advocating its relevance in the promotion of entrepreneurial activity.
Electronically diabatic atom–atom collisions: A self‐consistent eikonal approximation

A detailed theoretical and computational study of electronic transitions has been done in the short‐wavelength (or eikonal) limit for the nuclear motions. Equations for nuclear trajectories in effective potentials are simultaneously solved with equations for electronic transition amplitudes. The treatment is done in adiabatic and diabatic electronic representations, and is applied to three model potentials: noncrossing, crossing in the repulsive region, and crossing in the attractive region. Results from the eikonal approach are compared with exact coupled‐channel probabilities. It is found that a procedure based on the the diabatic representation and an average effective potential provides accurate results over wide ranges of collision energies, and is computationally efficient.
X-ray detection of hot intergalactic gas in small groups of galaxies.

With long observations using the IPC of the EINSTEIN-X-ray-observatory we have detected extended X-ray emission from hot gas in the two groups of galaxies, around NGC3607 and NGC5846. Both galaxies are the dominant galaxies in small groups. The presence of the gas around NGC5846 can be understood with the theory of galactic winds and cooling flows. Since the temperature of the gas is similar to the kinetic temperature of the motions of the galaxies in the group, the potential well of the group contains the gas, and so a comparison with other groups and clusters is useful. Since both groups studied by us show X-ray emission from extended hot gas, an extrapolation to all groups of galaxies is of interest.
A Multiple Ideal Point Model: Capturing Multiple Preference Effects from within an Ideal Point Framework

Previous research has suggested that households and individuals may possess multiple preferences for a given product category. These multiple preferences may be the result of multiple individuals in a household, different uses and usage occasions, and/or variety seeking. As such, single ideal point models that assume a single invariant ideal point may be operating from a false and misleading assumption. We propose a multiple ideal point model to capture these multiple preference effects. The basic premise of the model is that consumers may possess a set of ideal points, each of which represents a distinct preference. At any given purchase occasion, one of these points is “activated” with some probability, and choices are made with respect to its characteristics. In this article, the authors assess the multiple ideal point model and an associated estimation procedure with respect to the model's ability to recover a true choice structure. The authors then empirically test the model on Information Resources Inc. panel data from the powdered soft drink category. The authors discuss the results and introduce directions for further research.
Challenges and possibilities in consumers’ views of organic foods in Rajshahi

This study attempts to investigate how customers view organic food. This essay also tries to investigate the issues with promoting organic farming. Lack of knowledge about organic technology and consumer distrust of goods and advertising strategies are among the important problems. It is discovered that a variety of factors affected people's decisions to buy organic food. Health and environmental awareness were positively correlated with educational attainment. The majority of consumers expressed interest in learning more about the production of organic foods, and it is evident that organic agriculture might lessen the harmful effects of chemical agriculture. The majority of customers expressed a lack of trust in organic food products by being unwilling to pay more for quality assurance and organic certification. Furthermore, there is a significant opportunity to meet the local demand for organic food, notably on the vast agricultural acreage in Rajshahi. Rajshahi has the chance to increase organic food production thanks to the lower wage, which will afterwards lead to the creation of good jobs. The barriers to the growth of the organic markets were recognized as ignorance, ecological consciousness, consumer trust, accreditation, quality control mechanisms, current technology, information literacy, storage capabilities, and crop insurance. The agricultural market chain, which is made up of many intermediary organizations, is also vulnerable. A big benefit of producing organic products that require meticulous care is the accessibility of cheaper labor forces.
Fluorescence imaging of vascular endothelial growth factor in mice tumors using targeted liposome ICG probe

Indocyanine Green encapsulating liposomes (Lip/ICG) and scVEGF-Lip/ICG liposomes, decorated with site-specifically lipidated engineered single-chain vascular endothelial growth factor (scVEGF) for targeting VEGF receptors were tested as potential tracers for fluorescent tomography. Two groups of experiments were conducted with tumor-bearing mice (n=4 to 6 per group) with tumors placed in a scattering medium at the imaging depths of 1.5 and 2.0 cm. Lip/ICG and scVEGF-Lip/ICG were injected intravenously in the amounts corresponding to 5 nmol of ICG/mouse. We detected kinetics of increase and decline in fluorescent signals in tumors for both imaging depths and for both targeted and untargeted Lip/ICG. Maximum fluorescent signals were approximately 2-fold higher at 1.5 cm vs. 2.0 cm imaging. A signal from untargeted Lip/ICG reached maximum at 15 min post-injection and then rapidly declined with t1/2 ~15 min. In contrast, a signal from targeted scVEGF-Lip/ICG reached maximum at 30 min post-injection and then slow declined with t1/2 ~60-90 min. Preferential retention of scVEGF-Lip(ICG) vs. Lip(ICG) was confirmed by the analysis of fluorescence in cryosections of corresponding tumors, harvested at 400 min post-injection. Our results suggest that targeted scVEGF-Lip/ICG can provide for significantly better post-injection time window for detection of relatively deeply seated tumors.
Health Hazards, Hematological and Biochemical Alterations in Dry-Cleaning Workers using Perchloroethylene.

Perchloroethylene (PERC) is commonly used as a dry-cleaning solvent, it is attributed to many deleterious effects in the biological system. The study aimed to investigate the harmful effect associated with PERC exposure among dry-cleaning workers. The study was carried out on 58 adults in two groups. PERC-exposed group; include thirty-two male dry-cleaning workers using PERC as a dry-cleaning solvent and twenty-six healthy non-exposed subjects. History of PERC exposure, use of personal protection equipment (PPE), safety measurement of the exposed group was recorded. Blood sample was taken from each participant for measurement of hematological markers, liver and kidney function tests. The results showed that 28.1% of the workers were using PPE regularly while 71.9% of the workers were not. Most of the workers 31(96.9%) were disposed of their waste products in improper way. Non-significant differences were observed in hematological indices between PERC-exposed group and non-exposed group. Serum level of kidney and liver function markers of the dry-cleaning workers were higher with statistically significant difference compared with the non-exposed group. In conclusion, a non-significant alteration in hematological parameters, while significant changes in part of liver and kidney functions indices have been demonstrated. Clinical observation indicated a harmful effect in PERC-exposed group. Key words: Occupational, PERC, personal protective equipment, dry cleaner