Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of the role of HRCT chest in the differentiation of pattern of spectrum in lung diseases

Introduction: - CT is a modality used in imaging of internal structures/ organs by the use of radiation. HRCT is an examination protocol in CT for Lungs and Temporal bone. As HRCT uses thin slices so it provides detailed information which helps in better diagnosis. Aim and Objective:- To evaluate the Role of HRCT Chest in differentiation of pattern of spectrum in lung diseases to find out the different patterns in lung diseases. Methods & Materials:- The study was conducted on a period of 6 months on 30 patients. 16 slice CT machine was used for the scanning and thin sections were acquired by using HRCT protocols. Result:- In out of 30 patients, the common findings are Ground Glass Opacities, Tree In Bud Appearance, Reticular Opacities, Honey Combing, Consolidation Nodular Opacities. Conclusion:- HRCT chest is most important and valuable in diagnosis of lung diseases even when chest X-ray is normal. It is capable of imaging the lung with excellent spatial resolution and provides good anatomical detail.
An Afterthought: Staff of Color and Campus Wellness Within Higher Education Responses to COVID-19

While higher education has continued to adjust to COVID-19, which has included moving to virtual platforms and supporting students’ mental health, what is absent from these conversations is the campus staff enacting the rapidly changing university context. These professionals in academic and student affairs, residential life staff, and advising staff have had to readjust roles, responsibilities, and programs, all while facing ambiguous threats of budget cuts and struggling with their own wellness. Through a qualitative study at a midwestern university using Critical Race Theory, this study focuses on both the pandemic as well as the endemic concerns of racism Staff of Color experience at their higher education institutions. Findings reveal disconnects between university values and communication with the (lack of) financial prioritization and care. While many seek a return to the pre-COVID-19 campus, the strategies, execution, and prioritization of staff hold much longer ramifications regarding campus retention, inclusion, and equity.
Oscillation Dynamics of Multiple Water Droplets Levitated in an Acoustic Field

This study aimed to improve and investigate the oscillation dynamics and levitation stability of acoustically levitated water droplets. Contactless sample manipulation technology in mid-air has attracted significant attention in the fields of biochemistry and pharmaceutical science. Although one promising method is acoustic levitation, most studies have focused on a single sample. Therefore, it is important to determine the stability of multiple samples during acoustic levitation. Here, we aim to understand the effect of multiple-sample levitation on levitation stability in acoustic fields. We visualized the oscillatory motion of multiple levitated droplets using a high-speed video camera. To characterize the dynamics of multiple levitating droplets, the oscillation frequency and restoring force coefficients of the levitated samples, which were obtained from the experimental data, were analyzed to quantify the droplet–droplet interaction. The oscillation model of the spring-mass system was compared with the experimental results, and we found that the number of levitating droplets and their position played an important role in the levitation stability of the droplets. Our insights could help us understand the oscillatory behavior of levitated droplets to achieve more stable levitation.
Improvement of Maximum Power Point Tracking Perturb and Observe Algorithm for a Standalone Solar Photovoltaic System

Extraction of maximum power from PV (Photovoltaic) cell is necessary to make the PV system efficient. Maximum power can be achieved by operating the system at MPP (Maximum Power Point) (taking the operating point of PV panel to MPP) and for this purpose MPPT (Maximum Power Point Trackers) are used. There are many tracking algorithms/methods used by these trackers which includes incremental conductance, constant voltage method, constant current method, short circuit current method, PAO (Perturb and Observe) method, and open circuit voltage method but PAO is the mostly used algorithm because it is simple and easy to implement. PAO algorithm has some drawbacks, one is low tracking speed under rapid changing weather conditions and second is oscillations of PV systems operating point around MPP. Little improvement is achieved in past papers regarding these issues. In this paper, a new method named “Decrease and Fix” method is successfully introduced as improvement in PAO algorithm to overcome these issues of tracking speed and oscillations. Decrease and fix method is the first successful attempt with PAO algorithm for stability achievement and speeding up of tracking process in photovoltaic system. Complete standalone photovoltaic system’s model with improved perturb and observe algorithm is simulated in MATLAB Simulink.
Representing the finger-only topology for hand shape recognition

Automatic recognition of hand shapes in a moving image sequence requires the elements of hand tracking, feature extraction and classification. We have developed a robust tracking algorithm and a new hand shape representation technique that characterises the finger-only topology of the hand by adapting an existing technique from speech signal processing. The tracking algorithm determines the centre of the largest convex subset of the hand throughout an image sequence, using a combination of pattern matching and condensation algorithms. A hand shape feature represents the topological formation of the finger-only regions of the hand using a Linear Predictive Coding parameter set called cepstral coefficients. Feature extraction is performed on the polar dimensions of the hand region-of-interest, by tracking the finger-only region and extracting euclidean distances between the finger-only contour and the hand centre, which are then converted into cepstral coefficients. Experiments are conducted using mug-grabbing sequences to recognise 4 different hand shapes. Results demonstrate the robustness of hand tracking on cluttered backgrounds and the effectiveness of the hand shape representation technique on varying hand shapes.
Efficient Two-Stream Network for Online Video Action Segmentation

Temporal action segmentation is a task of predicting frame-level classes of untrimmed long-termed videos. It can be widely used in various applications including customer analysis, data collection, video indexing, and surveillance. Learning good representations from videos such as motion and spatial representation is a critical factor for model performance. Furthermore, the used model should make reliable decisions with low latency for practical use in a resource-constrained environment. However, many works in action segmentation consider just an accuracy using the pre-calculated representations from heavy 3-dimensional(3D) networks. In this paper, we propose a two-stream action segmentation pipeline that can learn motion and spatial information efficiently and operate online. While the temporal stream combines frame-grouping and TSM for capturing short-term dynamics and long-term temporal information at the same time, the spatial stream captures information on color and appearance complementary to representations from the temporal stream. In addition, the results of both the streams are combined by a cross-attention module to provide a desired classification result for the task. Since it can be operated without heavy 3D convolutional neural networks (CNNs), it takes much less memory and computation than conventional 3D-CNN-based methods. Our proposed network using a non-overlapping sliding window achieved segmentation performance on two action segmentation datasets comparable to many recent works that require full temporal resolution and pre-calculated features of 3D CNNs.
A case study of problem-based learning approach in a mathematics online learning course

Online learning has become common since then and has become a necessity during the Covid-19 pandemic. However, online learning is not as simple as converting face-to-face learning to online, therefore preparedness and readiness to produce effective online courses, especially mathematics online courses are urgently needed. Student engagement is one of the issues that need to be addressed in online learning, in order for students to stay motivated, participated and completed the course. Besides, problem solving and critical thinking skills are the important skills for students to develop, especially in mathematics related course. Both skills are also part of the 21st century skills and have been emphasized in Malaysia Education Blueprint 2013-2025. The problem-based learning (PBL) approach has been selected in this study as many studies have shown that PBL could enhance students' learning in terms of their abilities and skills in applying knowledge, problem solving, practicing higher order thinking and self-directing and reflecting their own learning. Under the PBL approach, students are responsible for their learning whereas teachers are responsible to facilitate students learning. In this study, the quasi-experimental research design has been applied to investigate the effectiveness of PBL approach on student performance in a mathematics online course, which has been implemented via Blackboard. Besides, the quantitative research using correlation analysis and t-test have been used to study the relationship of student engagement with student performance, as well as the effect of age and gender of students on both dimensions. We concluded that the PBL approach has significant impact on student performance in our study. We also concluded that the age and gender of student has significant impact on their class attendance, but no significant relationship can be obtained in terms of the Blackboard clicks and performance. Some recommendations are provided for future studies. © 2022 Author(s).
Mechanism of the Huangguoshu waterfall forest environment’s promotive effect on human health in Guizhou, China

Background The aim of this study was to investigate the specific mechanisms underlying the human health-promoting effects of the forest environment at Huangguoshu Falls, Guizhou, China. Methods Ninety-five participants were recruited and an eye tracker was used to record fixation and sweep indices. A questionnaire was also used to evaluate the effects of different subject environments on human emotions, perceived recovery and preferences. Thereafter, 24 participants with chronic fatigue syndrome (CFS) were recruited and the participants’ fatigue and stress-related scale indices and inflammatory factor levels were examined. Serum metabolites of the participants under different time waterfall forest interventions were detected by ultra performance liquid chromatography-quadrupole-time of flight mass spectrometry (UHPLC-Q/TOF-MS). Results Eye tracking paradigm analysis showed that the “waterfall” element was the most interesting element for participants and that the “charm” of the waterfall forest environment could be well perceived by participants. Scores on the Fatigue Scale, Anxiety Scale and Depression Scale decreased as the duration of treatment in the waterfall forest environment increased. Levels of inflammatory factors decreased after treatment in the waterfall forest environment. At the same time the level of antioxidants, represented by L-ascorbic acid, increased significantly. Conclusions The charm of the Huangguoshu waterfall scenery could be perceived by the participants and have a positive modulating effect on mood and cognitive function. In addition, the unique mixture of negative oxygen ions in this environment can increase the content of endogenous antioxidants and balance the metabolism of choline and amino acids.
Decentralized Robust Frequency Regulation of Multi-terminal HVDC-linked Grids

This paper proposes a new strategy for optimal grid frequency regulation (FR) in an interconnected power system where regional ac grids and an offshore wind farm are linked via a multi-terminal high voltage direct-current (MTDC) network. In the proposed strategy, decentralized H∞ controllers are developed to coordinate the operations of synchronous generators and MTDC converters, thus achieving optimal power sharing of interconnected ac grids and minimizing frequency deviations in each grid. To develop the controllers, robust optimization problems are formulated and solved using a dynamic model of the hybrid MTDC-linked grids with model parameter uncertainty and decentralized control inputs and outputs. The model orders of the controllers are then reduced using a balanced truncation algorithm to eliminate unobservable and uncontrollable state variables while preserving their dominant response characteris- tics. Sensitivity and eigenvalue analyses are conducted focusing on the effects of grid measurements, parameter uncertainty levels, and communication time delays. Comparative case studies are also carried out to verify that the proposed strategy improves the effectiveness, stability, and robustness of real-time FR in MTDC-linked grids under various conditions.
Development a novel multiepitope DNA vaccine against human SARS coronavirus-2: an immunoinformatic designing study

Human SARS coronavirus 2 (SARS-CoV-2) causes the current global COVID-19 pandemic. The production of an efficient vaccine against COVID-19 is under heavy investigation. In this study, we have designed a novel multiepitope DNA vaccine against SARS-CoV-2 using reverse vaccinology and DNA vaccine approaches. Applying these strategies led to reduce the time and costs of vaccine development and also improve the immune protective characteristics of the vaccine. For this purpose, epitopes of nucleocapsid, membrane glycoprotein, and ORF8 proteins of SARS-CoV-2 chose as targets for B and T-cell receptors. Accordingly, DNA sequences of selected epitopes have optimized for protein expression in the eukaryotic system. To this end, the Kozak and tissue plasminogen activator sequences were added into the epitope sequences for proper protein expression and secretion, respectively. Furthermore, interleukin-2 and beta-defensin 1 preproprotein sequences were incorporated to the designed DNA vaccine as an adjuvant. Modeling and refinement of fused protein composed of SARS-CoV-2 multiepitope antigens (fuspMA) have performed based on homology modeling of orthologous peptides, then constructed 3D model of fuspMA was more investigated during 50 ns of molecular dynamics simulation. Further bioinformatics predictions demonstrated that fuspMA is a stable protein with acceptable antigenic features and no allergenicity or toxicity characteristics. Finally, the affinity of fuspMA to the MHC I and II and TLRs molecules validated by the molecular docking procedure. In conclusion, it seems the designed multiepitope DNA vaccine could have a chance to be introduced as an efficient vaccine against COVID-19 after more in vivo evaluations.
No cutoff for circulants: an elementary proof

We give an elementary proof of a result due to Diaconis and Saloff-Coste (1994) that families of symmetric simple random walks on Cayley graphs of abelian groups with a bound on the number of generators never have sharp cutoff. Here convergence to the stationary distribution is measured in the total variation norm. This is a situation of bounded degree and no expansion; sharp cutoff (or the cutoff phenomenon) has been shown to occur in families such as random walks on a hypercube (Diaco-nis, 1996) in which the degree is unbounded as well as on a random regular graph where the degree is ﬁxed, but there is expansion (Diaconis and Saloff-Coste, 1993).
Design and optimisation of a novel asymmetric rotor structure for a PM‐assisted synchronous reluctance machine

This study proposes a novel asymmetric rotor structure with tuning-fork flux barriers for a permanent magnet (PM)-assisted synchronous reluctance machine (PMA-SynRM) to improve the torque characteristics. The proposed asymmetrical rotor structure can effectively decrease the flux leakage inside the rotor, as well as ensure the maximum values of the magnetic torque and the reluctance torque are near the same current phase angle as each other to achieve better utility. To realise this, the frozen permeability method is implemented to separate the total torque into the reluctance torque and the magnetic torque via a two-dimensional finite-element method – JMAG-Designer. To achieve the optimal torque characteristics in the proposed model, the Kriging method and a genetic algorithm are used for getting the optimised model. The contribution of this investigation into motor performance is validated by comparing the proposed model with a conventional PMA-SynRM with a symmetric rotor structure. Beyond that, all machine models are the same size, have the same number of magnets and are operated under the same conditions. A prototype of the proposed model is experimentally verified, i.e. the simulation results agree with the experimental results.
Solving the inverse problem for artificial irregularity diagnostics from extraordinary wave anomalous attenuation data

The paper presents formulation and solution for the problem of determination of spatial spectrum of artificial ionospheric irregularities from vertical HF radio sounding data on anomalous attenuation. The suggested method uses the dependence of extraordinary wave attenuation caused by multiple scattering from the irregularities on frequency to obtain the spectrum parameters. The method is applied to the data obtained in experiments with Sura heating facility carried out on September 6-9, 1999.
IMPLEMENTASI MODEL PEMBELAJARAN PROBLEM BASED LEARNING (PBL) BERBASIS LESSON STUDY UNTUK MENINGKATKAN KETERAMPILAN KOMUNIKASI DAN KOLABORASI MAHASISWA PADA MATA KULIAH PERENCANAAN PEMBELAJARAN DI SD

Dalam pembelajaran abad 21 ini, mahasiswa tidak lagi berpusat pada kemapuan kognitif saja, melainkan yang dibutuhkan keterampilan personal dan sosial. Keterampilan 4C perlu ditingkatkan dan harus dikuasai setiap peserta didik. Keterampilan kolaborasi dan komunikasi sebagai keterampilan dasar yang harus dikuasai pada siswa khususnya sekolah dasar. Hal ini pun juga berlaku bagi mahasiswa PGSD STKIP Bina Insan Mandiri perlu ditingkatkannya komunikasi dan kolaborasi agar nantinya mampu terbiasa untuk bersosialisai dan siap untuk bekerjasama dengan yang lain dalam kehidupan sehari-hari. Keterampilan komunikasi juga perlu ditingkatkan agar mahasiswa dapat menyampaikan ide/gagasan secara tepat dan cepat sesuai degan ejaan bahasa indonesia (EBI). Adapun tujuan dalam penelitian ini untuk mengetahui tingkat keterampilan komunikasi dan kolaborasi setelah diterapkannya model pembelajaran problem based learning berbasis lesson study. Metode yan digunakan dalam penelitian ini adalaj deskriptif kualitatif. Subyek penelitian ini yaitu mahasiswa semester 5 berjumlah 18 mahasiswa. Teknik pengumpulan data dengan metode observasi. Hasil penelitian menunjukkan rata – rata keterampilan komunikasi pada siklus 1 yaitu 84% dengan kategori baik sedangkan pada siklus 2 yaitu 91% dengan kategori sangat baik hal ini mengalami peningkatan sebasar 7%. Sementara itu, rata-rata hasil keterampilan kolaborasi mahasiswa pada siklus 1 yaitu 77,5% dengan kategori baik sedangkan pada siklus 2 yaitu 87% dengan kategori sangat baik mengalami peningkatan sebasar 9,5%. Dengan mengimplementasikan model pembelajaran Problem Based Learning mampu meningkatkan keteramplan komunikasi dan kolaborasi mahasiswa.
Cloud‐based authentication and key management protocol for advanced metering infrastructure in smart grid

In smart grid networks, the advanced metering infrastructure (AMI) enables sensors and communication networks to measure electricity consumed or generated by users. However, among the challenges to be overcome related to security in the AMI system is resistance to computer attacks, such as impersonation, denial of service, man in the middle, and redirection, which can compromise privacy, confidentiality, and availability of electrical systems. An efficient and effective authentication system is necessary to guarantee the privacy and confidentiality of data without compromising system performance, thus characterizing a challenge (need for a tradeoff between security and performance), which involves limited computing power and bandwidth and a high number of meters to be installed in a certain geographic area. This article introduces a group authentication and key agreement protocol that ensures both confidentiality and privacy of communications and avoids several computer attacks. It showed better communication and computational cost‐based performance compared to other protocols. Automated validation of internet security protocols and applications formally validated it, while security protocol animator tool simulated an intrusion, with good results.
The regulatory effects of Pseudostellaria heterophylla polysaccharide on immune function and gut flora in immunosuppressed mice

Abstract Polysaccharide (PF40) has been recognized as a main bioactive substances in Pseudostellaria heterophylla (Miq.). The current study explored the potential protective effects of PF40 on immune system in mice with cyclophosphamide‐induced immunosuppression. The mice were intragastric administered PF40 at the dosage of 100, 200 or 400 mg/kg once daily for 30 days, On the 24th and 25th day, the additional intraperitoneal injection of PF40 (50 mg/kg) were administered. The results showed that PF40 enhanced the cell‐mediated immunity via improvements in macrophage phagocytosis, splenocyte proliferation, NK cell activity and delayed type hypersensitivity. Equally, it improves humoral immunity through promoting the formation of serum hemolysin. Moreover, PF40 maintain the immune balance of splenic lymphocytes and altered the intestinal physiological status in Cyp‐induced mice. PF40 regulates the intestinal microbiota by restoring the relative abundance of Odoribacter and Mucispirillum and reducing the relative abundance of Sporosarcina, Yaniella, and Jeotgalicoccus in Cyp‐intervened mice. The findings suggested that PF40 might be a promising natural functional foods for reducing chemotherapy‐induced immunosuppression.
OFFLINE OCR ALGORITHM TO DETECT KURDISH/ ARABIC CHARACTERS IN SCANNED DOCUMENT

In this paper, Algorithm named (MRWL) Max Rightmost White Line is proposed to detect Kurdish/ Arabic characters’ segmentation in scanned document (printed document), it works in preprocess and segmentation stages of OCR processes, these two stages are significant parts of OCR and affects the accuracy of algorithm. The MRWL starts to remove text margins around document to reduce processing time, then, scans to find Top Line (TL) and Bottom Line (BL) for each sentence in paragraph which can be used to measure height of characters. Based on TL and BL, the Base Line (BSL) can be detected using horizontally Most Frequency Black Pixel (MFBP) which is useful to find characters’ segmentation (Atallah and Omar, 2008) . Finding TL, BL and BSL of each sentence help to find characters location in document. Six phases involve in algorithm, each phase has its own functionally. The Algorithm is tested with different input documents and the average accurate rate of detected segmentations is recorded as 96.93%.