Miracle-dz/UniFAR-FTUs huggingface dataset:
Experimental and theoretical analysis for the shear capacity of the square rebar reinforced concrete beams during the period of the Republic of China (1912–1949)

Abstract The material properties and bond-slip behaviour of the reinforced concrete beams during the period of the Republic of China (1912–1949) are different from those of modern reinforced concrete beams, so it is necessary to study the calculation method of the shear capacity of this type of beams. First, the material properties of the concrete and the square rebar, the bond-slip behaviour, and the failure mechanism of the beams were obtained in the tests by using square rebar during the period of the Republic of China(ROC) and concrete with the mix proportions of the ROC period. The results show that the ROC beam had a critical crack that propagates to the upper surface of the beam causing the beam failure. Then, a modified arch-truss model was proposed to quantitatively evaluate the relationship between the critical crack propagating process and the shear value, which is in good agreement with the test results. Finally, based on the calculation results of the modified model, a simplified trilinear model was proposed to determine the critical height of diagonal crack propagation in ROC reinforced concrete beams. The research results can provide a scientific basis for the shear capacity calculation and conservation of ROC reinforced concrete beams.
Creating Healthy Organizations

Lowe’s Creating a Healthy Organization is not a step-by-step program for organizational change. He succinctly encapsulated the book’s purpose in the title’s tag line “How Vibrant Work Places Inspire Employees to Achieve Sustainable Success” from the dust jacket. This is an organizational ‘how-to’ book of a different kind. Lowe offers an insightful, evidence-based diagnosis of the kinds of mindset, actions, principles, values, leadership, and culture required to strengthen the connections between people and performance in order to create a healthy organization that is more capable of sustainable success. Furthermore, he offers organizations the opportunity to traverse a different path – a decidedly more holistic, healthy path that requires the co-creation of a corporate culture that leads toward sustained success that benefits all stakeholders and the environment. Inclusive Leadership
Grape Bunch Detection at Different Growth Stages Using Deep Learning Quantized Models

The agricultural sector plays a fundamental role in our society, where it is increasingly important to automate processes, which can generate beneficial impacts in the productivity and quality of products. Perception and computer vision approaches can be fundamental in the implementation of robotics in agriculture. In particular, deep learning can be used for image classification or object detection, endowing machines with the capability to perform operations in the agriculture context. In this work, deep learning was used for the detection of grape bunches in vineyards considering different growth stages: the early stage just after the bloom and the medium stage where the grape bunches present an intermediate development. Two state-of-the-art single-shot multibox models were trained, quantized, and deployed in a low-cost and low-power hardware device, a Tensor Processing Unit. The training input was a novel and publicly available dataset proposed in this work. This dataset contains 1929 images and respective annotations of grape bunches at two different growth stages, captured by different cameras in several illumination conditions. The models were benchmarked and characterized considering the variation of two different parameters: the confidence score and the intersection over union threshold. The results showed that the deployed models could detect grape bunches in images with a medium average precision up to 66.96%. Since this approach uses low resources, a low-cost and low-power hardware device that requires simplified models with 8 bit quantization, the obtained performance was satisfactory. Experiments also demonstrated that the models performed better in identifying grape bunches at the medium growth stage, in comparison with grape bunches present in the vineyard after the bloom, since the second class represents smaller grape bunches, with a color and texture more similar to the surrounding foliage, which complicates their detection.
Effect of Chemistry on Electrodynamics in the Martian Dynamo Region

Electromagnetic interactions between Mars remnant crustal magnetic fields and solar and planetary ions lead to time and space variations of the ionosphere. In this work, we continue the investigations started by Riousset et al. [2013] and address the effect of chemistry on ion populations in the dynamo region, where ion dynamics are driven by collisions while electrons are still mostly magnetized. We adopt a mesoscale model to simulate dynamics of electrons and ions in the upper atmosphere (100–400 km). Our approach focuses on numerical studies using the Martian Multifluid Magnetohydrodynamic (MF-MHD) Model (M). The dynamo is a region which varies in time and space due to the lack of a global planetary intrinsic magnetic field, the location of the remnant crustal fields, and the planetary rotation responsible for day/night transition and subsequent trans-terminator particle transfer. The time scales of atmospheric collisions, gyromotions, and chemical processes are discussed in detail to support the selection of relevant reactions for mesoscale studies of the dynamo regions. Several schemes are available in the referenced literature [e.g., Najib et al., 2011; Brain et al., 2015; Dong et al., 2018], and the chemistry model developed as part of this work is based on Najib et al. [2011]. The improved model more accurately reflects changes in the population of planetary ions, which can alter the dynamo current, thereby also causing perturbations of the magnetic field. The MAVEN mission has shown the importance of ion escape in the Martian atmospheric loss, and previous modeling studies [e.g., Riousset et al., 2014] have shown that electrodynamics in the dynamo region may impact upward transport of ions from this region, supporting the need for further studies. This work shows that the inclusion of chemistry results in substantial changes of ion distributions. Furthermore, differences in the symmetry, strength and
Enhanced Visibility of Subduction Slabs by the Formation of Dense Hydrous Phase A

Phase A (Mg7Si2O8(OH)6) is one of the important dense hydrous magnesium silicates in subducting slab, because it forms after the breakdown of antigorite serpentine and could be the dominant hydrous phase in the upper‐mantle deep slab for the water transportation into deep Earth. In this study, the compressional (P) and shear (S) wave velocities of phase A were measured at simultaneous pressure and temperature conditions up to 11 GPa and 1073 K. Combined with elastic properties of olivine and pyroxenes, we calculate the hydration effect on the velocities of harzburgite lithology in cold subduction zones throughout the depth ranges where phase A is thermodynamically stable. Our calculations suggest that the hydration increases both P‐ and S‐wave velocities of harzburgite; at ∼5 wt% hydration, its seismic detectability is enhanced by 1%–1.5% in velocity contrasts relative to its anhydrous counterpart.
Development and Psychometric Evaluation of "Caregiver Burden Questionnaire for Family Caregivers of Patients Undergoing Hemodialysis": A Protocol for A Sequential Exploratory Mixed-Method Study

Objective: Caregiver burden is defined as the physical, financial, mental, and social problems stemmed from providing care for one of the family members who is involved with a medical problem. The precise measurement of caregiver burden is crucial, and it is essential to have an appropriate and specific tool for measuring caregiver burden. This study will be carried out using sequential exploratory mixed-method design with the aim of development and psychometric evaluation of a questionnaire for caregiver burden in family caregivers of hemodialysis patients. Method : The study will be done in 2 phases: 1. qualitative study and literature review, and 2. designing and psychometric evaluation of the questionnaire. In the qualitative phase, family caregivers of hemodialysis patients, patients, nurses, physicians, and social workers will be selected using the maximum variation purposive sampling method. Data will be gathered through semi-structured interviews using a combination of the questions derived from the model and open-ended questions and will be analyzed using directed content analysis. The literature review will be carried out based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses to improve the reporting of the systematic review. After developing the primary item pool, in the quantitative phase, the psychometric properties of the questionnaire will be evaluated. In this regard, face, content, and construct validity (exploratory factor analysis), internal consistency (Alpha’s Cronbach), reliability (test-retest), responsiveness, interpretability, and feasibility of the questionnaire will be assessed. Results: The primary questionnaire will be developed based on the qualitative and systematic literature review; then, its psychometric properties will be assessed in the second phase. The result section will consist of the findings of these two phases. Conclusion: It seems that a specific questionnaire could be a facilitator of identifying and measuring the actual caregiver burden.
Survey of Deep Representation Learning for Speech Emotion Recognition

Traditionally, speech emotion recognition (SER) research has relied on manually handcrafted acoustic features using feature engineering. However, the design of handcrafted features for complex SER tasks requires significant manual effort, which impedes generalisability and slows the pace of innovation. This has motivated the adoption of representation learning techniques that can automatically learn an intermediate representation of the input signal without any manual feature engineering. Representation learning has led to improved SER performance and enabled rapid innovation. Its effectiveness has further increased with advances in deep learning (DL), which has facilitated deep representation learning where hierarchical representations are automatically learned in a data-driven manner. This article presents the first comprehensive survey on the important topic of deep representation learning for SER. We highlight various techniques, related challenges and identify important future areas of research. Our survey bridges the gap in the literature since existing surveys either focus on SER with hand-engineered features or representation learning in the general setting without focusing on SER.
Anti‐disturbance inverse optimal control for systems with disturbances

Inverse optimal control is a widely used technique for solving various optimal problems arising in the controlled system. However, this method becomes inapplicable to optimal problems when the system has disturbances. In this article, we propose a novel anti‐disturbance inverse optimal controller design for a class of high‐dimensional chain structure systems with any disturbances, matched, or mismatched. First, a disturbance observer is employed to get the estimates of the disturbances in the system. Then using backstepping approach, the disturbance estimation is incorporated in the virtual control laws, and consequently a control Lyapunov function (CLF) is obtained. Finally, a composite controller is designed by developing an inverse optimal control method using the obtained CLF function. We show the stability analysis of the anti‐disturbance controller with rigorous proofs, which minimizes an optimal index while the output converges. Moreover, simulation study and analysis for real application to DC–DC buck converters reveal that the proposed composite controller achieves good performance and stabilizes the system with disturbances.
Asymmetric Volatility Relevance in Risk Management: An Empirical Analysis using Stock Index Futures

The objective of this research work is to show the relevance of asymmetries in estimating volatility. The methodology consists in the application of ARCH-type models and implied volatilities of options (IV) to estimate Value-at-Risk (VaR). These for a portfolio of stock index futures for various time horizons. The empirical analysis is carried out for the futures contracts for the Standard and Poors 500 and Mexican Stock Exchange Indices. According to the results, the IV model is superior in terms of precision compared to the ARCH-type models. It is recommended to use the relevant statistical gains when asymmetries are included with respect to when asymmetries are not used. The referred gains range from 4 to 150 basis points of minimum capital risk requirements. The originality of the present work consists of showing the importance of considering the asymmetric effects with IV and ARCH-type models in volatility forecasts within risk management analysis. It is concluded that the methodology means gains in monetary terms.
Structural studies of the DNA partitioning protein IncC from the plasmid RK2

Plasmid DNA partitioning is a crucial process for the transfer of at least a single copy of plasmid to the daughter cells during bacterial cell division. Partitioning for various low-copy number plasmids involves a DNA-binding protein (ParB), a centromere-like DNA site ( parS) and a ParA-family protein. Interestingly, the RK2 plasmid encodes two ParA proteins of different lengths. The longer protein is IncC1 (364 a.a), while IncC2 lacks a N- terminal domain of 105 amino acids (IncC NTD). The secondary structure of IncC NTD by NMR spectroscopy and other biophysical methods has been determined as random coil. It appears to bind DNA weakly and non-specifically. The expression and purification of IncC1 and IncC2 proteins was optimized. The two proteins and IncC NTD were characterized using various biophysical methods including Circular Dichroism, Analytical Ultracentrifugation, Small Angle X-ray Scattering, Size Exclusion Chromatography-Multi Angle Light Scattering, and EMSAs. Bacterial two hybrid assays and chemical crosslinking showed the two IncC proteins form homo- and hetero-dimers and interact with KorB protein. IncC1 and IncC2 proteins bind to DNA, non-specifically. IncC1 binds DNA weakly in the absence of nucleotides but IncC2 protein was found to bind DNA only in the presence of nucleotides (ADP, ATP).
Meningkatkan keterampilan sosial pasien skizofrenia katatonik melalui social skill training

Social interaction in people with schizophrenia is a serious problem, because if it is not treated it will make the situation worse. This case study aims to improve social skills in people with schizophrenia using Social Skills Training. Psychological assessment using interviews, observation, Wechsler Adult Intelligence Scale (WAIS), Graphic Test, and Sack’s Sentence Completion Test (SSCT). The subject is 18 year old male. The results of the intervention showchanges in the form of being able to say hello, introduce yourself ﬁrst, interact with people around, and the subject is no longer in the room often.
Impact of Learning Motivation on Students’ Academic Achievement: Mediating Role of Constructive Feedback

The study aimed to find out the impact of learning motivation after the intervention of constructive feedback on students’ academic achievement. A true-experimental research with randomization pretest-posttest control group design was used in the study. The study sample comprised 97 students of grade IX that was selected purposively. The chemistry achievement test was used to measure the academic achievement. Learning motivation in the Chemistry questionnaire was used to measure learning motivation. Both the instruments were administered twice, as pretest and posttest before and after the intervention. Overall learning motivation through constructive feedback was found a significant impact on students’ academic achievement. Students’ task-value was found as the best predictor of students’ academic achievement, whereas the students’ self-efficacy and students’ self-regulation also showed significant impact on students’ academic achievement in Chemistry subject. It is recommended that constructive feedback should be incorporated in daily formative assessment practices in the classroom setting.
Induction Heating of Thermoplastic Materials by Particulate Heating Promoters

Induction heating is a fast and selective heating method, which can also be applied to polymeric materials, even though these materials do not offer the required electrical or ferromagnetic properties. To compensate for this deficiency, polymeric matrixes (high density polyethylene and polyamide 6) were compounded with various ferromagnetic and electrically conductive particles. The experimental series included induction heating experiments of compounds with different particle materials and variable filler grades at two distinct frequency levels (430 kHz and 2500 kHz). A mechanical characterization of the compounds was performed to identify the influence of the particles on matrix properties. The heating experiments showed a significant temperature rise of the particle doped materials, when they were exposed to an alternating magnetic field. The temperature rise was observed with plates as well as with pellets. The heating effect was found to be dependent on the frequency and the particle material. The best results were obtained from ferromagnetic particles like iron and magnetite, whereas for example non-ferromagnetic carbon black could only be activated in pellet-shape at high magnetic field strength. To reach the melting temperature of the polymer within a maximum time frame of three minutes, the filler content of specific particles could be as low as 5 wt. %. The mechanical properties of the materials, such as tensile strength and stiffness were influenced only marginally, while the impact strength was reduced by the particles by up to 25%.
Comparative effect of chemical and organic fertilizers on primary metabolite contents of Ocimum bascilicum L. and Majorana hortensis Moench

Organic fertilizers are useful substitutes to inorganic fertilizers which improve the soil quality. In the present work, it was shown that organic fertilizers works better on primary metabolite contents of Ocimum basilicum and Marjorana hortensis than chemical fertilizers. Marjorana plant showed increased primary metabolite content compared to Ocimum plant under the treatment of organic fertilizers, but there was significant difference between the two plants indicating organic fertilizers were better. It concludes in general that applying organic fertilizers to the plants is an ecofriendly technique to improve the yield and quantity of the plants.
miR-155 regulates pro- and anti-inflammatory cytokine expression in human monocytes during chronic hepatitis C virus infection

Background Hepatitis C virus (HCV) dysregulates innate and adaptive immune responses while monocytes (M) play a crucial role in linking innate and adaptive immunity to control viral infection. A transcription factor T-bet is upregulated to dampen M functions via the c-Jun N-terminal kinase (JNK) pathway, followed by enhanced Tim-3 expression in chronic HCV infection. However, the molecular mechanisms that control the expression in M are yet unknown. miR-155 has been implicated as a key regulator controlling diverse biological processes through posttranscriptional repression, but the influences of miR-155 on these regulators and effectors still need to be studied. Methods Forty HCV-infected patients and 40 healthy subjects (HS) were recruited, THP-1 cells (human acute monocyte leukemia cell line) were cultured with HCV-infected Huh 7.5 cells. The expression levels of miR-155 and JNK1/JNK2/JNK3 were measured by real-time RT-PCR. IL-10/IL-12 was detected by flow cytometry. THP-1 cells were transfected with mimics-155 and negative control, SOCS1, p-STAT1, p65, p-smad, p-p38, and p-JNK were measured by Western blot. TNF-α levels were measured by ELISA. Student’s t-test was used in statistics. Results The study showed that miR-155 was upregulated in CD14+ M in HCV-infected patients compared to healthy subjects (P<0.05). Moreover, the upregulation of miR-155 in CD14+ M from HCV-infected patients induced TNF-α production and JNK gene expression, which, in turn, led to T-bet upregulation. Also, miR-155 upregulation in CD14+ M of HCV-infected patients increased the IL-12 and decreased the IL-10 production. Conclusions The obtained results indicated that miR-155 upregulation in M during HCV infection enhances the activation of TNF-α and JNK pathways, promotes the expression of transcription factor T-bet, and triggers pro- and anti-inflammatory mediators. Together, these data reveal new information regarding the mechanisms of chronic HCV infection.
Consumer Knowledge Sharing Behavior and Consumer Purchase Behavior: Evidence from E-Commerce and Online Retail in Hungary

The twenty-first century has been full of fundamental changes in consumers’ behavior patterns, especially with the use of diverse social media knowledge-sharing platforms. Therefore, companies have highlighted the significance of knowledge sharing and the importance of social network use in purchasing processes. Accordingly, his paper tries to reveal how consumer purchase behavior (CPB) can be affected by consumer knowledge sharing behavior (CKSB) and the moderating role played by value co-creation dimensions, which are citizenship behavior (CB) and participation behavior (PB), within a sustainable e-commerce field. To test our hypotheses deducted from the literature review, we opted for the PLS-SEM method. We also employed other innovative approaches, such as the IPMA matrix, MAICOM test, FIMIX approach, and CTA analysis, to evaluate the outer and inner model. Our statistical population covered individuals living in Hungary with at least one online purchase involvement. We distributed the questionnaire via various online platforms and, finally, 433 completed questionnaires were prepared for analysis. The results showed that CPB, CB, and PB are positively influenced by the CKSB. However, the link between CPB and CB was not confirmed. As for the moderating role of gender, the permutation test was applied to compare male and female groups and see the difference between them. With a focus on CKSB, this study contributes to the success of international marketing strategies to attain higher competitive advantages.