Miracle-dz/UniFAR-FTUs huggingface dataset:
Current Developments of Artificial Intelligence in Digital Pathology and Its Future Clinical Applications in Gastrointestinal Cancers

Simple Summary The rapid development of technology has enabled numerous applications of artificial intelligence (AI), especially in medical science. Histopathological assessment of tissues remains the gold standard for diagnosis of gastrointestinal (GI) cancers for subsequent management. In a traditional anatomical pathology (AP) laboratory, histopathologists are required to manually assess, quantify and classify diseases under a microscope in a semiquantitative or qualitative manner. The conversion of analogue-to-digital pathology is on the rise, conforming with trends toward digitalization. The rapid adoption of digital pathology (DP) is driven by factors such as the worldwide shortage of pathologists and medical technologists, the increasing incidence of cancer and the critical need to improve laboratory efficiency. In this review, we aim to provide a comprehensive summary of algorithms for AI detection and classification of GI cancer. We will also provide critical insight into the application of algorithms for routine care in clinical practice. Abstract The implementation of DP will revolutionize current practice by providing pathologists with additional tools and algorithms to improve workflow. Furthermore, DP will open up opportunities for development of AI-based tools for more precise and reproducible diagnosis through computational pathology. One of the key features of AI is its capability to generate perceptions and recognize patterns beyond the human senses. Thus, the incorporation of AI into DP can reveal additional morphological features and information. At the current rate of AI development and adoption of DP, the interest in computational pathology is expected to rise in tandem. There have already been promising developments related to AI-based solutions in prostate cancer detection; however, in the GI tract, development of more sophisticated algorithms is required to facilitate histological assessment of GI specimens for early and accurate diagnosis. In this review, we aim to provide an overview of the current histological practices in AP laboratories with respect to challenges faced in image preprocessing, present the existing AI-based algorithms, discuss their limitations and present clinical insight with respect to the application of AI in early detection and diagnosis of GI cancer.
Enhancing Co2 Conversion with Plasma Reactors in Series and O2 Removal

In this work, we take a crucial step towards the industrial readiness of plasma-based CO 2 conversion. We present a stepwise method to study plasma reactors in series as a first approach to a recycle flow. By means of this procedure, the CO 2 conversion is enhanced by a factor of 3, demonstrating that a single-pass plasma treatment performs far below the optimal capacity of the reactor. Furthermore, we explore the effect of O 2 in the mixture with our flexible procedure. Addition of O 2 in the mixture has a clear detrimental effect on the conversion, in agreement with other experiments in atmospheric pressure plasmas. O 2 removal is however highly beneficial, demonstrating a conversion per pass that is 1.6 times higher than the standard procedure. Indeed, extracting one of the products prevents recombination reactions. Based on these insights, we discuss opportunities for further improvements, especially in the field of specialised separation techniques.
Political connection status decisions and benefits for firms experiencing financial difficulties in emerging markets

There is relatively little research exploring the benefits of political connection status decisions for firms experiencing financial difficulties in emerging markets. This paper investigates financially distressed firms that benefit from their political connection status in Indonesia. This study uses three measurements of financial distress as the dependent variables: Altman Z-score, negative working capital, and interest coverage ratio. Firm size, profitability, liquidity, leverage, and operating cash flow are independent variables. Quarterly data for the period from 2012 to 2018 from 327 non-financial companies were obtained from the Indonesia Stock Exchange. To analyze the relationship between financially distressed companies and decisions on the status of political connections as supporters or opponents, the random effects probit model (REPM) was used. The results show that firms with political status as opposition to the government have a strong positive correlation with experiencing financial difficulties. Meanwhile, companies with political connections as government supporters have a strong negative correlation. Companies with politically connected status as opposition experience financial difficulties in terms of negative working capital and interest coverage ratios. Then, debt financing was not found to be a significant problem for financially distressed companies with a political support status of the government. There are indications that they have benefited from political connections, such as more accessible debt financing.
Epos – an instrument for the assessment of the ethical position in software development

Abstract Digital technology becomes more powerful, intelligent, pervasive and ubiquitous. Ethical aspects of this development have not yet drawn the appropriate attention of researchers and engineers. This paper presents an instrument that aims at measuring the individual ethical position with regard to the design and development of computer software. The development of the Epos tool was based on two data collections. The data of the first survey (n1 = 147 participants) were used to select items and to determine the factorial structure of the questionnaire. Results show that the Epos instrument reliably assesses peoples’ ethical opinion with respect to five central components: (1) regulation, (2) data privacy, (3) domain specific knowledge, (4) societal responsibility and (5) company responsibility. In the second survey, we determined the stability of the instruments factor structure by assessing a sample of n2 = 196 participants. A confirmatory factor analysis (CFA) supported the initial factor structure. Next steps and further implications are discussed regarding the final version of the questionnaire.
A snapshot review: In vitro characterization of lipid membranes and their applications

Cell membranes are the crucial boundaries of living cells that determine their structure, sustenance, and functioning. In order to understand the functioning of these biological membranes, it is important to determine their structural composition. These biological membranes are complex in nature and hence experimentation on natural membrane systems remains a tedious task. Preparing model membranes that are similar in structure to natural membranes for characterization and study purposes has been in practice for decades and is a work in progress. Artificial membranes ranging from lipid suspension as vesicles to supported lipid membranes are created using various techniques namely self-assembly, vesicles fusion, and Langmuir–Blodgett technique. These biomimetic membrane models are studied using characterization tools such as Calorimetry, Infrared Spectroscopy, Fluorescence Spectroscopy, X-ray scattering, and Neutron scattering. This paper reviews different methods of preparing artificial membrane models and various biophysical techniques to characterize them with deep insights into applications of these membrane models across various fields such as biosensing, drug discovery, and drug delivery.
Storage Procedures, Low Oxygen, and Low Carbon Dioxide Atmospheres on Storage Quality of ‘Golden Delicious’ and ‘Delicious’ Apples

In a 4-year laboratory and commercial study, ‘Golden Delicious’ and ‘Delicious’ apples (Malus domestica Borkh.) stored in 1.0% to 1.5% O2 + 1.0% to 1.9% CO2 at 0° to 0.5°C and 90% to 92% RH for 6 to 10 months maintained a higher firmness and acid level than apples stored in standard commercial atmospheres of 2.5% O2 + 1.0% to 1.5% CO2 at 0°. Fruit stored in 1.0% to 2.5% O2 with a rapid CA procedure were firmer than those with a slow CA procedure. There was no fruit injury or increased alcohol or off-flavor production resulting from the 1.0% to 2.5% O2 + 0.5% to 2.0% CO2 storage atmospheres established by the rapid CA procedure. Reduction of storage CO2 from 2.0% to 0.5% did not affect the firmness of ‘Delicious’ apples kept in 1.0% or 2.5% O2, but appreciably reduced firmness of ‘Golden Delicious’ kept in 2.5% O2 and to a lesser extent in 1.0% O2.
Risk Measurement of the Financial Credit Industry Driven by Data: Based on DAE-LSTM Deep Learning Algorithm

The risk measurement of financial credit industry is an important research issue in the field of financial risk assessment. The design of financial credit risk measurement algorithm can help investors avoid greater risks and obtain higher returns, so as to promote the benign development of financial credit industry. Based on the combined deep learning algorithm, this paper studies the risk measurement of financial and credit industry, and proposes a fusion algorithm of deep auto-encoder (DAE) and Long Short-Term Memory (LSTM) network. The algorithm recombines the value of fixed features by using the unsupervised mechanism of DAE, and extracts non fixed features for measurement combined with the memory characteristics of LSTM network. The experimental results show that: compared with single generalized regression neural network and LSTM network, the average accuracy of DAE-LSTM algorithm is improved by about 6.49% and 3.25% respectively, which has a better application effect in credit risk measurement.
Realistic 5G backhaul

The hype surrounding the 5G mobile networks is well justified in view of the explosive increase in mobile traffic and the inclusion of massive “non-human” users that form the internet of things. Advanced radio features such as network densification, cloud radio access networks (C-RAN), and untapped frequency bands jointly succeed in increasing the radio capacity to accommodate the increasing traffic demand. However, a new challenge has arisen: the backhaul (BH), the transport network that connects radio cells to the core network. The BH needs to expand in a timely fashion to reach the fast spreading small cells. Moreover, the realistic BH solutions are unable to provide the unprecedented 5G performance requirements to every cell. To this end, this research addresses the gap between the 5G stipulated BH characteristics and the available BH capabilities. On the other hand, heterogeneity is a leading trait in 5G networks. First, the RAN is heterogeneous since it comprises different cell types, radio access technologies, and architectures. Second, the BH is composed of a mix of different wired and wireless technologies with different limitations. In addition, 5G users have a broader range of capabilities and requirements than any incumbent mobile network. We exploit this trait and develop a novel scheme, termed User-Centric-BH (UCB). The UCB targets the user association mechanism which is traditionally blind to users’ needs and BH conditions. The UCB builds on the existing concept of cell range extension (CRE) and proposes multiple-offset factors (CREO) whereby each reflects the cell's joint RAN and BH capability with respect to a defined attribute (e.g., throughput, latency, resilience, etc.). In parallel, users associate different weights to different attributes, hence, they can make a user-centric decision. The proposed scheme significantly outperforms the state-of-the-art and unlocks the BH bottleneck by availing existing but misused resources to users in need.
Design and Development of a Multi-Functional Bioinspired Soft Robotic Actuator via Additive Manufacturing

The industrial revolution 4.0 has led to a burst in the development of robotic automation and platforms to increase productivity in the industrial and health domains. Hence, there is a necessity for the design and production of smart and multi-functional tools, which combine several cutting-edge technologies, including additive manufacturing and smart control systems. In the current article, a novel multi-functional biomimetic soft actuator with a pneumatic motion system was designed and fabricated by combining different additive manufacturing techniques. The developed actuator was bioinspired by the natural kinematics, namely the motion mechanism of worms, and was designed to imitate the movement of a human finger. Furthermore, due to its modular design and the ability to adapt the actuator’s external covers depending on the requested task, this actuator is suitable for a wide range of applications, from soft (i.e., fruit grasping) or industrial grippers to medical exoskeletons for patients with mobility difficulties and neurological disorders. In detail, the motion system operates with two pneumatic chambers bonded to each other and fabricated from silicone rubber compounds molded with additively manufactured dies made of polymers. Moreover, the pneumatic system offers multiple-degrees-of-freedom motion and it is capable of bending in the range of −180° to 180°. The overall pneumatic system is protected by external covers made of 3D printed components whose material could be changed from rigid polymer for industrial applications to thermoplastic elastomer for complete soft robotic applications. In addition, these 3D printed parts control the angular range of the actuator in order to avoid the reaching of extreme configurations. Finally, the bio-robotic actuator is electronically controlled by PID controllers and its real-time position is monitored by a one-axis soft flex sensor which is embedded in the actuator’s configuration.
Penerimaan E-Learning Berbasis Moodle dengan Pendekatan Pengembangan Teori Technology Acceptance Model (TAM) pada Konteks Mahasiswa Perguruan Tinggi Keagamaan Islam Negeri

Penelitian ini dilakukan dengan tujuan untuk menguji dan menganalisis faktor yang mempengaruhi penerimaan penggunaan e-learning berbasis moodle dengan menggunakan kerangka pengembangan teori Technology Acceptance Model (TAM). Penelitian menggunakan metode kuantitatif menggunakan data primer yang diperoleh melalui kuesioner. Populasi yang menjadi objek penelitian adalah seluruh mahasiswa jenjang sarjana di Institut Agama Islam Negeri Ponorogo dengan total sampel yang dapat diperoleh yaitu 300 responden. Pengumpulan data dilakukan melalui survey berupa kuesioner yang dibagikan kepada responden melalui google forms. Pengujian dilakukan melalui analisis Structural Equation Model (SEM) dengan menggunakan bantuan software Smart-PLS. Berdasarkan hasil pengujian hipotesis yang diajukan dalam penelitian diperoleh hasil bahwa pengaruh sosial (SI) berpengaruh terhadap persepsi kemudahan (PEOU), persepsi manfaat (PU) dan secara langsung berpengaruh terhadap minat perilaku penggunaan (BI), karakteristik pengajar (IC) berpengaruh terhadap persepsi kemudahan (PEOU dan, persepsi manfaat (PU), kondisi fasilitas berpengaruh terhadap persepsi kemudahan (PEOU). Selain itu penelitian ini juga berhasil membuktikan bahwa persepsi kemudahan (PEOU) berpengaruh terhadap persepsi manfaat (PU) dan minat perilaku penggunaan (BI), persepsi manfaat (PU) berpengaruh terhadap minat perilaku penggunaan (BI). Penelitian ini tidak berhasil menemukan bukti adanya pengaruh dari karakteristik pengajar (IC) terhadap minat perilaku penggunaan (BI), pengaruh kondisi fasilitas (FC) terhadap persepsi kemudahan (PU) dan minat perilaku penggunaan (BI). Namun, seluruh variabel eksternal yang diuji terhadap model TAM ditemukan berpengaruh secara tidak langsung terhadap minat perilaku penggunaan e-learning berbasis moodle oleh mahasiswa IAIN Ponorogo.
CPW slot antenna with Y-shaped central monopole and matching arms

Abstract A coplanar waveguide slot antenna is herein presented. A rectangular slot is excited by a Y-shaped monopole etched on a single FR4 substrate. This structure exhibits two resonances due to the presence of the slot and the central monopole which can be used to design a dual-band or a wideband antenna. A parametric analysis is presented to describe the impedance matching mechanism for the two impedance bandwidths (BWs), as well as for the wideband antenna. The latter is fabricated and provides a measured impedance BW from 2.28 to 3.6 GHz, and gain larger than 2 dBi, yielding an outstanding BW/size trade-off. Finally, a 60 mm × 60 mm back metallic reflector is used to achieve a directive antenna with 6 dBi of measured gain, and an impedance BW from 2.16 to 3.59 GHz.
Adaptive Filtering Based MPPT Tracking of Solar Energy Systems

: A significant improvement in energy utilization can be achieved by using a simple dc–dc converter controlled by an MPPT algorithm, reducing the required size of the PV array for a given power output. The simplest and cheapest MPPT control operates the PV array at a constant voltage equal to its standard test conditions (STC) MPP voltage provided by the manufacturer. This approach ignores the effects of insolation and temperature variations on the MPP voltage. The utilization efficiency can be further improved, at a small increase in implementation cost, by employing a suitable MPPT technique. These are simple algorithms that do not require previous knowledge of the PV generator characteristics or the measurement of solar intensity and cell temperature. The most commonly applied MPPT technique is the PO otherwise the system is perturbed in the opposite direction. However it has some limitations in the initial tracking, as it is slow when the system starts, however after sometime it works well. To improve this, adaptive filter optimization has been proposed which considers the predictive power along with previous and current power parameter. Experimental results show that proposed system shows better performance in terms of initial maximum power point tracking.
A review on topological architecture and design methods of cable-driven mechanism

Research on the cable-driven mechanism has greatly developed with the booming of the robots in the past 30 years, and a range of corresponding theoretical studies have been published on them. The large-scale robot or manipulator with the complex cable-driven mechanism can be reconfigured. However, more theoretical studies are required on their topological architecture design and optimization to achieve this. Therefore, the applied cable-driven architectures and the corresponding theoretical studies are reviewed and summarized here. The parallel, serial, and differential architecture are illustrated, as well as their theories and methods, such as the workspace analysis based on the Jacobian matrix, particle swarm optimization and genetic algorithm, and kinematic design based on the graph theory are described. The features of the architecture and the theory studies are concluded. It is hoped that this study will help with design of future studies.
An overview of concepts for aircraft drag reductions

A current overview of aerodynamic drag reduction concepts which have potential for reducing aircraft fuel consumption is presented. The discussion shows where the greatest percentages of aircraft fuel is burned and what areas have the greatest potential for fuel conservation. The paper deals with aerodynamic improvements and touches only briefly on structural and propulsion improvements. Concepts for reducing pressure drag (i.e., roughness, wave, interference, and separation drag), drag due to lift/induced drag, and skin-friction drag at subsonic and supersonic speeds are emphasized.
Pengaruh Penggunaan Media Animaker Terhadap Hasil Belajar Peserta Didik pada Mata Pelajaran IPS Sekolah Dasar

Penelitian tersebut memiliki tujuan untuk mengetahui pengaruh pada media audio visual ANIMAKER terhadap hasil belajar Ilmu Pengetahuan Sosial (IPS) pada siswa kelas V SDN Pulo Gebang 05 Jakarta Timur. Dasar dari penelitian ini merupakan penggunaan media pembelajaran yang belum positif maka dari itu nilai yang didapat siswa dibawah kriteria ketuntasan minimal (KKM). Penggunaan metode pada penelitian dengan metode quasi experimental design ini dengan Nonequivalent Control Group Design. Pada sampel penelitian terdiri dari 93 siswa, kelas V-A, V-B dan V-C dengan teknik sampel jenuh . Jenis instrument berupa tes pilihan ganda dan angket. Analisis data dengan teknik analisis yaitu statistic memakai SPSS 25.0 dalam tes normalitas, penggunaan rumus uji Kolmogorov-Smirnov, homogenitas, dan uji ANOVA. Hasil penelitian memperoleh terdapat pengaruh positif dari penggunaan media audio visual ANIMAKER dengan meningkatnya hasil belajar IPS. Berdasarkan angket media animaker terdapat pengaruh yang signifikan dengan ftabel > fhitung yaitu 5,380 > 4,18 bahwa H0 ditolak dan H1 diterima menunjukan penerapan serta penggunaan atau implikasi media pembelajaran animaker memberikan peningkatan dalam hasil belajar IPS siswa. Maka dapat disimpulkan bahwa media Animaker cukup efektif dipergunakan dalam pembelajaran IPS untuk meningkatkan hasil belajar IPS siswa kelas 5 SDN Pulo Gebang 05 Jakarta Timur.
A comparative experimental and theoretical study on the structural and optical properties of ZnO synthesized at room temperature using an ultrasonication technique

In the present article we report a comparative experimental and theoretical study on the structural and optical properties of ZnO. First principle calculations were carried out using density functional theory (DFT) to study the electronic structure of ZnO. The direct‐type band gap was found in the ZnO's typical estimated energy band structure in the Brillouin zone path G‐G or in the middle of the Γ k‐point grid. To develop UV/ZnO/O2/H2O2 system for photodegradation of organic contaminants in an aqueous system, zinc oxide (ZnO) nanostructures were synthesized using an ultrasonication process at ambient temperature. To test the photocatalytic activity of synthesized nanostructures, we used phenol red (PR) dye as a test substrate. We found that ZnO nanostructures photo‐degraded PR dye at a rate of over 90% under ultraviolet light irradiation, converting photonic energy into chemical energy (photocatalytic energy conversion) that can be used for water purification. To explore the structural, optical, morphological, and compositional characteristics of synthesized ZnO nanostructures, various techniques including powder X‐ray diffraction, Fourier‐transform infrared spectroscopy, UV‐visible spectroscopy, scanning electron microscopy, and energy dispersive X‐ray spectroscopy were used.
Inhibitors of Ethylene Synthesis and Action: A Comparison of Their Activities in a Lettuce Root Growth Model System

The activity of purported inhibitors of ethylene synthesis and ethylene action was tested in a lettuce (Lactuca sativa L. ‘Grand Rapids’) root growth model system. Ethylene production by lettuce seedlings was inhibited by three purported inhibitors of ACC-synthase: AOA, l-canaline (CAN), and AVG. However, except for AVG, these compounds did not increase root growth, suggesting that the endogenous basal rate of ethylene production did not play a role in controlling the growth of these seedling roots. The promotive effective of AVG on root growth was not due to an inhibition of ethylene production, since it retained its effect in the presence of externally supplied ethylene. Of the five purported inhibitors of ethylene action studied, only NBA and silver thiosulfate (STS) demonstrated anti-ethylene action without toxic side effects. Three other compounds reported to block ethylene action—CO2, DIHB, and MCEB—inhibited growth by themselves and failed to provide clear evidence that they blocked ethylene action in the lettuce root growth assay system. Chemical names used: 1-aminocyclopropane-1-carboxylic acid (ACC); (aminooxy)acetic acid (AOA); [S-(E)]-2-amino-4-(2-aminoethoxy)-3-butanoic acid (AVG); 2,5-norbornadiene (NBA); 3,5-diiodo-4-hydroxybenzoic acid (DIHB); and 5-methyl-7-chloro-4-ethoxycarbonylmethoxy-2,1,3-benzothiadiazole (MCEB).