Miracle-dz/UniFAR-FTUs huggingface dataset:
Basic Consideration of Collaborative Filtering Based on Rough C-Means Clustering

Collaborative filtering (CF) is a technique for realizing recommender systems found in e-commerce sites and video streaming services. Appropriate content recommendations to individual users will improve usability, purchase rates, video ratings, and corporate profits. Clustering is a technique for automatically classifying and summarizing the data by extracting clusters composed of similar objects. Clustering-based CF extracts clusters composed of users with similar interests and preferences, and recommends contents with high preference degree within the cluster. Rough C-means (RCM)-type methods can extract overlapped clusters dealing with the certainty, possibility, and uncertainty of belonging of object to clusters. In this study, we propose two-types of RCM-based CF, namely, GRCM-based CF (GRCM-CF) and $\pi$ GRCM-based CF ($\pi$ GRCM-CF). Furthermore, we verified the recommendation performance of the proposed methods, GRCM-CF and $\pi$ GRCM-CF, through numerical experiments using two real-world datasets, namely, NEEDS-SCAN/PANEL dataset and MovieLens dataset.
Visualizing the Importance of Floor-Plan Image Features in Rent-Prediction Models

This study proposes a rent-prediction model that allows users to understand which parts of a floor-plan image (FPI) significantly affect a rent prediction. Principal Component Analysis (PCA) and Bag of Features (BoF) are used to extract feature vectors from an FPI. The importance of each feature vector, derived from the FPI, is measured and visualized based on 100,000 rental properties sampled from the LIFULL HOME'S dataset. The experimental result suggests that the wall and orientation symbol drawn on an FPI contribute to the rent prediction for both PCA and BoF, although BoF provides a better understanding of which parts of an FPI significantly affect the rent prediction.
Surround Gate Transistor With Epitaxially Grown Si Pillar and Simulation Study on Soft Error and Rowhammer Tolerance for DRAM

A new dynamic random access memory (DRAM) memory cell transistor is fabricated, and its soft-error immunity and rowhammer tolerance are studied. The vertical channel is formed by selective epitaxial growth of silicon pillar, and the surround gate forms a fully depleted (FD) channel, which can suppress floating-body effects, such as hysteresis. A TCAD simulation study compares this device and conventional bulk saddle FinFET in terms of soft error immunity and rowhammer tolerance. The confined channel limits soft error because of its thin channel volume for charge generation due to alpha and neutron particles. The surround gate device is inherently free from rowhammer attack as each silicon body of any memory cell transistor is fully isolated from neighboring word lines.
Supplier Development Program Though Knowledge Sharing Effectiveness: A Mentorship Approach

The market in which firms compete magnifies the need for buying firms to effectively manage and develop their supply chain. One of the important notions in the management and development of the supply chain is the implementation of supplier development program. Previous extensive literature review has identified various types of activity in the supplier development program, which categorized as low involvement activity to high involvement activity. Further, extensive literatures on supplier development program implementation and its implication on supplier’s capability are also available. However, there is still limited empirical research for investigating the determinants of knowledge sharing effectiveness in supplier development programs. Aimed at bridging that gap, this study attempts to investigating the role of supplier’s organizational culture, information and communication technology (ICT), and perceived behavioral control as the determinants of knowledge sharing effectiveness by mentorship in the supplier development program (SD). A survey questionnaire was employed to collect data from 200 suppliers after conducting mentorship training at the suppliers’ site. The data were analyzed using bootstrap resampling method (with 5,000 resamples). The bootstrap samples are used to estimate the Partial Least Square (PLS) path model. The results of path analysis indicated that all variables are significantly associated with knowledge sharing effectiveness with mentoring mechanism (p-values< 0.05) except collaborative culture to knowledge sharing effectiveness which was insignificant. It was also observed that ICT and perceived behavioral control affected the effectiveness of knowledge sharing by mentorship in the SD program.
Fault Detection Using Autoencoder with Linear Hidden Layer Dynamics

This paper presents a novel structure for data-driven fault detection using multi-layer autoencoder whose hidden layer trajectory is embedded into a linear space. The hidden layer is constructed using the view of system behaviour and its trajectories are described by a kernel representation. Fault detection is carried out by monitoring the residue of the hidden layer. The proposed structure has the ability to capture complex nonlinear dynamical features while providing a clear representation for the hidden layer. Simulation studies on continuously stirred reactor (CSTR) is also conducted, which demonstrates that the proposed approach can detect faults effectively while distinguishing between faults and unknown disturbances.
Simulation of Tunable Electrical Circuits Using NI ELVIS II Complex

Tunable passive and active bandpass filters due to their university and flexibility help to simplify designing devices which are applied for various functional purposes. These filters are useful for electronic, information-measuring and control systems, as well as for biomedical, acoustic and hydroacoustic equipment. In this regard, the inclusion of tunable filters in the training course of electrical engineering is very important. The NI ELVIS II complex, applied for measurements, allows studying the characteristics of tunable filters in both the time and frequency domain. The examples of transient processes in tunable passive and active filters of various orders are considered, frequency characteristics obtained with the tools of the NI ELVIS II complex are described.
3D Rapid-Prototyped 21-31-GHz Hollow SIWs for Low-Cost 5G IoT and Robotic Applications

This article presents, for the first time, new design and fabrication techniques for Hollow Substrate Integrated Waveguides (HSIWs), demonstrated in the nominal frequency from 21 to 31 GHz, for use in wireless communication applications such as 5G, IoT and robotics. The design and fabrication techniques introduced in this paper feature: 1) the use of low-cost rapid prototyping additive manufacturing based on polymer jetting (PJ), and 2) the use of commercially available through-substrate copper via transitions. In contrast to the conventional SIW designs and fabrications, this new approach does not rely on through-substrate via fabrication, hence avoiding some difficult manufacturing steps, such as through-substrate etching, via formation and via metallization, which are considered complex and expensive to implement. The 3D printed HSIWs in this article can achieve a propagation loss of lower than 1.56 Np/m (13.55 dB/m), which is considered one of the results with the lowest propagation loss achieved to date, when compared to the state-of-the-art.
Development of a Numerical Simulator for Methane-hydrate Production

Methane gas hydrate which is considered energy source for the next generation has an urgent need to develop reliable numerical simulator for coupled THM phenomena in the porous media, to minimize problems arising during the production and optimize production procedures. International collaborations to improve previous numerical codes are in progress, but they still have mismatch in the predicted value and unstable convergence. In this paper, FEM code for fully coupled THM phenomena is developed to analyze methane hydrate dissociation in the porous media. Coupled partial differential equations are derived from four mass balance equations (methane hydrate, soil, water, and hydrate gas), energy balance equation, and force equilibrium equation. Five main variables (displacement, gas saturation, fluid pressure, temperature, and hydrate saturation) are chosen to give higher numerical convergence through trial combinations of variables, and they can analyze the whole region of a phase change in hydrate bearing porous media. The kinetic model is used to predict dissociation of methane hydrate. Developed THM FEM code is applied to the comparative study on a Masuda’s laboratory experiment for the hydrate production, and verified for the stability and convergence.
LAMINAR FLOW HEAT TRANSFER OF A PSEUDO PLASTIC FLUID THROUGH A DOUBLE PIPE HEAT EXCHANGER

An experimental study was carried out to obtain the mean convective heat transfer coefficient of aqueous carboximethyl cellulose (CMC) solutions in double-pipe heat exchangers. Co-current and counter- flows were considered in the investigation. From the experimental data a Nusselt number was calculated for a wide range of Graetz number, Reynolds number, and CMC concentrations. Increasing the Graetz and Reynolds numbers promote the heat transfer and variation of CMC concentration has a noticeable effect on the Nusselt number.
A viral histone-like protein exploits antagonism between linker histones and HMGB proteins to obstruct the cell cycle

Virus infection necessarily requires redirecting cellular resources towards viral progeny production. Adenovirus encodes the histone-like protein VII that causes catastrophic global reorganization of host chromatin to promote virus infection. Protein VII recruits the family of high mobility group box (HMGB) proteins to chromatin along with the histone chaperone SET. As a consequence of this recruitment, we find that protein VII causes chromatin-depletion of several linker histone H1 isoforms. The relationship between linker histone H1 and the functionally opposite HMGB proteins is critical for higher order chromatin structure. However, the physiological consequences of perturbing this relationship are largely unknown. Here, we employ complementary systems in Saccharomyces cerevisiae and human cells to demonstrate that adenovirus protein VII disrupts the H1-HMGB balance to obstruct the cell cycle. We find that protein VII causes an accumulation of G2/M cells both in yeast and human systems, underscoring the high conservation of this chromatin vulnerability. In contrast, adenovirus E1A and E1B proteins are well-established to override cell cycle regulation and promote transformation of human cells. Strikingly, we find that protein VII obstructs the cell cycle even in the presence of E1A and E1B, suggesting that protein VII-directed cell cycle disruption ensures host resources are directed towards viral proliferation during infection. Together, our results demonstrate that protein VII targets H1-HMGB1 antagonism to obstruct cell cycle progression, revealing an unexpected chromatin vulnerability exploited for viral benefit.
Effects of the selective dopamine D3 receptor antagonist PG01037 on morphine-induced hyperactivity and antinociception in mice

Dopamine D3 receptor (D3R) antagonists have been reported to attenuate the abuse-related effects of opioids in preclinical studies and have therefore garnered interest as novel pharmacotherapeutics for the treatment of opioid use disorder (OUD). However, some disparities among the effects of different D3R antagonists have been observed, most notably in their modulation of the behavioral effects of psychostimulants. For example, pretreatment with the highly-selective D3R antagonist PG01037 enhances the locomotor-activating effects of cocaine, yet other D3R antagonists attenuate this response. It is unclear whether such differences among D3R antagonists may also extend to opioids, partially because PG01037 has not been investigated in this context. The purpose of this study was to assess the impact of PG01037 administration on the locomotor-activating, antinociceptive, and cataleptic effects of morphine in mice. C57Bl/6J mice were pretreated with PG01037 (0 – 10 mg/kg) and tested for 1) locomotor activity induced by acute morphine administration (5.6 – 56 mg/kg), 2) locomotor sensitization following repeated morphine administration (56 mg/kg), 3) antinociception following acute morphine administration (18 mg/kg), and 4) catalepsy following administration of PG01037 alone or in combination with morphine (56 mg/kg). PG01037 attenuated the acute locomotor-activating and antinociceptive effects of morphine, but did not prevent the induction of morphine-induced locomotor sensitization and did not induce catalepsy alone or in combination with morphine. These results suggest that attenuation of opioid-induced hyperactivity is a behavioral effect shared among selective D3R antagonists, lending further support to their investigation as treatments for OUD. However, PG01037 is unlike more D3R-selective antagonists in its attenuation of opioid-induced analgesia.
The relationship between hippocampal-dependent task performance and hippocampal grey matter myelination and iron content

Individual differences in scene imagination, autobiographical memory recall, future thinking and spatial navigation have long been linked with hippocampal structure in healthy people, although evidence for such relationships is, in fact, mixed. Extant studies have predominantly concentrated on hippocampal volume. However, it is now possible to use quantitative neuroimaging techniques to model different properties of tissue microstructure in vivo such as myelination and iron. Previous work has linked such measures with cognitive task performance, particularly in older adults. Here we investigated whether performance on scene imagination, autobiographical memory, future thinking and spatial navigation tasks was associated with hippocampal grey matter myelination or iron content in young, healthy adult participants. Magnetic resonance imaging data were collected using a multi-parameter mapping protocol (0.8 mm isotropic voxels) from a large sample of 217 people with widely-varying cognitive task scores. We found little evidence that hippocampal grey matter myelination or iron content were related to task performance. This was the case using different analysis methods (voxel-based quantification, partial correlations), when whole brain, hippocampal regions of interest, and posterior:anterior hippocampal ratios were examined, and across different participant sub-groups (divided by gender and task performance). Variations in hippocampal grey matter myelin and iron levels may not, therefore, help to explain individual differences in performance on hippocampal-dependent tasks, at least in young, healthy individuals.
Conformational Dynamics of NSP11 Peptide of SARS-CoV-2 Under Membrane Mimetics and Different Solvent Conditions

The intrinsically disordered proteins/regions (IDPs/IDPRs) are known to be responsible for multiple cellular processes and are associated with many chronic diseases. In viruses, the existence of a disordered proteome is also proven and is related to its conformational dynamics inside the host. The SARS-CoV-2 has a large proteome, in which, structure and functions of many proteins are not known yet, along with nsp11. In this study, we have performed extensive experimentation on nsp11. Our results based on the CD spectroscopy gives characteristic disordered spectrum for IDPs. Further, we investigated the conformational behavior of nsp11 in the presence of membrane mimetic environment, α-helix inducer, and natural osmolyte. In the presence of negatively charged and neutral liposomes, nsp11 remains disordered. However, with SDS micelle, it adopted an α-helical conformation, suggesting the helical propensity of nsp11. Finally, we again confirmed the IDP behavior of nsp11 using MD simulations. In future, this conformational dynamic study could help to clarify its functional importance in SARS-CoV-2 infection.
Multimodal multiscale analysis reveals flexible DNA contacts of bacterial nucleoprotein filaments

Gene silencing in bacteria is mediated by chromatin proteins, of which Escherichia coli H-NS is a paradigmatic example. H-NS forms nucleoprotein filaments with either one or two DNA duplexes. However, the overall structures, arrangements of DNA-binding domains (DBDs), positions of DBD–DNA contacts, and determinants of genomic distribution for these linear and bridged filaments are uncertain. To connect H-NS structures that silence genes in vivo with features elucidated in vitro, we developed a multimodal, multiscale analysis that combines a new method for chromatin reconstitution and mapping (Nitro-seq), ChIP-seq, tethered-nuclease mapping of DBD–DNA contacts (TEN-map), ·OH footprinting, molecular dynamics, and bioinformatics. We find that DNA sequence principally governs H-NS-filament location with indistinguishable sequence specificity in bridged or linear forms with or without the H-NS modifiers StpA and Hha, and that DBD–DNA contacts vary in orientation and position with ∼10-bp average spacing. Our results support a hemi-sequestration model of linear-to-bridged filament switching.
Evolutionary and ecological processes influencing chemical defense variation in an aposematic and mimetic Heliconius butterfly

Chemical defences against predators underlie the evolution of aposematic coloration and mimicry, which are classic examples of adaptive evolution. Surprisingly little is known about the roles of ecological and evolutionary processes maintaining defence variation, and how they may feedback to shape the evolutionary dynamics of species. Cyanogenic Heliconius butterflies exhibit diverse warning color patterns and mimicry, thus providing a useful framework for investigating these questions. We studied intraspecific variation in de novo biosynthesized cyanogenic toxicity and its potential ecological and evolutionary sources in wild populations of Heliconius erato along environmental gradients, in common-garden broods and with feeding treatments. Our results demonstrate substantial intraspecific variation, including detectable variation among broods reared in a common garden. The latter estimate suggests considerable evolutionary potential in this trait, although predicting the response to selection is likely complicated due to the observed skewed distribution of toxicity values and the signatures of maternal contributions to the inheritance of toxicity. Larval diet contributed little to toxicity variation. Furthermore, toxicity profiles were similar along steep rainfall and altitudinal gradients, providing little evidence for these factors explaining variation in biosynthesized toxicity in natural populations. In contrast, there were striking differences in the chemical profiles of H. erato from geographically distant populations, implying potential local adaptation in the acquisition mechanisms and levels of defensive compounds. The results highlight the extensive variation and potential for adaptive evolution in defense traits for aposematic and mimetic species, which may contribute to the high diversity often found in these systems.
ISC-FS: An Improved Spectral Clustering with Feature Selection for Defect Prediction

—We notice the lack of historical data with labels always exists in software defect prediction (SDP). Unsupervised learning and cross-project defect prediction (CPDP) have tried to address this problem. However, traditional unsupervised learning always requires manual intervention while CPDP faces the challenge of heterogeneity between different projects. Therefore, this paper proposed a framework called Improved Spectral Clustering with Feature Selection (ISC-FS) to conduct unsupervised learning for defect prediction without human effort in this paper. First, ISC-FS clusters the software entities and gets pseudo-labels. Second, we do a feature selection, of which the key idea is different clusters hold the different magnitude of features. Last, the selected features are fed to a spectral clustering method based on connectivity-distance. To validate the proposed method, experiments were carried out on 28 projects from PROMISE and NASA datasets, and comparisons were made with the other ﬁve unsupervised methods. The results show the promising performance that ISC-FS can outperform referential methods.
Constructing a Test Method to Evaluate Collaborative Cloud Finance Information System

 Abstract —Cloud computing technology can effectively save business costs and facilitate public use without having to buy expensive computer equipment. Cloud computing allows immediate access to critical decision-making information. This paper establishes a test method for solving finance information system (FIS) development problems combining cloud computing technology and the grey situation decision-making (GSDM) model. This method facilitates collaborative FIS systems design performance evaluation and demonstrates the proposed GSDM method effectiveness.
Phytophthora agathidicida: research progress, cultural perspectives and knowledge gaps in the control and management of kauri dieback in New Zealand

R. E. Bradshaw* , S. E. Bellgard , A. Black , B. R. Burns , M. L. Gerth , R. L. McDougal , P. M. Scott, N. W. Waipara , B. S. Weir , N. M. Williams , R. C. Winkworth , T. Ashcroft, E. L. Bradley , P. P. Dijkwel , Y. Guo, R. F. Lacey , C. H. Mesarich , P. Panda and I. J. Horner Bio-Protection Research Centre, School of Fundamental Sciences, Massey University, Palmerston North 4410; Manaaki Whenua – Landcare Research, St Johns, Auckland 1072; Bio-Protection Research Centre, Lincoln University, Lincoln 7647; School of Biological Sciences, The University of Auckland, Private Bag 92019 Auckland, 1142; School of Biological Sciences, Victoria University of Wellington, Wellington 6012; Scion, NZ Forest Research Institute Ltd, Rotorua 3010; NZ Institute for Plant and Food Research, Te Puke 3182; NZ Institute for Plant and Food Research, Mt Albert, Auckland 1025; Kauri Dieback Programme, c/-Ministry for Primary Industries, Ruakura Research Centre, Hamilton; Bio-Protection Research Centre, School of Agriculture and Environment, Massey University, Palmerston North 4410; and NZ Institute for Plant and Food Research, Private Bag 1401, Havelock North 4130, New Zealand
Issues of Innovative Development and Management of Enterprises

In this paper have been discussed issues of innovative development and management of enterprises. Innovative management and increasing the efficiency of production of innovative products and services will ensure economic growth, changes in key macro-microeconomic indicators. Therefore, the study analyzed the double correlation coefficients between the volume of innovative products and services created and key economic indicators. According to the calculations, the volume of innovative products, works and services created has a high correlation with all sectors of the economy.