Miracle-dz/UniFAR-FTUs huggingface dataset:
Green Product Market Development Strategy of Mobile Network Group Buying Community: Based on Three-Party Evolutionary Game and Simulation Analysis

With the advent of the 5G era, the mobile network group buying community dominated by focusing on social relations shows great development potential. However, in the mobile network group buying community, the mixed information makes the information environment of the community more complex. Information asymmetry will lead to “mistakes” in consumers’ choice, making it impossible for some important markets to be fully developed. Considering the gains and losses of three interest subjects—governments, enterprises, and consumers in the green product market under information symmetry, in this paper, an evolutionary game model involving governments, enterprises, and consumers was built. Numerical experiments and simulation were performed using SciPy, a scientific computing library of Python, to study the main factors influencing the healthy development of the green product market. The research results showed under information symmetry, when the governments’ benefit from increased government credibility was higher than the cost of governments for screening the information of enterprises’ products and identifying the green products, the expected fine of enterprises for producing high carbon products was higher than the difference between the actual cost increment and the actual income increment of enterprises for producing green products, and the utility perception of consumers from purchasing green products was higher than the cost of consumers for purchasing green products, the three-party game would evolve to a socially ideal stable state. The above conclusions provide useful policy suggestions for governments to vigorously develop the green product market.
Validity of freehand three-dimensional ultrasound system in measurement of three-dimensional surface shape of shoulder muscles

Freehand three-dimensional ultrasound (3DUS) system is a promising technique for accurately assessing muscle morphology. However, its accuracy has been validated mainly in terms of volume by examining lower limb muscles. This study aimed to validate 3DUS in the measurements of 3D surface shape and volume by comparing them with MRI measurements while ensuring the reproducibility of participant posture by focusing on the shoulder muscles. The supraspinatus, infraspinatus, and posterior deltoid muscles of 10 healthy males were scanned using 3DUS and MRI while secured by an immobilization support customized for each participant. A 3D surface model of each muscle was created from the 3DUS and MRI methods, and the agreement between them was assessed. For the muscle volume, the mean difference between the two models was within −0.51 cm3. For the 3D surface shape, the distances between the closest points of the two models and Dice similarity coefficient were calculated. The results showed that the median surface distance was less than 1.21 mm and Dice similarity coefficient was larger than 0.85. These results suggest that, given the above error is permitted, 3DUS can be used as an alternative to MRI in measuring volume and surface shape, even for the shoulder muscles.
Vereinfachte Vordimensionierung von Wabenträgern

Wabenträger sind schon lange als materialsparende Leichtbauträger im Einsatz und haben früher auch zu entsprechenden Kosteneinsparungen geführt. Mit der Zunahme der Fertigungskosten stehen heute vor allem ästhetische Gründe für den Einsatz von Wabenträgern im Vordergrund. Die neuen Stahlbautabellen C5/05 des Stahlbau Zentrums Schweiz (SZS) [1] enthalten Grundwerte für Wabenträger, die eine einfache Vordimensionierung ermöglichen und somit den Entwurf erleichtern. Der vorliegende Aufsatz erläutert die technischen Grundlagen und gibt Hinweise zur Anwendung der tabellierten Werte.
Dynamic contrast-enhanced magnetic resonance perfusion volumetrics can differentiate tuberculosis of the spine and vertebral malignancy

Background There is considerable overlap in radiologic features of tubercular and malignant spinal lesions on conventional magnetic resonance imaging (MRI). Purpose To evaluate the role of dynamic contrast-enhanced (DCE) MRI perfusion parameters in differentiating vertebral malignancy from spinal tuberculosis. Material and Methods This was a prospective study and we enrolled consecutive patients presenting with a clinical/radiologic evidence of vertebral lesions. DCE-MRI of the spine was performed using 3D volume interpolated breath-hold examination (VIBE) sequence after intravenously injecting 0.1 mmol/kg body weight of gadopentetate dimeglumine. We used Tofts model to calculate DCE parameters that included Ktrans (transfer constant), kep (rate constant), ve (fractional volume of extracellular extravascular space), and iAUC (initial area under the curve). We compared the mean value of each perfusion parameter by type of lesion (tubercular/malignant) at 0.05 significance level and performed receiver operating characteristic curve analysis. Results We could confirm histologic/cytologic diagnosis in 35 of the 45 patients recruited. Of these, 19 were tubercular and 16 were malignant lesions. The mean (± standard deviation) of kep (min−1) was significantly higher (2.89 ± 3.3) in malignant compared to tubercular lesions (0.81 ± 0.19), whereas ve was significantly lower in malignant (0.27 ± 0.13 mL/g) compared to benign lesions (0.47 ± 0.12 mL/g) at 0.05 significance level. kep cutoff of ≥1.17 min−1 had a sensitivity of 93.8% and specificity of 100% with a diagnostic accuracy of 94.4% in detecting malignant disease. Conclusion High kep is the single best predictor of malignant vertebral lesions. We recommend kep cutoff value of ≥1.17 min−1 that has high diagnostic accuracy in identifying malignant lesions.
Research on synchronization technique of the DRM system

To deal with the degradation of the synchronization performance in low SNR condition, a novel DRM (Digital Radio Mondiale) synchronization algorithm is proposed. The proposed algorithm employs cyclic prefix for timing synchronization and fractional frequency offset estimation like conventional methods, but accomplishes frame synchronization and integer frequency offset estimation using time pilot cells and differential coding technologies, which are designed specially for the DRM system. After channel estimation and equalization, frequency pilot cells are used to estimate residue fractional frequency offset and subsequent sample offset as well as fixed phase offset to achieve complete synchronization. Simulation results show that the proposed algorithm can possesses better time and frequency synchronization performance than the conventional method in the multi-path fading channel with low SNR condition.
Proteomic analysis of liver tissue reveals Aeromonas hydrophila infection mediated modulation of host metabolic pathways in Labeo rohita

Aeromonas hydrophila (Ah) is an opportunistic Gram-negative bacterium and a serious global pathogen causing Motile Aeromonas Septicaemia (MAS) in fish and many other vertebrates. The pathogenesis of aeromonas septicaemia is complex and involves multiple perturbed pathways. Molecular analysis of host tissues could be a powerful approach to identify mechanistic and diagnostic immune signatures of disease. We performed a deep proteomic analysis of Labeo rohita liver tissue to examine changes in the host proteome during Ah infection. A total of 2525 proteins were identified of which 158 were found differentially expressed during Ah infection. Functional analysis of significant proteins identified the dysregulation of several metabolic enzymes, antioxidative proteins, cytoskeletal proteins and immune related proteins. Proteomic analysis revealed the alterations in the cellular defence mechanisms including phagolysosomal killing and apoptosis during Ah infection. Our systemic approach revealed the protein dynamics in the host cells to explore the putative biological processes underlying the metabolic reprogramming of the host cells during Ah infection. Our findings paved the way for future research into the role of Toll-like receptors (Tlr3), C-type lectins (Clec4e) and metabolic enzymes in Ah pathogenesis leading towards host directed immunotherapies to tackle the Ah infection in fish. IMPORTANCE Bacterial disease is one of the most serious problems in aquaculture industry. Aeromonas hydrophila (Ah), a Gram-negative bacterium causes motile aeromonas septicaemia (MAS) in fish. Small molecules that target the metabolism of the host have recently emerged as potential treatment possibilities in infectious diseases. However, the ability to develop new therapies is hampered due to lack of knowledge about pathogenesis mechanisms and host-pathogen interactions. Molecular level analysis of host tissues could be helpful in finding mechanistic immunological markers of diseases. We examined alterations in the host proteome during Ah infection in Labeo rohita liver tissue to find cellular proteins and processes affected by Ah infection. Our systemic approach revealed protein dynamics underlying the host cells’ metabolic reprogramming during Ah infection. Our work is an important step towards leveraging host metabolism in targeting the disease by providing a bigger picture on proteome pathology correlation during Ah infection.
A new high frequency, zero-voltage switched, PWM converter

A high-efficiency, high-power-density converter operating at constant frequency and switching at zero voltage is presented. Zero voltage switching (ZVS) conditions are achieved over a broad input voltage and output current range. Continuous power transfer from the input to the output minimizes the output filter requirements, and, by using the integrated magnetics technique, high power density can be achieved. By employing the same configuration as classical pulse width modulation (PWM) topologies, a new family of ZVS-PWM converters can be derived. An experimental 5 V, 100 A converter was designed and built. The converter operates from an input voltage of 200 to 430 VDC, at a 400 kHz switching frequency. <<ETX>>
Linking population dynamics models with empirically derived models through phytoplankton primary production

Abstract There are alternative methods for estimation of phytoplankton primary production (PP) that are fundamentally different in the calculation approach. The process‐oriented PP model is a mechanistic, empirically derived method based on the photosynthesis–light relationships. The population dynamics‐based PP calculation, which is a synthetic method, provides a production estimate based on population dynamics of phytoplankton. These alternative methods were here compared with regard to production estimates and linked to enhance the performance of the existing models of population dynamics applied to a wide variety of lakes worldwide in terms of morphometry, nutrient status, and light environments. Estimates of PP were shown to be sensitive to changes in phytoplankton sinking and zooplankton grazing rates in both methods. Production estimates in the process‐oriented PP model were also sensitive to light‐associated parameters such as day length. Although the production estimated from the population dynamics‐based PP calculation tended to be lower than that from the process‐oriented PP model irrespective of lake morphometry, production estimates calculated from both methods with standard parameterization were comparable when production was estimated on an annual timescale. However, it was also shown that the alternative methods could produce different production estimates when estimated on shorter timescales such as cyanobacterial blooms in summer. Cyanobacteria with low mortality due to grazing and sinking losses have been considered as trophic bottlenecks, but there is increasing evidence that their mortality is, to a considerable extent, due to parasitic pathogens. In the case of cyanobacterial blooms, an addition of parasite‐related loss term (19%–33% of standing stock) resulted in a resolution of the difference in production estimates between the methods. These analyses theoretically support the critical role of parasitism and resolve the bottleneck problem in aquatic ecosystem metabolism.
A Hierarchical Classification System for the Detection of Covid-19 from Chest X-Ray Images

With the ever-increasing cases of the Covid-19 pandemic, it is important to leverage deep learning methods to create tools that can aid in relieving the pressure that is put on the limited resources in most developing countries. In this work, we propose a hierarchical classification system for the classification of Covid-19 from Chest X-Ray (CXR) images following a recent proposal of massive use of this modality instead of CT. The system composed of multiple binary classifiers outperforms a tailor-made multi-class classifier COVID-Net. We also show that using well-known established deep learning frameworks combined with a global attention mechanism outperforms the baseline COVID-Net specifically designed for the classification of Covid-19 from CXR images. Our method shows approximately a 4% improvement in the sensitivity to Covid-19 detection from 91% of COVID-Net to 96%. Using popular networks with the possibility of cross-domain transfer learning ensures that the designing and training times are reduced. Furthermore, well-established frameworks can be faster adapted into an application in clinical practice.
Analyzing TripAdvisor reviews of wine tours: an approach based on text mining and sentiment analysis

Wine packaged tours as a specific aspect of wine tourism have so far been neglected in research, for this reason, the purpose of this study is to study the key elements for the success of the wine tour in Tuscany (Italy), evaluating the points of strength and weakness. ,The study combines approaches of text mining, sentiment analysis and natural language processing, drawing on data from the TripAdvisor platform, obtaining through an automatic procedure 9,616 reviews from 600 tours in the years 2010–2020. ,The authors identified six elements of successful wine tours expressed by research subjects: tour guide; logistical aspects; the quality of the wine; the quality of the food; complementary tourist and recreational activities; the landscape and historic villages. The key strength associated with success was the integration of the leading wine product with food, landscape and historic villages, while the main criticisms were concerned with the organization and planning of the tour. Furthermore, the tour guide also plays a fundamental role in consumer satisfaction. ,The limitations of the method were linked to the origin of the data used. The main one is that TripAdvisor does not allow you to have social and personal information about the tourist who wrote the review; therefore, the methods are substantially complementary to the traditional survey through questionnaires. ,The proposed model can be used both by professionals to improve the quality of their products and by policymakers to promote the territorial development of quality wine-growing areas. ,The proposed model can be useful for policymakers to promote the territorial development of quality wine-growing areas. ,The methodology we tested is easily transferable to many countries and to the authors’ knowledge, for the first time attempts to combine multidimensional scaling, sentiment analysis and natural language processing approaches.
Target Tracking Method in Aerial Video Based on Saliency Fusion

For the problem that when doing target tracking under dynamic background, the object extraction is susceptible to interference. Based on the static and dynamic saliency maps of video sequence, this paper presents a method of feature fusion. By calculating the weight for each of the significant area of the extracted static and dynamic saliency, based on human visual attention mechanism, the weighted comprehensive significant figure is get, so as to determine the status of the target. Several experiments are done by the mathod put forward in this paper and the experimental results show that the algorithm is able to solve the problem of susceptible to interference in target tracking, while ensuring robustness and meeting the real-time and accuracy needed. And the algorithm in this paper not only improves the real-time performance and robustness on the premise of guaranteeing the tracking accu racy, but also gives attribution to the field of target tracking. Keywords-salience;aerial video;target tracking; dynamic background ;biological vision
Fall pipe ROV Trenching Conversion

This version of the thesis only covers the non-confidential part of the report. Tideway, as an offshore contractor, is often involved during the construction of an offshore wind farm to carry out cable burial and/or rock placement operations. The process of burying a cable, by means of a trencher, is until now executed by subcontractors. Tideway considers conducting the cable burial proceedings themselves, rather than hire a subcontractor. The goal of this research is to identify whether it is feasible to integrate burial equipment into the fall pipe ROV of the Flintstone, such that Tideway can carry out both burial and rock placement operations, as separate activities, using a single vessel. A literature study is performed in order to produce a qualitative analysis of the existing jet trenching theory, and revealed that both the relationship between jet-production and total momentum flux of a jet system (Vlasblom, 2003) and the mathematical relationships for moving jets (Yeh et al., 2008), can serve as the basis for a computational model. Furthermore, an overview of the main components of an ROV jet trencher is added to the report. A mathematical model is built in order predict the trench performances on the basis of the available hydraulic power. This model contains three different calculations methods, which are based on the collected theory, and provides a range of achievable burial depth versus ROV transit velocity, within which the actual trench performances are expected.
Egocentric Indoor Localization from Room Layouts and Image Outer Corners

Egocentric indoor localization is an important issue for many in-home smart technologies. Room layouts have been used to characterize indoor scene images by a few typical space configurations defined by boundary lines and junctions, which are mostly detectable or inferable by deep learning methods. In this paper, we study camera pose estimation for egocentric indoor localization from room layouts that is cast as a PnL (Perspective-n-Line) problem. Specifically, image outer corners (IOCs), which are the intersecting points between image borders and room layout boundaries, are introduced to improve PnL optimization by involving additional auxiliary lines in an image. This leads to a new PnL-IOC algorithm where 3D correspondence estimation of IOCs are jointly solved with camera pose optimization in the iterative Gauss-Newton algorithm. Experiment results on both simulated and real images show the advantages of PnL-IOC on the accuracy and robustness of camera pose estimation over the existing PnL methods.
A Signal Processing Method For Extracting Shaft Speed Information From Vibration Signal

In the case of no shaft speed measurement, the effective acquisition of shaft speed information is the premise of speed-related fault feature extraction, so it is necessary to preprocess the vibration signal and extract the shaft speed information from the vibration signal. In this paper, a signal preprocessing method for extracting shaft velocity information from vibration signals is described in detail. Based on the theory of signal processing, this paper summarizes the method of extracting shaft velocity signal without shaft speed measurement, and verifies the effectiveness of relevant theoretical methods and shaft speed extraction accuracy based on practical application cases.
Contamination of drinking water between source and point-of-use in rural households of South Africa and Zimbabwe: implications for monitoring the Millennium Development Goal for water

Aims: To assess contamination of drinking water in rural Zimbabwe and South Africa Methods: We conducted a cohort study of 254 children aged 12-24 months in rural South Africa and Zimbabwe. In dry and wet seasons, we measured water quality, using the indicator organism E. coli, at improved and unimproved sources, in household storage and drinking cups. We also recorded hygiene and socio-economic factors for each household. Results: For improved sources, samples with E. coli counts less than 10 cfu/100ml were as follows: at source: 165 (88%); in household storage 137 (59%); in drinking cups 91 (49%). The corresponding values for unimproved sources were: source 47 (29%); household storage 32 (19%); drinking cups 21 (18%). This significant deterioration in microbial quality of water from improved sources was seen in both countries and both survey rounds. Conclusion: Although improved sources generally delivered ‘safe’ water at the point-of-supply, 12% of source samples were contaminated and as such were ‘unsafe’. Furthermore, in household storage, more than 40% of samples were ‘unsafe’. For monitoring the Millennium Development Goal for water, UNICEF-WHO are assuming an equivalence between ‘improved’ sources and ‘safe’ water. Our findings suggest that this equivalence may be unsound.
Genuine wide-bandgap microcrystalline emitter Si-HBT with enhanced current gain by suppressing homocrystallization

The energy bandgap of microcrystalline silicon ( mu c-Si) emitter prepared by the plasma CVD method for Si-HBTs was investigated. The mu c-Si films directly deposited on c-Si substrates were confirmed to have almost the same energy bandgap as c-Si because of mu c-Si crystallization, resulting in formation of a homojunction. In order to suppress such a homojunction formation, a c-Si surface modification method using an a-SiC thin layer was proposed. The a-SiC layer was confirmed to have the effect of producing an abrupt and uniform heterojunction. A current gain as high as 523 was obtained by using the a-SiC thin layer, which was 24 times larger than that without the a-SiC layer. >
Succinct Graph Structures and Their Applications Spring 2018 Lecture 2 : April 11

The following tool is very useful in many randomized constructions of spanners and related structures. In the most general setting, we are given universe U = {u1, . , un} (e.g., the set of vertices in the graph) and a collection Σ = {S1, . , Sm} of m = poly(n) subsets Si ⊆ U consisting of elements of U (e.g., the neighborhood sets of the vertices). We are in particular interested in the case where each Si ∈ Σ is large, say, has at least ∆ elements (e.g., vertices of degree at least ∆). A subset S ⊆ U is a hitting set for Σ if S ∩ Si 6= ∅ for every Si ∈ Σ. Our goal is to compute a small hitting set for Σ.