Miracle-dz/UniFAR-FTUs huggingface dataset:
Heterogeneity of White Matter Hyperintensities in Cognitively Impaired Patients With Cerebral Small Vessel Disease

Objective Similar white matter hyperintensities (WMH) might have different impact on the cognitive outcomes in patients with cerebral small vessel disease (CSVD). This study is to assess the possible factors related to the heterogeneity of WMH in cognitively impaired patients with CVSD. Methods We analyzed data from a cohort of patients with CVSD who were recruited consecutively from the Beijing Tiantan Hospital from 2015 to 2020. WMH, lacunes, enlarged perivascular space (ePVS), microbleeds and lacunar infarcts were rated on brain MRI. A score of <26 on the Montreal Cognitive Assessment (MoCA) indicated cognitive impairment. A mismatch was defined as the severity of WMH not matching the severity of cognitive dysfunction. Type-1 mismatch was defined as a mild WMH (Fazekas score = 0-1) associated with cognitive impairment, and type-2 mismatch was defined as a severe WMH (Fazekas score = 5-6) associated with normal cognitive function. Ultrasmall superparamagnetic iron oxide (USPIO)-enhanced SWI on 3-Tesla MRI was used to image the penetrating arteries in basal ganglia to explore the underlying mechanism of this mismatch. Multivariable logistic regression was used to analyze the association between the imaging features and cognitive impairment. Results In 156 patients, 118 (75.6%) had cognitive impairment and 37 (23.7%) showed mismatch. Twenty five (16.0%) had type-1 mismatch and 12 (7.7%) had type-2 mismatch. Regression analysis found that WMH, lacunes, microbleeds and total CSVD scores were associated with cognitive impairment and were independent of vascular risk factors. However, lacunes, microbleeds and total CSVD scores were related to the mismatch between WMH and cognitive impairment (p=0.006, 0.005 and 0.0001, respectively). Specially, age and ePVS in basal ganglia were related to type-1 mismatch (p=0.04 and 0.02, respectively); microbleeds and total CSVD scores were related to type-2 mismatch (p=0.01 and 0.03, respectively). Although the severity of WMH was similar, the injury scores of penetrating arteries were significantly different between those with and without cognitive impairment (p=0.04). Conclusions Heterogeneity of WMH was present in cognitively impaired patients with CSVD. Conventional imaging features and injury of penetrating arteries may account for such heterogeneity, which can be a hallmark for early identification and prevention of cognitive impairment.
MEASURING, CHARACTERISATION AND MODELLING OF LOAD DYNAMIC BEHAVIOUR IN A WET OVERFLOWDISCHARGE BALL MILL

Overflow ball mills have found popular application in the ore dressing process for post-primary grinding firstly owing to their ability to produce finer grinds, necessary for efficient mineral liberation and better flotation recovery and secondly due to lower initial capital outlay. However they are inefficient and intensive energy consumers. This trend has been exacerbated in the wake of increased installation of large diameter ball mills to benefit from economies of scale, coupled with diminishing ore quality currently being experienced by mines worldwide. To fully utilise the available mill capacity and achieve optimal performance whilst maintaining energy efficiency for these large devices, closer and more effective control is needed. Satisfaction of this need would result in stability of the entire mineral processing circuit, thereby reducing the overall cost in mineral extraction. Clear and deeper understanding of the in-mill behaviour is fundamental to the realisation of the above objective. This thesis explores several experimental and modelling techniques to obtain deeper understanding of the internal behaviour of an overflow ball mill. A direct load sensor comprising an inductive proximity probe and a conductivity probe installed through the mill shell has been utilised to collect information of the media and slurry dynamic positions inside a laboratory ball mill while a commercial on-line ball and pulp sensor was employed to collect similar information on an industrial overflow ball mill. Useful insights were acquired that can help the design of control strategies for optimal mill performance. Four feature variables, i.e. dynamic media angle, slurry pool angle, conductivity signal amplitude and the slurry pool depth, derived from the sensor signals data were characteristically influenced by changes in mill operational conditions. Therefore the possibility of using these features to predict the associated mill operational variables is feasible. In view of the findings, two multivariate models, one based on the concept of data projection to latent space (PLS) and the other combining PLS and radial basis functions neural networks (RBF) were built and applied to predict the in-mill slurry density and ball load volume. Both models yielded adequate predictions, albeit the hybrid PLS-RBF model displayed marginally better prediction performance. The results are indicative of the available potential
Workforce Planning in Agriculture: Agricultural Education and Capacity Building at the Crossroads

Agriculture is a vital part of the Australian economy and is likely to remain so. Its ongoing viability however depends on having a well-qualified workforce at all levels. Current projections are that the gap between the availability of jobs and the supply of graduates is increasing and must be cause for concern. The viability of the industry depends on continuing the innovation process through research and development but the current support for higher degree students has deteriorated significantly in the last decade to the point of being unattractive to the best students. All sectors of the industry have a vested interest in promoting careers in agriculture in order that their own workforce needs are addressed. The minimalist approach to the promotion of agriculture has allowed a negative image of the industry to be portrayed and the perception created that a career in agriculture is not attractive. The reality is however that there are great opportunities in an industry which is high tech, highly mechanised, involved with international marketing and environmental sustainability. Prospective students need to be properly informed and it is the industry as a whole which is responsible for ensuring that they are.
Determining the Calibration Life of Measuring Devices by Means of Parameter Deviation Function

The paper presents the results obtained by performing an experimental study on specific measuring devices - caliper rules. The study is aimed at determining the calibration life of the measuring devices as a function of the metrological reliability, due to the internal parameter deviation. The experimental study conducted is aimed at determining the calibration life of external caliper rules of 150 mm, with depth rod and with a resolution of 0.05 mm. The experimental data is represented by the measuring errors, obtained for the same nominal size. Data is grouped in samples produced at a certain interval of time, by measuring the same dimension with a set of caliper rules. The conclusion which can be drawn from the research performed on the considered set of caliper rules is that the method for determining the calibration life based on parameter deviation can be used for establishing the appropriate moment for performing the calibration for a specific set of measuring devices. By performing the appropriate program in the case of a set of specific measuring devices, it is possible to test whether the values obtained for the calibration life in each case considered meet the requirements set in the appropriate standards. In the case presented in the paper, the pre-set calibration life proved to be earlier than necessary and the application of this method would reduce the entire costs of the appropriate operation.
The roles of attachment to parents and gender in the relationship between Parental criticism and muscle dysmorphia symptomatology in adolescence

ABSTRACT Adolescents are a population particularly at risk of body dissatisfaction, namely body dysmorphic disorder. The most recent literature has begun to increasingly examine muscularity as a critical element of body image. The drive for muscularity is recognized in both sexes as a risk factor for muscle dysmorphia. The present study aimed to investigate the roles of attachment to parents and gender on the association between parental criticism and muscle dysmorphia symptomatology. This study included 1062 participants (49.9% female) with an average age of 17.44 years (SD = 1.14). Path analysis modeling yielded significant results show that parental criticism appears to predict body dysmorphic concerns via parental alienation in both genders. and in males in particular it is associated with a greater drive for muscularity, in accordance with the male aesthetic model of physical appearance. Limits, future directions for research and practical implications are discussed.
ISO 14000 environmental management system in construction: An examination of its application in Turkey

In recent years, the ISO 14000 environmental management system (EMS) prepared by the International Standards Organization (ISO) has been widely used within all sectors throughout the world. There are some methods needed in order to maintain and develop environmental performance within all sectors, including the construction sector, for the protection of sustainable development and the environment worldwide. ISO 14000 EMS originated from such need. In recent years, an increased interest has also emerged in relation to the use of EMS in the construction sector. However, despite such interest, studies about applications regarding the use of the ISO 14000 EMS by construction firms have not reached the desired level. In this article, the impact of the ISO 14000 EMS on construction firms within Turkey is being reviewed by using the questionnaire survey method. A questionnaire survey study is conducted with 68 individual construction firms, which represent the top category in Turkey and operate in national and i.
Performance of CERES-rice model for prediction of different rice cultivars at Navsari

Filed experiment was conducted during kharif season of 2012 at college farm of Navsari Agricultural University, (Gujarat) to investigate the CERES-Rice model validation for three rice cultivars, viz., V1 - Jaya, V2 - Gurjari and V3 - GNR-2 with three different dates of transplanting, viz., D1- 12 July, 2012, D2- 27 July, 2012 and D3-11 August, 2012 and two nitrogen levels, viz., N1-75 kg/ha and N2-100 kg/ha. The experiment was laid out in a split plot design. The model was subsequently validated against observed data from field experiment. From the response of CERES-Rice model it was found that among the genotypes prediction accuracy for cv. Gurjari at third date of transplanting at 100 kg N level was better in respect to panicle initiation with percent error PE (-4.25%), anthesis (-3.40%) and beginning of grain filling (1.05%). But for physiological maturity stage, cv. GNR-2 was found better at third date of transplanting at same N level with PE (-0.97%) as comparison to other treatments.
Didactics: Peculiarities of Programmed Teaching of a Cartwheel to Boys Aged 14

The purpose of the study was to determine the peculiarities of programmed teaching of a cartwheel to boys aged 14. Material and methods. The study participants were 20 boys aged 14. The children and their parents were fully informed about all the features of the study and gave their consent to participate in the experiment. To solve the tasks set, the following research methods were used: study and analysis of scientific and methodological literature; pedagogical observation, timing of training tasks; pedagogical experiment, methods of mathematical statistics, factor analysis. Results. The analysis of similarities revealed that the program components are interrelated. Series of training tasks I, II and IV are combined into one group and provide conditions for teaching boys aged 14 a cartwheel. Conclusions. As a result of factor analysis, the study obtained a two-factor model of the teaching program where training tasks are closely connected with one another, which indicates their effective selection. Factor models of the teaching program explain 69.371% and 75.394% of the variation of results. The study found that the effectiveness of the program depends on the modes of exercise repetition. The use of the mode of exercise repetition of 6 sets 2 times each with a rest interval of 60 s increases the effectiveness of the proposed program (p <0.05).
Life-cycle costs calculations and green design options. Computer monitors as example

In this paper the application of two life-cycle methods on a 17" Philips-branded monitor are discussed. The two methods are life-cycle costing, for obtaining the complete life-cycle cost profile of the monitor, and the Eco Indicator (a practical life cycle assessment method), for obtaining the environmental profile of the monitor. From a comparison of the results of the two studies it appears that there is a strong positive correspondence between economical and environmental aspects, implying that environmental improvement in the life cycle in many instances will lead to cost savings. The results are so encouraging that further studies are ongoing.
Practical Analysis and Design of a 50:1 Cycloidal Magnetic Gear with Balanced Off-Axis Moments and a High Specific Torque for Lunar Robots

Future space missions require new robotic technologies, such as precision gearboxes capable of achieving speed-reduction ratios in excess of 1000:1, specific torques exceeding 50 N*m/kg, operation in environmental temperatures as low as 40 K, and operation in low-atmosphere or hard vacuum, with high reliability and lifetime. The tribological challenges associated with lengthy missions in harsh space environments may be ameliorated with contactless magnetic gearing solutions. This paper employs an extensive parametric 2-D finite element analysis (FEA) study to optimize the high-torque stage of a two-stage surface permanent magnet radial flux cycloidal magnetic gear train, accounting for the impacts of practical fabrication constraints, which degrade the achievable performance and shift the optimal gear ratio. This paper presents a novel discussion of the internal stress distribution and the reaction forces acting on the structure of the cycloidal magnetic gear. This paper also proposes a rotor with three sections to simultaneously balance the center of mass, radial magnetic forces, and off-axis torques. A proof-of-concept prototype was developed, and the experimental slip torque and specific torque are presented. The specific torque of the prototype discussed in this paper is competitive with commercial mechanical cycloidal-type drives with a similar torque rating.
FIGAN: A Missing Industrial Data Imputation Method Customized for Soft Sensor Application

Missing data is quite common in the industrial field, resulting in problems in downstream applications, as most data driven methods used in these applications rely on complete and high-quality dataset to build a high-quality model. Existing methods deal with missing data individually regardless of its downstream application, treating all variables equally without considering their different roles in the downstream application. This would affect imputation performance for key variables, thus deteriorating the accuracy of the downstream model. A considerable challenge is how to refine the missing data imputation task. In this paper, a new method termed fine-tuned imputation GAN (FIGAN) is designed to achieve customized data imputation for industrial soft sensor. The major contribution of the paper lies in two aspects: 1) different from the original imputation GAN (GAIN) which treats all variables equally, FIGAN is guided by a soft sensor module so as to achieve customized data imputation by performing improved data imputation on quality-related variables. Enhanced accuracy for the final industrial soft sensor would be possible; 2) in addition, since labels of the soft sensor might also have missing data, a soft sensor with pseudo labeling is designed to conquer the problem with data imputation and label prediction being optimized interactively. Case studies on a converter steelmaking process and a penicillin fermentation process show the feasibility of the proposed FIGAN. It is noted that such customized imputation could be readily transferred to other downstream applications with missing data. Note to Practitioners—Industrial data is often incomplete and needs proper treatment. Meanwhile, downstream applications with preprocessed data vary under different industrial scenes. The focus of this study is to develop a customized data imputation method for specific downstream applications such as soft sensing. A fine-tuned imputation GAN is designed with a soft sensor module so as to guide the data imputation for good imputation on key variables of the soft sensor. Considering that missing data exists not only in measurement variables but also in soft sensor labels, a semi-supervised soft sensor is designed to handle missing data in the labels, optimized together with the imputation model. The customized data imputation can thus improve the final performance of the downstream model which is a soft sensor in this work. The customization could be transferred to other applications such as an anomaly detection model as well.
Degradation of benzene, toluene, and xylene with high gaseous hourly space velocity by double dielectric barrier discharge combined with Mn3O4/activated carbon fibers

A novel strategy for the degradation of high gaseous hourly space velocity benzene, toluene, and xylene (BTX) by double dielectric barrier discharge (DDBD) coupled with Mn3O4/ activated carbon fiber (ACF) catalysts was proposed in this work. A series of Mn3O4/ACF catalysts were synthesized using the hydrothermal method and characterized. The results showed that all the prepared catalysts could improve the degradation of BTX in the DDBD system and inhibit the production of ozone. Among the catalysts with different Mn loading, the 5.6%Mn3O4/ACF, with the highest Mn(+3) content (43.2%) and the highest absorbed oxygen content (38.5%), presented the best catalytic performance. In the 5.6% Mn3O4/ACF + DDBD system, the degradation efficiency of benzene, toluene and xylene could reach 49.9%, 79.7% and 97.1%, respectively, with a specific input energy of 400 J l−1. The carbon balance and CO2 selectivity, meanwhile, were 83.3% and 51.1%, respectively. It seemed that Mn(+3) and absorbed oxygen content could be a reference for the catalytic performance of Mn3O4/ACF catalysts. The higher the Mn (III) and absorbed oxygen, the better the catalytic performance of the Mn3O4/ACF catalysts. The organic by-products were identified by chromatography-mass spectrometry, and a possible reaction mechanism of BTX in the DDBD reactor and catalyst surface was proposed based on the composition of organic by-products.
A dynamic adjustment model of saccade lengths in reading for word-spaced orthographies: evidence from simulations and invisible boundary experiments

ABSTRACT Contemporary models of eye movement control in reading assume a discrete target word selection process preceding saccade length computation, while the selection itself is assumed to be driven by word identification processes. However, a potentially more parsimonious, dynamic adjustment view allows both next word length and its content (e.g. orthographic) to modulate saccade length in a continuous manner. Based on a recently proposed center-based saccade length account a new regression model of forward saccade length is introduced and validated in a simulation study. Further, additional simulations and gaze-contingent invisible boundary experiments were used to study the cognitive mechanisms underlying skipping. Overall, the results support the plausibility of dynamic adjustment of saccade length in word-spaced orthographies. In the future, the present regression formula-based computational model will allow a straightforward implementation of influences of current and next word content (visual, orthographic, or contextual) on saccade length computation.
Research on Knowledge Graphs with Concept Lattice Constraints

The application of knowledge graphs has been restricted in some domains, especially the industrial and academic domains. One of the reasons is that they require a high reliability of knowledge, which cannot be satisfied by the existing knowledge graph research. By comparison, traditional knowledge engineering has a high correctness, but low efficiency is an inevitable drawback. Therefore, it is meaningful to organically connect traditional knowledge engineering and knowledge graphs. Therefore, we propose a theory from Attribute Implications to Knowledge Graphs, named AIs-KG, which can construct knowledge graphs based on implications. The theory connects formal concept analysis and knowledge graphs. We firstly analyze the mutual transformation based on the ideas of symmetry with a strict proof among the attribute implication, the formal context and the concept lattice, which forms the closed cycle between the three. Particularly, we propose an Augment algorithm (IFC-A) to generate the Implication Formal Context through the attribute implication, which can make knowledge more complete. Furthermore, we regard ontology as a bridge to realize the transformation from the concept lattice to the knowledge graph through some mapping methods. We conduct our experiments on the attribute implication from the rule base of an animal recognition expert system to prove the feasibility of our algorithms.
Corporate governance and sustainability reporting quality: evidence from Nigeria

Purpose This study aims to examine the association between corporate governance and sustainability reporting quality of listed firms in Nigeria. Design/methodology/approach The authors measure corporate governance using board governance variables (board size, board independence, board gender diversity and board expertise) and audit committee attributes (audit committee size, audit expertise and audit meeting). The authors measured sustainability reporting quality using a scoring system, which ranges between 0 and 4. The highest score is achieved when sustainability reporting is independently assured by an audit firm. The lowest score refers to the absence of sustainability reporting. The study emphasizes 120 listed firms on Nigeria Stock Exchange using the ordered logistic regression technique. Findings The results indicate that board governance variables (board size, board gender diversity and board expertise) and audit committee attributes (audit committee size, audit expertise and audit meeting) are significantly associated with sustainability reporting quality. Additional analysis reveals that external assurance contributes to the quality of sustainability reporting through corporate governance characteristics. Research limitations/implications This study is restricted to a single country. Future studies should consider a cross-country study, which may help to establish a comparative analysis. Likewise, the future study could consider other regression techniques using a continuous measurement of the global reporting initiative in measuring sustainability reporting quality. Practical implications This study’s findings have important implications for policymakers and practitioners, especially the corporate executives and top management. Companies are encouraged to restructure their board to enhance better monitoring and support towards better sustainability reporting. Social implications Disclosure on sustainability reporting helps corporate organizations advance the issues of sustainability both nationally and globally. Originality/value This current study adds to accounting literature by examining how corporate governance contributes to sustainability reporting practices within the Nigerian context. Drawing from the result, the study provides strong interconnectivity between the corporate board and audit committee in driving sustainability reporting quality within an organizational context.