Miracle-dz/UniFAR-FTUs huggingface dataset:
The Relevance of Vertical Housing to the Socio-Economic Characteristics of Occupants in Semarang City, Indonesia: Particularly the Proximity of Public Facility Aspects

Population growth and economic development can lead to increased housing demand amid limitations and rising land prices in the City of Semarang, Indonesia. One effort to overcome this challenge has involved shifting the approach to providing shelter to building vertical housing. However, various problems have emerged which suggest that vertical housing is not currently relevant to the socio-economic characteristics of its inhabitants. Thus, this study aims to determine the relevance of vertical housing to residents’ socio-economic characteristics particularly in proximity of public facility aspects. To achieve the research objective, this research uses quantitative research method. Importance–performance analysis (IPA) uses to determine the relevance of vertical housing to residents’ socio-economic characteristics and geospasial tools use to analyze descriptively the proximity of public facilities. Based on the relevance analysis, it can be concluded that the relevance between residents in apartments and residents in flats has some differences. This could happen because of differences in the location and financial capability of residents in apartment and flat. Performance improvement is needed, especially on economic factors for apartments and accessibility factors for low-cost flats so that vertical housing can become more relevant. Therefore, these findings can become input in formulating a policy for providing affordable vertical housing in the Semarang that is well-suited to the socio-economic characteristics of its inhabitants.
Pleistocene to Recent rejuvenation of the Hebron Fault, SW Namibia

Abstract The Hebron Fault in SW Namibia is associated with a <1 m to 9.6 m high scarp displacing Proterozoic basement and Middle to Late Pliocene crystalline conglomerates. The young age of strata exposed in the fault scarp together with evidence for displacement of aeolian dunes, post-dating the Middle Stone Age, suggests that latest fault displacements occurred during the Late Pleistocene to recent. Recorded historical seismic events show that the fault zone is still active. Latest movements of the fault are recorded by: down-to-the-SW offset of calcrete-cemented conglomerate; fluvially modified, asymmetric hanging wall, graben-like structures; at least two left-stepping jogs in the fault trace and structural data from basement rocks in which late-stage crush zones overprint earlier cataclasite. These features provide consistent evidence that the present scarp formed predominantly by normal dip-slip displacement on a NW-striking, steeply SW-dipping master fault with only a minor dextral strike-slip component. Strongly veined cataclastic fault rocks adjacent to the scarp in basement most probably originated at depths of 4–10 km. The conclusion is therefore that recent fault activity has reactivated a pre-existing, much older fault. Aerial photographic lineaments and similar fault scarps identified NW and SE of the present study area are interpreted as extensions of the same fault structure. Hence the total length of the Hebron Fault is at least 300 km subparallel to the Atlantic margin of southern Africa. Our observations confirm that the Hebron Fault is a neotectonic feature of regional significance that may relate to late Cenozoic and particularly Quaternary neotectonic activity in NE Namibia and NW Botswana.
High Dimensional Data Classification Approach with Deep Learning and Tucker Decomposition

Along with the success of deep learning are extensive models and huge amounts of data. Therefore, efficiency in deep learning is one of the most concerning problems. Many methods have been proposed to reduce the complexity of models and have achieved promising results. In this paper, we look at this problem from the data perspective. By leveraging the strengths of Tensor methods in data processing as well as the efficiency of deep learning models, we aim to reduce costs in many aspects such as storage and computation. We present a data-driven deep learning approach for high-dimensional data classification problems. Specifically, we use Tucker Decomposition, a tensor decomposition method, to factorize the large, complex structure raw data into small factors and use them as the input of lightweight deep model architecture. We evaluate our approach on high-dimensional, complex datasets such as video classification on the Jester dataset and 3D object classification on the ModelNet dataset. Our proposal achieves competitive results at a reasonable cost.
Do you see any problem? On the Developers Perceptions in Test Smells Detection

Developers are continuously implementing changes to meet demands coming from users. In the context of test-driven development, before any new code is added, a test case should be written to make sure new changes do not introduce bugs. During this process, developers and testers might adopt bad design choices, which may lead to the introduction of the so-called Test Smells in the code. Test Smells are bad solutions for implementing or designing test code. We perform a broader study to investigate the participants’ perceptions about the presence of Test Smells. We analyze whether certain factors related to the participant’ profiles concerning background and experience may influence their perception of Test Smells. Also, we analyze if the heuristics adopted by developers influence their perceptions about the existence of Test Smells. We analyze commits of open source projects to identify the introduction of Test Smells. Then, we conduct an empirical study with 25 participants that evaluate instances of 10 different smell types. For each Test Smell type, we analyze the agreement among participants, and we assess the influence of different factors on the participants’ evaluations. Altogether, more than 1250 evaluations were made. The results indicate that participants present a low agreement on detecting all 10 Test Smells types analyzed in our study. The results also suggest that factors related to background and experience do not have a consistent effect on the agreement among the participants. On the other hand, the results indicate that the agreement is consistently influenced by specific heuristics employed by participants. Our findings reveal that the participants detect Test Smells in significantly different ways. As a consequence, these findings introduce some questions concerning the results of previous studies that do not consider the different perceptions of participants on detecting Test Smells.
Characterization of trade-offs between immunity and reproduction in the coral species Astrangia poculata

Background Living organisms face ubiquitous pathogenic threats and have consequently evolved immune systems to protect against potential invaders. However, many components of the immune system are physiologically costly to maintain and engage, often drawing resources away from other organismal processes such as growth and reproduction. Evidence from a diversity of systems has demonstrated that organisms use complex resource allocation mechanisms to manage competing needs and optimize fitness. However, understanding of resource allocation patterns is limited across taxa. Cnidarians, which include ecologically important organisms like hard corals, have been historically understudied in the context of resource allocations. Improving understanding of resource allocation-associated trade-offs in cnidarians is critical for understanding future ecological dynamics in the face of rapid environmental change. Methods Here, we characterize trade-offs between constitutive immunity and reproduction in the facultatively symbiotic coral Astrangia poculata. Male colonies underwent ex situ spawning and sperm density was quantified. We then examined the effects of variable symbiont density and energetic budget on physiological traits, including immune activity and reproductive investment. Furthermore, we tested for potential trade-offs between immune activity and reproductive investment. Results We found limited associations between energetic budget and immune metrics; melanin production was significantly positively associated with carbohydrate concentration. However, we failed to document any associations between immunity and reproductive output which would be indicative of trade-offs, possibly due to experimental limitations. Our results provide a preliminary framework for future studies investigating immune trade-offs in cnidarians.
Deep Learning for Safety: Helmet Detection in Construction Site Image Using YOLOv8

This research aims to implement deep learning algorithms related to safety at construction site images by detecting helmet usage among workers. To construct a deep learning model, it is necessary to acquire a photograph dataset. This study's dataset came from public sources. The subsequent procedure involves annotating the helmet entity within the image and implementing augmentation methods, such as vertical and horizontal image rotation, to enhance the dataset's diversity, resulting in 1067 images. The dataset will be divided into two parts: the training and testing sets, with proportions of 80% and 20%, respectively. Using the YOLOv8 algorithm, we conducted several tests examining different epoch values, such as 25, 50, and 100. In order to assess the efficacy of the model, the mean Average Precision (mAP) metric was employed. The findings of our study indicate that the highest achieved mean average precision (mAP) is 0.980 at epoch 25, based on the testing set. Notably, this value remains consistent when employing epoch 100. The results indicate that combining YOLOv8 and augmentation demonstrates proficient helmet detection capabilities.
Fully Distributed Optimal Economic Dispatch for Microgrids under Directed Communication Networks Considering Time Delays

Distributed generation and demand-side management are expected to play a more prominent role in future power systems. However, the increased number of generations and load demands pose new challenges to optimal energy management in a microgrid. In this paper, an economic dispatch model for microgrids considering Traditional Generators (TGs), energy storage units, wind turbines (WTs), and flexible loads is established. To tackle the Economic Dispatch Problem (EDP) over directed communication networks, a fully distributed algorithm developed by leveraging a two-step state information exchange mechanism is proposed. In addition, by employing a fixed stepsize, the proposed algorithm demonstrates rapid convergence. Furthermore, our algorithm is well-suited for nonquadratic convex cost functions. Subsequently, we extend our algorithm to address imperfect communication scenarios. Even in the presence of arbitrarily large yet bounded time delays, our algorithm exhibits robustness. Finally, several numerical examples are given to verify the correctness and effectiveness of the developed results.
VAR Analysis: What Drives The Profitability of Islamic Commercial Banks?

Third-party funds of Islamic commercial bank in period of 2015-2021 have been increasing, as well as the matter of financing. However, the profitability of Islamic commercial bank during those years were fluctuating below 1,5% which affected the average of Return on Assets in 2015-2021 below a healthy level of 1,1%. In 2017, the third-party funds and financing has been increased, but ROA value tended to be constant, while in 2020, the increase of third-party funds and financing was inversely proportional to ROA ratio value that was actually decreased. This phenomenon incompatibility with theory has stated that the higher distribution of financing, it would determine the higher ROA ratio. Since, banking sector was often regarded as a heart of driving force of the country’s economy and profitability was significant for banking continuity. It needed to conduct a research on determinants that affected profitability of Islamic commercial banks. Hence, this research was aimed to analyze the effects of third-party funds, NPF, Operational Cost, and SBIS on ROA. The method in this research was quantitative with vector auto regression model as the analysis method. Based on the result of estimation, the third-party funds, NPF, and Operational Cost did not affect, but SBIS affected positively on ROA.
Bank Lending in Dual Narratives: Economic Policy Uncertainty and Interest-Rate Derivatives

This research aims to examine whether banks can employ interest-rate derivatives to mitigate or intensify the effects of economic policy uncertainty on bank lending. By testing two opposing hypotheses, it offers valuable insights into how the interplay between bank lending, interest-rate derivatives, and EPU can influence bank’s loan growth. Using a sample of 1,285 Bank Holding Companies (BHCs) for the period from 1986 to 2017, panel regression analysis confirms a negative relationship between EPU and Commercial Industrial (C&I) loan growth. This negative association is not only statistically significant but also economically meaningful. Specifically, when EPU increases by one standard deviation, bank holding companies (BHCs) experience a decrease in loan growth rate by 91 basis points. While derivative users exhibit a significantly higher mean loan growth compared to non-users, the interaction term between interest-rate derivative usage and EPU is negative and statistically significant. This suggests that the usage of interest-rate derivatives aggravates the negative impact of EPU on bank lending.
Improving test team performance through an Episodic Organizational Change implementation: A case study replication and extension

CONTEXT: Despite using organizational change interventions as adaptive mechanisms to meet external and internal demands, the software industry still faces challenges in implementing effective team restructuring and reorganizing their projects to maintain or improve the productivity and quality of their activities. GOAL: This paper presents the analysis of an Episodic Organizational Change (EOC) implemented in a matrix company in the software industry that culminated in the restructuring and reorganization of a multitasking test team responsible for ensuring coverage of different test scopes demanded by several projects simultaneously. METHOD: To compare and extend the findings regarding the implementation process of EOCs in the software industry, we replicated a case study that analyzed the motivations, action plan, critical success and failure factors, positive and negative impacts, lessons learned, and suggestions for improvements. RESULTS: The experience gained in this replication suggests that the steps and elements analyzed in this case study can become an EOC analysis process applied in the software industry. Compared to the original case study, the results of this replication corroborate with the motivations, goals, action plan implementation approach, and positive results. However, they diverge from generated negative results. Besides, they expand the findings related to critical factors. Finally, they suggest a pattern in the life cycle of this type of intervention. CONCLUSION: The findings substantiate that the implementation of EOCs that impact the dynamics of teams involved in the development of software projects directly influences the productivity and quality of their deliveries. These results underscore organizations’ need for a careful and diligent approach in planning, managing, and implementing these interventions. The analysis of implemented EOCs can enhance the efficiency of this type of intervention, mitigating risks, seizing opportunities, and reducing the occurrence of failures.
Association between recovering from tempo perturbations and reading measurements

A strong correlation between auditory temporal processing and reading proficiency has been consistently observed across clinical and nonclinical populations, spanning various age groups and languages. Specifically, rhythm sensitivity in both the music and speech domains has been considered to be fundamental for accurately tracking the hierarchical acoustic components in speech, playing a central role in the development of reading skills. However, the empirical validation of this hypothesis has primarily utilized stimuli with an isochronous underlying beat structure, which is limited in its ability to capture the nonlinearity inherent in the perception of timing within the speech and music domains. In our current study, we introduced perturbation stimuli and demonstrated a relationship between sensorimotor synchronization performance and reading measurements in the neurotypical adult population. Specifically, the current study highlighted that sensorimotor synchronization during the post-perturbation time window yields notably superior predictive value across a wide array of reading measurements when compared to the pre-perturbation time window, which, in contrast, did not predict reading measurements. Furthermore, our novel curve fitting analysis effectively captured the nonlinear aspects of participants’ sensorimotor synchronization performance when recovering from tempo perturbation, providing further insight into their auditory temporal processing abilities when responding to timing changes in auditory signals—a phenomenon commonly encountered in both speech and music contexts.
Multi‐scale modeling for the prediction of Young's modulus of alkali‐activated slag concrete

Alkali‐activated slag is an alternative to ordinary Portland cement that can be used for structural applications. Young's modulus is an important property to predict stress or strains in concrete. However, the fib Model Code 2010 overestimates it for alkali‐activated slag concrete. Multi‐scale models allow the determination of concrete property from the features of the microstructure. In this study, an analytical micromechanics‐based multi‐scale homogenization model is applied to predict Young's modulus of alkali‐activated slag. It is compared to experimental results found in the literature on paste, mortar and concrete. Better predictions of Young's modulus are achieved from multiscale models compared to the fib MC 2010. Accuracy could be enhanced by improving the predictions for the degree of activation of slag for the different mixes.
Geochemical feature and its tectonic significance of Gemucuo Oligocene potassic volcanic rocks in the Qiangtang area ,Tibet,China

There is a suite of potassic volcanic rocks(~30Ma)occurred in Gemucuo,Qiangtang area mainly composed of olivine tephrite,olivine trachy-basalt,aegirite augite trachyte and leucite phonolite.SiO2 content of this suit ranges from 46% to 60%,Al2O3 from 3% to 21%,Mg# from 0.14 to 0.63,K2O/Na2O ratio is above 1.The volcanic rocks are enriched in LREE and depleted in com-patible element(Cr、Ni)and HFSE(Nb、Ta、Ti). The eHf(t)of whole rock mass ranges from-1.28 to-6.20. It is indicated that the pri-mary magama source originated from minor melting of an ancient subduction mantle wedge which was metasomatised of astheno-sphere fluid,and consanguineous igneous magma went through AFC(Assimilation Fractional Crystallization). The potassic to ultra-potassic volcanic rocks in Gemucuo,Yulinshan and Huochetoushan together formed the Oligocene potassic to ultrapotassic volcanic rock belt in Qiangtang area.Combined with the study of the magmatic evolution of Cenozoic volcanic rocks in southern Qiangtang,the genesis of the magma might be related to the upwelling of asthenosphere and thinning of lithosphere,which were induced by the sepreation of Qiangtang intracontinental subduction plate 35Ma ago.
Generating Pseudo Random Volumes for Volumetric Research

Volumetric data is commonly used to understand the structure of an object, like the human body, underground structures, or weather data. However, it is difficult to use this data as it requires expensive equipment and is difficult to automate. This data is expensive to create and catalogue on a large enough scale for a controlled study. We present a solution to this challenge by releasing an open-sourced system to create volumes solely designed for user studies for immersive experiences displayed through a Virtual Reality (VR) or Augmented Reality (AR) headset. By utilizing a system like this, we not only have a clear understanding of how a study can be received in Mixed Reality (MR), but it is possible to have a high level of control over the data, allowing for a higher degree of flexibility in the underlying data design. To facilitate this, we have designed a modular system designed to generate and validate volumes, adhere to a rule set interact within them from a VR or AR interface and evaluate the types of volumes that could be formed.
PHYSICAL SIMULATION OF DEFORMATION AND FAILURE MECHANISM OF SOFT AND HARD INTERBEDDED SALT ROCKS

Considering the geological formation characteristics of salt mines in China,a series of physical simulation experiments were carried out to simulate the soft and hard interbedded salt rocks.The influences of dip angle,interlayers and interfaces on the deformation and failure mechanism of soft and hard interbedded salt rocks were discussed.The test results and theoretical analysis show that:(1) As the dip angle changes,the uniaxial compressive strength curve of soft and hard interbedded salt rocks presents U-shape. (2) When the dip angle θ 30°,the failure mode is structural failure dominantly controlled by the hard interlayers;when 45°θ75°,the failure mode is shear or sliding failure dominantly controlled by weak interlayers or weak interfaces;when 85°θ90°,the failure mode is splitting failure at hard layers or partial shear failure at weak layers. (3) Shear or sliding failure along weak interlayers or weak interfaces is the internal cause that the uniaxial compressive strength curve of soft and hard interbedded salt rocks shows U-shape.Therefore,when setting the range of internal pressures,more attention should be paid to the shear strength of weak interlayers and weak interfaces,in particular those at the haunches of storages,to prevent these interlayers and interfaces from being damaged and to avoid potential leakage of gas.
Relationship between Banks’ Perception on Bank of Tanzania Regulatory Reviews and Financial Performance: Evidence from selected Commercial Banks in Tanzania

The Central Bank of Tanzania has undergone various bank regulations reviews at different periods of time such as the one undertaken in 1998, 2008 and 2014. This study, therefore, intended to assess the relationship between banks perception on regulatory requirements reviews decisions and the bank performance. The study employed a cross-sectional design with the target population of 36 commercial banks. A sample of 120 respondents were selected from 24 commercial banks obtained in Dar es Salaam City. Primary data were collected from bank managers while secondary data were collected from audited annual financial statements. Descriptive statistics and correlation analysis were used for data analysis. Findings from the study showed that most banks had high perception regarding new regulations. However, the study noted low perception on the number of quarterly publication days, and on liquidity and cash reserve ratios requirements which seemed to be difficult for most banks to afford. Correlation analysis results showed that the relationship between banks perception on the new regulatory requirements and the financial performance was positive and significant with a high degree of correlation. The study concludes that most banks highly supported the reviews made by the BoT on capital adequacy and information reporting and disclosure requirements. The study recommends that commercial banks need to implement the new capital adequacy requirements and information reporting and disclosure requirements with special attention in order to make banks more profitable. Moreover, the regulator of banks needs to think on reviewing publication days and liquidity requirements.