Miracle-dz/UniFAR-FTUs huggingface dataset:
GREEN INFRASTRUCTURE TRANSITIONAL MANAGEMENT SPHERE ANALYSIS OF POLICIES AND REGULATIONS IN KUALA LUMPUR, MALAYSIA

Kuala Lumpur (KL) is experiencing rapid development leading to urban green space fragmentation. Green infrastructure (GI) could be the answer to the fragmented green space issue. Nevertheless, how policies and legislations contribute to the spatial establishment of GI in KL remains unclear. Thus, the policies and regulations governing GI establishment in KL were examined in this study. A total of 77 records associated with policies and regulations that may contribute to GI spatially were reviewed. In order to evaluate the efficacy of the chosen articles, the transition management sphere analysis was applied. The study discovered that Malaysia is still lacking in GI policies and regulations. Furthermore, this study also highlighted different challenges and opportunities during optimising GI implementation in spatial design. The finding can be a reference for future policy and regulation establishment.
Endurance Training Improves GLP-1 Sensitivity and Glucose Tolerance in Overweight Women

Abstract Context and objective Obesity and inactivity are risk factors for developing impaired glucose tolerance characterized by insulin resistance and reduced beta-cell function. The stimulatory effect of glucagon-like peptide 1 (GLP-1) on insulin secretion is also impaired in obese, inactive individuals. The aim of this study was to investigate whether endurance training influences beta-cell sensitivity to GLP-1. Participants and intervention Twenty-four female participants, age 46 ± 2 years, body mass index 32.4 ± 0.9 kg/m2, and maximal oxygen consumption 24.7 ± 0.8 mL/kg/min participated in a 10-week exercise training study. Methods Beta-cell sensitivity to GLP-1 was assessed in a subset of participants (n = 6) during a 120-minute hyperglycemic glucose clamp (8.5 mM) including a 1-hour GLP-1 (7-36 amide) infusion (0.4 pmol/kg/min). Changes in glucose tolerance, body composition, and cardiorespiratory fitness were assessed by oral glucose tolerance tests (OGTTs), dual-energy X-ray absorptiometry scans, magnetic resonance scans, and maximal oxygen consumption (VO2max) tests, respectively. Results The c-peptide response to infusion of GLP-1 increased 28 ± 3% (P < 0.05) toward the end of the hyperglycemic clamp. The insulin response remained unchanged. Training improved glucose tolerance and reduced GLP-1, insulin, and glucagon levels during the OGTTs. Training increased VO2max (from 24.7 ± 0.8 to 27.0 ± 0.7 mL/kg/min; P < 0.05) and reduced visceral fat volume (from 4176 ± 265 to 3888 ± 266 cm3; P < 0.01). Conclusion Along with improved glycemic control, endurance training improved beta-cell sensitivity to GLP-1 in overweight women. The study was deemed not to constitute a clinical trial and was not registered as such.
Quantitative analysis and discrimination of lard in chicken fat using FTIR
spectroscopy and chemometrics for halal authentication

Lard (LD) has a similarity with chicken fat (CF) in terms of physicochemical characteristics especially fatty acid composition and FTIR spectra, therefore, analysis of lard in a binary mixture with CF is challenging. This study aimed to employ FTIR spectra in normal and derivative modes in combination with multivariate calibrations for quantitative analysis of LD and CF in the binary mixture and to discriminate pure LD and LD in the mixture with CF using discriminant analysis (DA). LD and CF were prepared randomly at a certain concentration to be used as calibration and validation sets, respectively. All mixtures were scanned using an FTIR spectrophotometer at 4000-650 cm -1 in absorbance mode. Some wavenumbers, FTIR spectral modes and multivariate calibrations were optimized to provide high accuracy and precision as indicated by the high value of coefficient determination (R2 ) and low values of errors in calibration and validation. The results revealed that FTIR spectra using normal spectra at combined wavenumbers of 3100-2750 and 1500-660 cm-1 with R2 for the relationship between actual and FTIR predicted values of > 0.99 in calibration and validation with an error in calibration of 0.008% and error validation of 0.032%. DA could discriminate LD and LD in the mixture with CF with an accuracy level of 100%. FTIR spectroscopy in combination with chemometrics offered a reliable method for quantitative analysis and discrimination of LD in a binary mixture with CF.
On the symplectic invariance of log Kodaira dimension

Suppose that A and B are symplectomorphic smooth affine varieties. If A is acylic of dimension 2 then B has the same log Kodaira dimension as A. If the dimension of A is 3, has log Kodaira dimension 2 and satisfies some other conditions then B cannot be of log general type. We also show that if A and B are symplectomorphic affine varieties of any dimension then any compactification of A by a projective variety is uniruled if and only if any such compactification of B is uniruled.
Survey and Comparative Study of LoRa-Enabled Simulators for Internet of Things and Wireless Sensor Networks

The Internet of Things (IoT) is one of the most important emerging technologies, spanning a myriad of possible applications, especially with the increasing number and variety of connected devices. Several network simulation tools have been developed with widely varying focuses and used in many research fields. Thus, it is critical to simulate the work of such systems and applications before actual deployment. This paper explores the landscape of available IoT and wireless sensor networks (WSNs) simulators and compares their performance using the Low Power Wide Area Network (LPWAN) communication technology called LoRa (Long Range), which has recently gained a lot of interest. Using a systematic approach, we present a chronological survey of available IoT and WSNs simulation tools. With this, we categorized and content-analyzed published scientific papers in the IoT and WSNs simulation tools research domain by highlighting the simulation tools, study type, scope of study and performance measures of the studies. Next, we present an overview of LoRa/LoRaWAN technology by considering its architecture, transmission parameters, device classes and available simulation tools. Furthermore, we discussed three popular open-source simulation tools/frameworks, namely, NS-3, OMNeT++ (FLoRa) and LoRaSim, for the simulation of LoRa/LoRaWAN networks. Finally, we evaluate their performance in terms of Packet Delivery Ratio (PDR), CPU utilization, memory usage, execution time and the number of collisions.
Cross-spectral human behavior recognition based on deep convolutional networks for global temporal representation

Abstract. The purpose of behavior recognition is to recognize the actions of the human body in action. It plays a great role in surveillance, video recommendation, and human-computer interaction with video. With the rise of neural networks, behavior recognition has also continued to develop and progress and has reached a relatively advanced level. However, behavior recognition is still insufficient in recognizing complex human movements and recognizing videos in different bands. To solve this problem, this paper establishes a convolutional neural network (CNN) cross-spectral human behavior recognition algorithm based on global time domain representation. It adopts the method of time-domain feature extraction, construction of optimized convolutional neural network layers, and global time-domain cross-spectrum construction. It also uses videos from the unified compliance framework (UCF)-sports and UCF-11 datasets for experiments. Experiments show that the algorithm achieves an average accuracy of 90% in the behavior recognition of UCF-sports. It still maintains an average accuracy rate of >90 % in the more complex behavior recognition of UCF-11, and the highest accuracy rate is 93%.
Accurate and Energy-Efficient Bit-Slicing for RRAM-Based Neural Networks

<italic>Computation-in-memory</italic> (CIM) paradigm leverages emerging memory technologies such as resistive random access memories (RRAMs) to process the data within the memory itself. This alleviates the memory-processor bottleneck resulting in much higher hardware efficiency compared to von-Neumann architecture-based conventional hardware. Hence, CIM becomes an attractive alternative for applications like neural networks which require a huge number of data transfer operations in conventional hardware. CIM-based neural networks typically employ bit-slicing scheme which represents a single neural weight using multiple RRAM devices (called slices) to meet the high bit-precision demand. However, such neural networks suffer from significant accuracy degradation due to non-zero G<inline-formula><tex-math notation="LaTeX">$_{\min }$</tex-math></inline-formula> error where a zero weight in the neural network is represented by an RRAM device with a non-zero conductance. This paper proposes an unbalanced bit-slicing scheme to mitigate the impact of non-zero G<inline-formula><tex-math notation="LaTeX">$_{\min }$</tex-math></inline-formula> error. It achieves this by allocating appropriate sensing margins for different slices based on their binary positions. It also tunes the sensing margins to meet the demands of either high accuracy or energy-efficiency. The sensing margin allocation is supported by 2’s complement arithmetic which further reduces the influence of non-zero G<inline-formula><tex-math notation="LaTeX">$_{\min }$</tex-math></inline-formula> error. Simulation results show that our proposed scheme achieves up to 7.3× accuracy and up to 7.8× correct operations per unit energy consumption compared to state-of-the-art.
Outcomes of Allograft Medial Patellofemoral Ligament Reconstruction in Children and Adolescents with Hypermobility

Introduction Medial patellofemoral ligament (MPFL) reconstruction is used to treat patellofemoral instability either in isolation or in combination with other procedures. Use of allograft can preserve native tissue in children and can be advantageous in patients with connective tissue disorders, including ligamentous laxity. There is limited evidence regarding functional outcomes of allograft MPFL reconstruction in children and adolescents. This study aimed to assess the short to mid-term results of allograft MPFL reconstruction in children with hypermobility at a tertiary pediatric orthopedic center. Materials and Methods: We retrospectively reviewed all children and adolescents who had undergone allograft MPFL reconstruction over 4 years. The primary outcome measure was the validated Kujala score for patellofemoral disorders. The secondary outcome measures included complications such as redislocation of the patella needing revision surgery. Patients with hypermobility were quantified using Beighton criteria. Statistical analysis was performed using Graph Pad Prism (V6). Results Between 2012 and 2016, the senior author performed 76 allograft MPFL reconstructions in 57 patients. Nineteen patients had bilateral surgery. The mean age was 14 (7–16) years with a female: male ratio of 3:1. The mean Beighton score was 7. Hypermobility was part of a syndrome in ten patients. The mean follow-up was 3 (1–4) years. Nine patients had trochleoplasty and six patients had tibial tubercle osteotomy, in addition to allograft MPFL reconstruction. These fifteen patients, who had additional procedures, were excluded during the analysis of the outcome measures. The mean Kujala score was 89 (80–100). The overall complication rate was 11% (9/76). These included two patella fractures and seven (9%) patients with recurrent instability needing revision surgery. There was no significant difference in complication rates between syndromic and nonsyndromic patients (P = 0.9). Conclusion Our study shows excellent short to mid-term functional outcomes of allograft MPFL reconstruction in children and adolescents with hypermobility.
Calibration of simulation parameters for wind erosion gas-solid two-phase flow in arid and semiarid soils

ABSTRACT To construct a coupled simulation model of soil wind erosion and two-phase flow in arid and semiarid regions, the proper contact parameters of the soil discrete element simulation model are obtained based on the angle of repose (AoR) calibration test. The coupled simulation model is established by combining computational fluid dynamics. The response value of the wind speed of sand initiation is used to verify the model’s accuracy. Due to the characteristics of arid and semiarid soils, this paper uses the Hertz-Mindlin with JKR contact model in EDEM software to calibrate the soil parameters based on soil physical tests and designs the Plackett-Burman, steepest climb, and Box-Behnken tests according to Design-Expert software to obtain the soil AoR second-order regression. With the AoR of 33.52° as the target, the best combination of parameters is obtained: soil-soil collision recovery of 0.64, soil-steel static friction coefficient of 0.31, JKR surface energy of 3.302 J m-2. Finally, by using calibrated parameters and the threshold wind velocity as the response value, the wind-sand air-solid two-phase flow test is conducted in ANSYS Fluent and EDEM, with the relative error between the starting wind speed recorded by the high-speed camera in the wind tunnel test and the threshold wind velocity shown in the simulation model calculated to be 8.7%, and the calibrated soil parameters met the requirements of the coupled simulation.
Group Decision Making Using Bayesian Network Inference with Qualitative Expert Knowledge

In group decision making, different experts often think about the same problem in quite different ways. They frequently have different opinions for decision making about the same situation. Using a Bayesian network structure for optimizing problems, different experts who work as a group for projects may have different solutions for indentifying the causal relationships among variables in the BN model and quantifying graphical models with numerical probabilities. For example, expert-1 may state that “making a decision in situation A causes situation B and making a decision in situation B causes situation C”. But expert-2 may state that “making a decision in situation B causes situation A and making a decision in situation A causes situation C”. Even in a simple case of decision making, the expert knowledge obtained from different experts is quite different. It is typically not possible to avoid contradictions among different expert’s solutions in group decision making. In this article, we propose a practical framework and a methodology for transforming expert knowledge or final group decision making statements into a set of qualitative statements and probability inequality constraints for inference in a Bayesian Network. First, we need to identify a set of alternatives on which the experts have opinions and then consider the problem of constructing a group preference ranking. If such a group preference ranking can be created, then one could utilize the alternative at the top of the ranked list the alternative preferred by the group. Second, after we obtain the most preferred alternative or statement such as “A causes B and then B causes C” from the group decision making, we propose a formal method to transform knowledge, represented by a set of qualitative statements, into an a priori distribution for Bayesian probabilistic models. The mathematical equation for Bayesian inference is derived based on knowledge obtained from the final group decision statements. The set of model parameters, consistent with the statements, and the distribution of models in the structure-dependent parameter space are presented. We also propose a simplified method for constructing the “a priori” model distribution. Each statement obtained from the experts is used to constrain the model space to the subspace which is consistent with the statement provided. Finally, we present qualitative knowledge models and then show a complete formalism of how to translate a set of qualitative statements into probability inequality constraints. Several cases of Bayesian influence are classified and the probability inequality constraints presented in each case are described. 5
Effectiveness of N-Acetylcysteine on Zinc oxide Nanoparticles-Induced Cardiotoxicity in Adult Albino Rats

Background : Zinc Oxide nanoparticles (ZnO NPs) are broadly utilized in medications, foodstuffs, cosmetics plus toothpastes. Studies have shown that the heart is one of the target organs following oral exposure to ZnO NPs. N-acetylcysteine (NAC) is a free radical scavenger, used to combat damage in various tissues. This research was performed to define the mechanistic hypothesis of ZnO NPs induced cardiotoxicity and the possible protective role of NAC. Methods : The research was performed on 40 adult albino rats; divided into 5 groups each of 8 rats, group I as a negative control, group II (positive control) received distilled water, group III (NAC group) received (200 mg/kg) NAC dissolved in distilled water, group IV (ZnO NPs group) : received (422 mg/kg) ZnO NPs dissolved in distilled water, group V (NAC and ZnO NPs group): received NAC then ZnO NPs in the same doses. The treatments were given via oral gavage, once daily for 4 weeks. Results : There was a significant increase in mean values of cardiac enzymes and a significant decline in the total antioxidant capacity in ZnO NPs treated group as compared with the control group. DNA fragmentation was observed in heart tissues of ZnO NPs treated group. Histological examination of the heart of ZnO NPs treated group revealed degenerated myocardium, vacuolated cytoplasm, and congestion in myocardial blood vessels when compared with control group. Conclusion: Administration of NAC offered protection against cardiotoxic effects induced by ZnO NPs. and to evaluate the protective role of NAC supplementation in albino rats.
CREATING HARMONY AND SUSTAINABILITY THROUGH RAMPAK NAONG BRINGEN KORONG - BASED MANAGEMENT CONTROL SYSTEM

<p class="JurnalASSETSABSTRAK"><strong>ABSTRACT</strong></p><p><span class="y2iqfc"><span lang="EN">This research aims to empirically see how leaders' role in creating tone as a form of culture-based Management Control System. This study uses a qualitative interpretive approach to obtain a holistic picture of a unique phenomenon, the story of the tobacco trading business in Bondowoso, which Madurese workers dominate. Business practice is thick with the value of "Rampak Naong Bringen Korong" as an alternative spirit of SPM based on local wisdom. The results of this study seek to build a conceptual framework for MCS based on local wisdom "Rampak Naong Bringen Korong" which is abstracted from various empirical field findings expected to maintain balance, accountability, business order, and sustainability. </span></span></p><p class="JurnalASSETSABSTRAK"><strong><em>ABSTRAK</em></strong><em></em></p><p><span class="y2iqfc"><span lang="EN">Penelitian ini bertujuan untuk melihat secara empiris bagaimana peran pemimpin dalam menciptakan tone sebagai salah satu bentuk dari Sistem Pengendalian Manajemen berbasis budaya. Penelitian ini menggunakan pendekatan kualitatif interpretif untuk mendapatkan gambaran holistik tentang sebuah fenomena unik, kisah usaha dagang tembakau di Bondowoso yang didominasi oleh pekerja suku Madura. Praktik bisnis yang kental dengan nilai “Rampak Naong Bringen Korong” sebagai spirit alternatif SPM berbasis kearifan lokal. Hasil dari penelitian ini berusaha membangun sebuah kerangka konseptual SPM berbasis kearifan lokal “Rampak Naong Bringen Korong” yang disarikan dari berbagai temuan empiris lapangan yang diharapkan akan menjaga keseimbangan, akuntabilitas, keteraturan bisnis dan sustainability. <br /></span></span></p>
THE PSYCHOLINGUISTIC BASIS OF THE LINGUISTIC CONCEPTUALIZATION

The object of this article is the methodology of psycholinguistics concerning analyzing concepts. The article's relevance is due to the need to apply new approaches to linguistic phenomena analysis, for which a purely linguistic methodology is not enough. The com­pilation method, a comparative method, and a linguistic modeling method are utilized to fulfill the study's aim. The author describes in detail the research gaps that exist at the moment in psycholinguistics, in particular, the structure of the relationship between sen­sory, short-term and long-term memory is still not fully defined, and therefore the basis for a deep analysis of conceptualization is not fully clear. The author concludes that the psycholinguistic methodology has the greatest explanatory power concerning the cognitive process of conceptualization. At the same time, in the case of comparative analysis of va­rious linguistic cultures, the need for additional use of the conceptual and methodological apparatus of cultural studies and ethnology is actualized.
Modeling a multiple-chain emeraldine gas sensor for NH3 and NO2 detection

This paper describes atomistic device models of a multiple-chain polyaniline (PANI) gas sensing component, utilizing the non-equilibrium Green’s functions formalism. The numerical results are compared with experimental data of ammonia and nitrogen dioxide detection. Multiple molecules of PANI in the form of emeraldine salt were studied with more than one absorbed molecule of ammonia or nitrogen dioxide. From the I–V characteristics of the system with and without adsorbed gas molecules for gas concentrations of 3, 6, 9, and 12 ppm, the effective resistance changes, (R − R0)/R0, were obtained and compared with experimental results. A good agreement with the measured values was obtained. In summary, PANI as emeraldine salt was numerically modeled for several adsorbed gas concentrations, several gas configurations, and different PANI molecule positions, including carrier hopping between them. The results are comparable to the experiment and show good properties for the application as gas sensor device for NH3 detection and rather good properties for NO2 detection.
RR Lyrae Stars

Preface 1. Introduction 2. The absolute magnitude of the RR Lyrae stars 3. RR Lyrae stars in globular clusters 4. RR Lyrae stars of the galactic field 5. Period changes, the Blanzhko effect, and the double mode pulsation 6. RR Lyrae stars beyond the Milky Way Glossary of symbols Short list of journal abbreviations References Index.
Local Scale-Guided Hierarchical Region Merging and Further Over- and Under-Segmentation Processing for Hybrid Remote Sensing Image Segmentation

With the development of medium- and high-resolution satellites, successfully segmenting differently sized geo-objects remains a challenging issue for geographic object-based image analysis (GEOBIA). The hybrid image segmentation method is a good alternative to produce good segmentation that best matched the different sizes of geo-objects. However, the existing methods almost use segmentation parameters (SPs), such as scale, to control the sizes and shapes of segments. This will lead to two issues: (1) one single scale is impossible to segment every geo-object well due to the land cover complexity within remote-sensing imageries; (2) over- and under-segmented regions still occur in the segmentation results, whatever using any advanced segmentation methods. To solve the above problems, this paper developed a hybrid image segmentation method with local scale-guided hierarchical region merging and further over- and under-segmentation processing. First, the primitive segmentation was produced and then stratified into layers with different land covers. Then, the local scale was calculated for a more objective merging process in the separating layers. Third, the over- and under-segmentation at separating layers was recognized and re-processed for achieving a fine segmentation. To validate the proposed method, it was applied to three test images of gaofen-1 satellite with different land cover types, and ten competing methods were compared. The visual and quantitative results indicated the advantage of our method in segmenting out different sizes of geo-objects, which can effectively reduce the over- and under-segmentation error.