Miracle-dz/UniFAR-FTUs huggingface dataset:
Critical Factors Controlling Regrowth of Opportunistic Pathogens in Premise Plumbing

Opportunistic pathogens (e.g., Legionella pneumophila, Mycobacterium avium complex, Acanthamoeba polyphaga, Pseudomonas aeruginosa) residing in human-made water systems, particularly premise plumbing, are now the primary source of water-borne disease in developed countries. The prevention and control of opportunistic pathogens is a new challenge in premise plumbing due to the limited knowledge concerning the factors driving their occurrence and regrowth mechanisms, and also the complexity of premise plumbing conditions. The goal of this study is to identify key factors governing occurrence of opportunistic pathogens in drinking water distribution systems, particularly premise plumbing, via field investigations and lab-scale experiments. A molecular survey of three opportunistic pathogens (L. pneumophila, M. avium, P. aeruginosa), related groups (Legionella and mycobacteria) and two amoeba hosts (Acanthamoeba spp. and Hartmanella vermiformis) was performed in two real-word chloraminated drinking water distribution systems using quantitative polymerase chain reaction (q-PCR). A high occurrence of Legionella (≥ 69.0%) and mycobacteria (100%), lower occurrence of L. pneumophila (≤ 20%) and M. avium (≤ 33.3%), and rare detection of Pseudomonas aeruginosa (≤ 13.3%) was observed in both systems. Hartmanella vermiformis was more prevalent than Acanthamoeba. Three-minute flushing resulted in reduced gene copies of Legionella, mycobacteria, H. vermiformis and 16S rRNA genes (P<0.05) and distinct microbial community structure in postflushing water, implying strong regrowth potential of opportunistic pathogens in premise pluming.
An institutional perspective in the industry 4.0 scenario: A systematic literature review

Purpose: The growing adoption of Industry 4.0 offers opportunities and promotes changes in markets, business models, supply chains and operations. However, adopting new technologies and practices is beyond the simple rational decision and the search for efficiency. There are contextual social and cultural systems that influence the behavior of people and organizations. Hence, institutional theory can yield interesting insights in the study of Industry 4.0. The purpose of this article is to examine how and to what extent institutional theory has been used to explain Industry 4.0. Design/methodology/approach: A systematic literature review of Industry 4.0 and the broader field of digitalization was performed using Scopus, Web of Science and Google Scholar. The authors analyzed the results using multivariate techniques (Descending Hierarchical Classification and Correspondence Factor Analysis) with the aid of the IRAMUTEQ software.Findings: Results indicate there is little research that uses an institutional perspective to investigate Industry 4.0. Most of them are quantitative and are based on the concept of institutional isomorphism. Qualitative studies, e.g., case studies and the use of theories such as institutional logics and institutional work could generate a richer comprehension of Industry 4.0. Besides, consideration of meso (e.g., organizational fields) and macro (e.g., countries) level of analysis should be more extensively explored.Originality/value: This paper identifies research gaps and points to relevant issues frequently not considered by researchers and practitioners. It reinforces a call for an institutional perspective where the concept of Industry 4.0 can be understood as a rationalized myth. Therefore, the meaning, practices, and consequences of Industry 4.0 implementation are expected to vary across organizations and countries.
Comparative Study on Prefabrication Construction Process

The traditional methods of construction industry have made the appropriate initiative to make a paradigm shift in the prefabrication construction in order to achieve a higher standard and to adapt to the global business trend. This review paper present the challenges faced by the construction industry to integrate the prefabrication construction with the existing traditional method and to make the comparative study among the three countries; United Kingdom, Australia and Malaysia. Malaysia applied industrialised building system (IBS) which is defined as a construction system where components are manufactured at factories on or offsite, transported, and then assembled into a structure with minimum work. IBS involves prefabrication and installation of components at the construction site. While, modern method of construction (MMC) is the term used by the United Kingdom government to describe a number of innovations in house building. However, offsite manufacturing (OSM) is the term used for Australian and UK construction industries. This research studies the pattern of MMC, OSM and IBS to identify the pattern research scholars in the three countries and precast concrete system become popular system. Conversely, to highlight the important role of the government and researcher in educating the construction industry players and to transform the construction industry into a modern and efficient industry
Efficient Sample and Feature Importance Mining in Semi-Supervised EEG Emotion Recognition

Recently, electroencephalogram (EEG)-based emotion recognition has attracted increasing interests in research community. The weak, non-stationary, multi-rhythm and multi-channel properties of EEG data easily cause the extracted EEG samples and features contribute differently in recognizing emotional states. However, existing studies either failed to consider both the issues of sample and feature importance or only considered one of them. In this brief, we propose a new model termed sJSFE (semi-supervised Joint Sample and Feature importance Evaluation) to quantitatively measure the sample and feature importance by self-paced learning and feature self-weighting respectively. Experimental results on the SEED-IV data set show that the emotion recognition performance is greatly improved by mining both the sample and feature importance. Specifically, the average accuracy obtained by sJSFE across the three cross-session recognition tasks is 82.45%, which is respectively 3.72% and 7.21% and 10.47% and 18.82% higher than the results of traditional models. Besides, the feature importance vector depicts that the Gamma frequency band contributes the most, and the brain regions of prefrontal, left/right temporal and (central) parietal lobes correlate more to emotion recognition. The sample importance descriptor shows that continual transitions of video types in consecutive trials might weaken the feature-label consistency of the collected EEG data.
Gene Expression Profile Induced by Two Different Variants of Street Rabies Virus in Mice

Pathogenicity and pathology of rabies virus (RABV) varies according to the variant, but the mechanisms are not completely known. In this study, gene expression profile in brains of mice experimentally infected with RABV isolated from a human case of dog rabies (V2) or vampire bat-acquired rabies (V3) were analyzed. In total, 138 array probes associated with 120 genes were expressed differentially between mice inoculated with V2 and sham-inoculated control mice at day 10 post-inoculation. A single probe corresponding to an unannotated gene was identified in V3 versus control mice. Gene ontology (GO) analysis revealed that all of the genes upregulated in mice inoculated with V2 RABV were involved in the biological process of immune defense against pathogens. Although both variants are considered pathogenic, inoculation by the same conditions generated different gene expression results, which is likely due to differences in pathogenesis between the dog and bat RABV variants. This study demonstrated the global gene expression in experimental infection due to V3 wild-type RABV, from the vampire bat Desmodus rotundus, an important source of infection for humans, domestic animals and wildlife in Latin America.
Deep Scale-Variant Network for Femur Trochanteric Fracture Classification with HP Loss

Achieving automatic classification of femur trochanteric fracture from the edge computing device is of great importance and value for remote diagnosis and treatment. Nevertheless, designing a highly accurate classification model on 31A1/31A2/31A3 fractures from the X-ray is still limited due to the failure of capturing the scale-variant and contextual information. As a result, this paper proposes a deep scale-variant (DSV) network with a hybrid and progressive (HP) loss function to aggregate more influential representations of the fracture regions. More specifically, the DSV network is based on the ResNet and integrated with the designed scale-variant (SV) layer and HP loss, where the SV layer aims to enhance the representation ability to extract the scale-variant features, and HP loss is intended to force the network to condense more contextual clues. Furthermore, to evaluate the effect of the proposed DSV network, we carry out a series of experiments on the real X-ray images for comparison and evaluation, and the experimental results demonstrate that the proposed DSV network could outperform other classification methods on this classification task.
Incidence of Parasites on Frozen Alaska Pollock (Gadus chalcogrammus, Pallas, 1814) Fillets

The presence of parasites in marine fish is a serious problem for the fishing industry in many countries. Some species of parasites can present a risk to consumers. Human health can be compromised by allergic reactions to parasitic antigens (hypersensitivity). The aim of the present study was to report the occurrence of parasite larvae in samples of frozen Alaskan fish fillets. A total of 108 samples of frozen Alaska pollock fish fillet were purchased from commercial establishments in the state of São Paulo Brazil, from July 2017 to November 2019. The parasite search was carried out using the method dissection under transmitted light (candling table) according to AOAC (2005), method 985.12. Only 18 samples (17%), from four different brands, did not present any parasitic form, the others (90 samples) had at least one parasitic form, with the presence of cestodes of the order Trypanorhyncha (found in 73 samples) and nematodes of the Anisakidae family prevailing (found in 57 samples). It was also observed that more than half of the studied samples (76 samples) presented up to 5 parasitic forms in the kilogram rate. The results demonstrate the need for more data regarding the incidence of parasites in fish and their impact on human health, in order to alert the population and health authorities about its dangers, so that preventive and corrective measures are taken in the inspection process of these products, aiming to reduce any possibility of the occurrence of illnesses.
Faktor – Faktor Yang Mempengaruhi Kelemahan Pengendalian Intern Pemerintah Daerah (Studi Kasus Pada Kabupaten / Kota di Provinsi Jawa Tengah Periode 2012-2014)

The purpose of this study is to examine the effect of local revenue (PAD), complexity, size and economic growth on the weakness of internal control. The sample used in this study is 85 district / municipal governments in Central Java in 2012-2014. This research data is secondary data in the form of Summary of Semester Examination Result (IHPS) issued by Financial Supervision Agency (BPK), PDRB data, number of sub-districts and the number of residents obtained from Report of LKPD Examination Result from Audit Board (BPK) Central Java Province . Tests conducted using SPSS software version 20.0. The method used is using classical assumption test and multiple regression analysis, t test, F test, and test of coefficient of determination. The results showed that: (1) Revenue Original Regional no effect on the variable weakness of Internal Control. (2) Complexity has no effect on Internal Control weakness variable. (3) Size does not affect the weakness of Internal Control. (4) Economic growth has an effect on Internal Control weakness variable.
Raising teenage children in disadvantaged neighbourhoods: the experiences and challenges of immigrant mothers in Sweden

ABSTRACT Parenting is arguably the most critical factor in protecting teenagers from problem behaviours, such as delinquency and substance use. For immigrant mothers, however, the ability to care for their children might be negatively affected by challenges related to acculturation and area deprivation. The aim of this study was to raise this issue by examining parenting challenges and needs among immigrant mothers of teenagers living in disadvantaged neighbourhoods in Sweden. Such knowledge is crucial for society to be able to adequately support families in promoting their teenagers well-being. Based on an intersectional framework and qualitative interviews with 14 mothers, four themes related to challenges and needs emerged: structural challenges, cultural transition, psychosocial problems, and social support. The themes were highly intertwined and demonstrated substantial distress among immigrant mothers in relation to their parenting and protecting their children. Mothers’ were, therefore, highly engaged in parenting and expressed a desire and motivation to improve their parenting through social support. The introduction of culturally sensitive parenting support specifically aimed at this marginalized group of parents is encouraged.
ORIENT-31 as the Sakigake “Charging Samurai” Born of IMpower150 but Will MARIPOSA-2 IMPRESS in the “Meiji Modernization” of Post-3G EGFR TKI Progression?

Abstract Tyrosine kinase inhibitors (TKIs) have become the preferred first line therapy for those patients with non-small cell lung cancer (NSCLC) harboring epidermal growth factor receptor (EGFR) mutations. Given superior progression free survival (PFS) and overall survival (OS) when compared to earlier generations, third generation EGFR TKIs have become the first choice therapy in many parts of the world. Even though multiple strategies are in development to target both “on-target” and “off-target” resistance, the continuation of EGFR TKIs at the time of progression remains a controversial topic. This commentary focuses on both the ”classic” clinical trials of IMpower150 and IMPRESS and compares them to the recently reported ORIENT-31 and ongoing MARIPOSA-2 to discuss the future therapeutic strategies in the setting of progression post-third generation EGFR TKIs.
Innovative Strategies to Control Oxidation in Wine

The topic of wine oxidation and the need of innovative strategies to prevent its extent were the subject of this PhD thesis. The complexity of the oxidative chemical reactions occurring in wine during its conservation were highlighted, and multiple analytical approaches were used to provide a more comprehensive understanding of wine oxidation and to plan tailored strategies to avoid its occurrence. The complexity of wine oxidation could be in a simplified manner attributed to the following main factors: wine composition, storage conditions, and oxygen exposure. An integrated theoretical and experimental approach was used, including study of chemical, physical and technological variables involved in wine production and storage. Standard protocols currently used to analyse the wine composition were implemented, if needed, and the lab scale trials were coupled with monitoring real case study along the supply chain. In particular, the effectiveness of plant extracts (tannins) commonly used in oenology was also evaluate in order to better understand their antioxidant properties and to encourage an harmonized regulation of their use in winemaking. The information provided and the scientific approach proposed in this thesis work may be useful in future work aimed to study practical implications and effective strategies to control oxidation in wine.
Seasonal and Longitudinal Variations in Suspended Load Connectivity Between River Channels and Their Margins

Input of organic matter into stream channels is the primary energy source for headwater ecosystems and ultimately carbon to the oceans and hence is an important component of the global carbon cycle. Here, we quantify organic‐rich fine sediment mobilization, transport, and storage in a Strahler fourth‐order stream during individual intermediate‐sized storm events. By combining measurements of fallout radionuclides (FRNs) 7Be and 210Pb and stable water isotopes with a conceptual model of suspended load trapping by channel margins, we find that the channel bed was consistently a source of suspended load to the channel margins. Relative to storage on the channel margins, suspended load export increased through the spring and summer, perhaps related to the in‐channel decomposition of organic debris as indicated by its FRN exposure age and changing bulk δ13C composition. Trapping of suspended load by riparian margins limits sediment transport distances, which, given sufficient discharge to fully suspend the load, is nearly independent of stream discharge for sub‐bankfull discharges. Limited data indicate that the fractional size of the channel margins where trapping occurs decreases with increasing watershed area. Increasing transport length and decreasing fractional margin area with increasing watershed area results in a systematic downstream decoupling of the channel from local terrestrial organic matter exchange. These findings provide a framework for understanding suspended load dynamics in formerly glaciated regions where sediment production and fluxes are generally low and thus the annual input of organic debris is a major component of suspended load budget.
The Online Student Portfolio Implementation at the Faculty of Civil Engineering, Universiti Teknologi MARA, Pulau Pinang Malaysia

A student learning portfolio is a documentation of student work that exhibits a student's effort, learning progress, achievements, and competencies gained during a course or time in university. However, compiling a hardcopy student learning portfolio requires excessive physical resources and space. Therefore, an innovative, creative and economical solution is needed for quality student service. Hence the Faculty of Civil Engineering, Universiti Teknologi MARA, Pulau Pinang, has developed an initiative to implement an online student learning portfolio using the Google Sites online platform. This paper has two main objectives. Firstly, to describe the documentation processes of the online student portfolio implementation, which comprises the students' learning reflection, the cumulative Program Outcomes, (PO) attainment, and the progressive learning performance. Secondly, to evaluate the effectiveness of the implementation of the student learning portfolio using an online platform. 863 students participated and successfully produced the online learning portfolio. The output and feedback received from the participants show that the implementation of the online student portfolio is highly beneficial and effective for both the students and the Faculty management, especially during a pandemic like COVID-19, where an economical solution is required, and the availability of documentation online can be accessed remotely.
Collection channel and production decisions in a closed-loop supply chain with remanufacturing cost disruption

Enterprise risk management (ERM) focuses on managing functions of an entire business, with special attention to supply chain uncertainty. Managing supply chain through effective ERM will mitigate firm exposure to risk in operations and ensure the success of the business. We study collection channel and production decisions in a closed-loop supply chain (CLSC) with one dominant manufacturer and one retailer, from the perspective of both firm profit and system robustness. A robust system is desired as only minimal changes in production plan are necessary when facing disruption, and is valuable for enterprise risk reduction. We find that without disruption the indirect (retailer) collection channel achieves higher profit than that of the direct (manufacturer) channel, which is also true under some disruption cases. However, the direct channel is more robust when facing disruption, and generates more profits for manufacturers when the positive disruption is large. We also find that the revenue-sharing contracts are effective in coordinating members of the CLSC. Finally, we conduct numerical studies to validate the models and derive managerial insights.
Deep 3D Neural Network for Brain Structures Segmentation Using Self-Attention Modules in MRI Images

In recent years, the use of deep learning-based models for developing advanced healthcare systems has been growing due to the results they can achieve. However, the majority of the proposed deep learning-models largely use convolutional and pooling operations, causing a loss in valuable data and focusing on local information. In this paper, we propose a deep learning-based approach that uses global and local features which are of importance in the medical image segmentation process. In order to train the architecture, we used extracted three-dimensional (3D) blocks from the full magnetic resonance image resolution, which were sent through a set of successive convolutional neural network (CNN) layers free of pooling operations to extract local information. Later, we sent the resulting feature maps to successive layers of self-attention modules to obtain the global context, whose output was later dispatched to the decoder pipeline composed mostly of upsampling layers. The model was trained using the Mindboggle-101 dataset. The experimental results showed that the self-attention modules allow segmentation with a higher Mean Dice Score of 0.90 ± 0.036 compared with other UNet-based approaches. The average segmentation time was approximately 0.038 s per brain structure. The proposed model allows tackling the brain structure segmentation task properly. Exploiting the global context that the self-attention modules incorporate allows for more precise and faster segmentation. We segmented 37 brain structures and, to the best of our knowledge, it is the largest number of structures under a 3D approach using attention mechanisms.
Modeling landslide generated waves using the discontinuous finite element method

A new two‐layer model for impulsive wave generation by deformable granular landslides is developed based upon a discontinuous Galerkin finite element discretization. Landslide motion is modeled using a depth‐averaged formulation for a shallow subaerial debris flow, which considers the bed curvature represented by the local slope angle variable and accounts for inter‐granular stresses using Coulomb friction. Wave generation and propagation are simulated with the three‐dimensional non‐hydrostatic coastal ocean model Thetis to accurately capture key features such as wave dispersion. Two different techniques are used in treating wetting and drying (WD) processes during the landslide displacement and wave generation, respectively. For the lower‐layer landslide motion across the dry bed a classical thin‐layer explicit WD method is implemented, while for the resulting free‐surface waves interacted with the moving landslide an implicit WD scheme is utilized to naturally circumvent the artificial pressure gradient problem which may appear in the dynamic interaction between the landslide and water if using the thin‐layer method. The two‐layer model is validated using a suite of test cases, with the resulting good agreement demonstrating its capability in describing both the complex behaviors of granular landslides from initiation to deposition, and the consequent wave generation and propagation.