Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating the Influence of EA Capabilities on Digital Transformation in the Ministry of Finance of Indonesia

Enterprise Architecture (EA) has been adopted by the Ministry of Finance (MoF) of Indonesia since 2018 as a strategic methodology to achieve the MoF's organizational goals more effectively and efficiently by defining, mapping, aligning and integrating business domains, data, applications and technology. EA's role in digital transformation is listed in the MoF's EA Vision, namely as an orchestrator who accelerates and harmonizes digital transformation in the MoF and focuses on outcomes. However, a number of stakeholders considered that the value provided by EA to support the MoF's digital transformation was considered not optimal. This is allegedly caused by the insufficient maturity level of the MoF's EA capability. The purpose of this paper is to analyze the perceptions of the MoF's EA Team on the maturity of EA capabilities and their influence on the MoF's digital transformation. The methodology used in analyzing this effect is the Partial Least Square Structural Equation Model (PLS-SEM). The research findings demonstrate that the MoF's EA capabilities, categorized into enabler capability and utilization capability, have a significant positive influence on the digital transformation within the MoF.
The Influence of Meteorological Factors and the Time of Day on the Concentration of Ammonia in the Atmosphere Measured Using the Photoacoustic Method near a Cattle Farm—A Case Study

Influences of animals, time of day, air temperature and relative humidity, wind speed and direction on ammonia concentrations were investigated. A case study on a typical summer day from 7:00 to approximately 24:00 CEST (moderate wind speed, variable cloudiness and maximum global radiation higher than 950 W/m2) in west–central Poland is presented. Concentrations of this gas were measured at four heights (0.1–1.5 m), which were changed every 5 min, using a Nitrolux 1000 photoacoustic spectrometer. A micrometeorological station was established to also measure the surface energy budget components. The results presented are the average for each hour and for the entire day. The fine structure of concentration profiles, plume detection and uncertainty of ammonia flux calculation are also presented. The highest NH3 concentrations were at a 0.5 m height between 16:00 and 17:00 h when cows were grazing, but the lowest concentrations were between 23:00 and 24:00 h at the height of 1.5 m. The ammonia concentration increased with increasing air temperature and was the highest with a westerly wind direction and decreased with increasing air relative humidity. The greatest influence on the ammonia concentration was related to the presence of cows and the time of day, while a slightly smaller influence was noted in terms of air temperature and wind direction. A case study is suitable for presenting local effects, inhomogeneities and quantifying uncertainties in the bidirectional ammonia flux calculation.
Broadband Continuous Transverse Stub (CTS) Array Antenna for High-Power Applications

A continuous transverse stub (CTS) array antenna with broad bandwidth and high-power handling capacity is proposed in this paper. The technologies of multi-step impedance matching and T-shaped electromagnetic band-gap (EBG) loading are utilized, which improved the antenna operating frequency bandwidth. An H-plane lens horn is used to feed the CTS array. As a result, a good bandwidth capability of more than 32% is achieved, with a gain variation less than 3.0 dB. The measured sidelobe level (SLL) is below −18 dB in the entire frequency range. Moreover, the power handling capacity of the antenna is more than 80 MW and can reach the GW level after arraying, which indicates that this antenna has application potential in the high-power microwave (HPM) field.
Modelling irrigation water management under water shortage and salinity conditions

Establishment of efficient irrigation and drainage management for sustainable crop production can be a complex process because of the interactions that exist between the system variables involved such as the crop, soil water, and hydroclimatic conditions. Mathematical modelling has been recognised as a useful approach in the assessment of the impact of different irrigation and drainage practices on crop yield. The usefulness of mathematical models in identifying efficient management strategies under uncertain conditions is, however limited by the theories used in models as well as by the availability and quality of field data that can be used in the calibration and validation of these models. Many models have been developed and used to simulate water and solute flux in the crop rootzone. This thesis describes the development and application of the WAVE model to simulate water and solute transport in the vadose zone and their effect on crop transpiration and yield. The WAVE model was modified to include the effect of salinity on crop transpiration, and used to simulate soil water balances, to investigate long-term salinity build-up in the root zone, and in conjunction with a crop yield response model to assess their effect on crop yield. The practicality of the modelling approach in the establishment of optimal irrigation and drainage practices is considered through application to the Makhtaaral region of South Kazakhstan. The impact of several irrigation and drainage scenarios was evaluated. Optimal irrigation and drainage strategies for sustainable crop production have been derived. For the problem considered in this study, the WAVE model, along with the crop yield response model, can be used as a tool for assessing the impact of different irrigation and drainage scenarios on crop yield. The results demonstrate that the modelling approach is robust and applicable under and and semi-arid conditions and to a wide range of water shortage and salinity conditions.
140-GHz Affordable Miniaturized Array Antenna-on-Package for Sub-THz Transceiver

In this paper, an affordable and miniaturized 140 GHz transmit/receive (TRX) array antenna-on-package (AoP) is proposed through the conventional PCB process employing a single substrate. The proposed design approach involves an in-depth analysis of the potential performance degradation of an D-band antenna operating within a coarse process and pratical design guide for the configuration of the matching network packaging with robust wedge bonding. An asymmetric matching network design technique for a <inline-formula> <tex-math notation="LaTeX">$1\times 4$ </tex-math></inline-formula> array antenna packaging accounts the 1-bit digital beamforming capabilities of radio frequency integrated circuit (RFIC). In a first-of-its-kind demonstration, AoP with <inline-formula> <tex-math notation="LaTeX">$1\times 2$ </tex-math></inline-formula> transmit and <inline-formula> <tex-math notation="LaTeX">$1\times 4$ </tex-math></inline-formula> receive antennas are packaged with RFIC is fabricated. The measurements arrayed maximum gains of the transmit and receive antennas were noted to be 9.8 dBi and 11.8 dBi, respectively. Also, the gain bandwidths of 12.6% for the transmit antenna and 20.4% for the receive antenna are achieved. This work marks the first instance of a TRX AoP being fabricated from a single RF metal layer via a width/gap process condition of 100/<inline-formula> <tex-math notation="LaTeX">$80 \mu \text{m}$ </tex-math></inline-formula> in the D-band.
One-Stage Infrared Ships Detection with Attention Mechanism

Infrared marine target detection is a key technology in marine monitoring. However, Infrared ship detection still encounters complicated challenges due to the insufficient spatial resolution and low signal-to-noise ratio resulting in an extreme lack of texture details for small infrared objects. At the same time, the ocean environment is changeable, unclear, and complex due to the influence of many disturbances. To alleviate these challenges, a one-stage object detection based on You Only Look Once (YOLOv7) model with attention mechanism is proposed for infrared ship detection. Our approach incorporated the Coordinate Attention for Efficient Mobile Network Design (CA) with YOLOv7 to reduce disregarded detections in small target strategies. To verify the effectiveness of our algorithm, infrared small ship images are captured and annotated. The experimental results explained that the improved YOLOv7 model performs better with a mean Average Precision (mAP) of 56.4%, denoting a 1.7 percentage point advancement over the baseline YOLOv7 model. It shows that the improved model can detect infrared small targets with high detection probability.
Helicobacter pylori induces a novel form of innate immune memory via accumulation of NF-кB proteins

Helicobacter pylori is a widespread Gram-negative pathogen involved in a variety of gastrointestinal diseases, including gastritis, ulceration, mucosa-associated lymphoid tissue (MALT) lymphoma and gastric cancer. Immune responses aimed at eradication of H. pylori often prove futile, and paradoxically play a crucial role in the degeneration of epithelial integrity and disease progression. We have previously shown that H. pylori infection of primary human monocytes increases their potential to respond to subsequent bacterial stimuli – a process that may be involved in the generation of exaggerated, yet ineffective immune responses directed against the pathogen. In this study, we show that H. pylori-induced monocyte priming is not a common feature of Gram-negative bacteria, as Acinetobacter lwoffii induces tolerance to subsequent Escherichia coli lipopolysaccharide (LPS) challenge. Although the increased reactivity of H. pylori-infected monocytes seems to be specific to H. pylori, it appears to be independent of its virulence factors Cag pathogenicity island (CagPAI), cytotoxin associated gene A (CagA), vacuolating toxin A (VacA) and γ-glutamyl transferase (γ-GT). Utilizing whole-cell proteomics complemented with biochemical signaling studies, we show that H. pylori infection of monocytes induces a unique proteomic signature compared to other pro-inflammatory priming stimuli, namely LPS and the pathobiont A. lwoffii. Contrary to these tolerance-inducing stimuli, H. pylori priming leads to accumulation of NF-кB proteins, including p65/RelA, and thus to the acquisition of a monocyte phenotype more responsive to subsequent LPS challenge. The plasticity of pro-inflammatory responses based on abundance and availability of intracellular signaling molecules may be a heretofore underappreciated form of regulating innate immune memory as well as a novel facet of the pathobiology induced by H. pylori.
TRADING STRATEGY BASED ON INTRADAY ABNORMAL VOLUME IN THE STOCK EXCHANGE OF THAILAND

This thesis proposes a trading strategy which trades based on the observation and prediction of abnormal volume events of stocks listed on the Stock Exchange of Thailand (SET) during July 2010 to June 2016. This research found that a positive excess return follows an abnormal volume event defined by the abnormally-high standardized volume and standardized directional volume. To confirm that such events are exploitable, a strategy that trades on those events is tested and found that they generate positive alphas even after including commission fees. Previous work has shown that typically an abnormal volume event is accompanied by a substantial excess return on the same day. Thus, this thesis further improved the strategy by attempting to capture the excess returns on the same day as abnormal volume events. An algorithm capable of predicting those events with high precision is developed and integrated into the strategy, enabling trade initiation before the end of the day. A portfolio simulation on out-of-sample data shows that the intra-day strategy generates incremental excess returns.
An epidemiological study of period poverty among females of reproductive age group in Lucknow (U.P.)

Background: Females in developing countries face brunt of lack of access to affordable menstrual supplies and inequitable distribution of menstrual health education and are victims of period poverty. The objective of the present study was to estimate prevalence of period poverty and to determine association of period poverty with socio-demographic determinants, menstrual knowledge, menstrual hygiene management practices, and reproductive health. Materials and Methods: This was an analytical cross-sectional study, conducted at an urban primary health care centre. Reproductive age group (20–49 years) females attending the primary health care centre from December 2022 to May 2023 were selected for study. Data were collected on semi-structured, pre-tested questionnaires. The collected data were entered in M.S Excel and analysed in STATA version 17.0. Chi-square test was used for comparison of qualitative data, and for quantitative data, unpaired t-test was used. Results: The prevalence of period poverty in the present study was 92 (29.7%). The mean age of females with period poverty was 29.72 ± 7.13 years, and it was 26.45 ± 6.62 years with no period poverty (P 0.001). Period poverty was significantly associated with socio-demographic variables. Period poverty had significant association with menstrual knowledge, menstrual hygiene management practices, and reproductive health. Conclusion: Many females cannot afford menstrual health products to meet their monthly needs, and this may affect their education and socio-economic status. Improved access to affordable sanitary products is requisite of females.
The Source Code Comment Generation based on Abstract Syntax Tree

Code summarization provides the main aim described in natural language of the given function; it can benefit many tasks in software engineering. Due to the special grammar and syntax structure of programming languages and various shortcomings of different deep neural networks, the accuracy of existing code summarization approaches is not good enough. We proposes to use abstract syntax trees for source code summarization . Our solution is inspired by recent advances in neural machine translation, as well as an approach called SBT by Hu et al. We evaluate our approach using the automated metric BLEU and compare it to other relevant models.
Machine learning-based estimation and clustering of statistics within stratigraphic models as exemplified in Denmark

Estimating a covariance model for kriging purposes is traditionally done using semivariogram analyses, where an empirical semivariogram is calculated, and a chosen semivariogram model, usually defined by a sill and a range, is fitted. We demonstrate that a convolutional neural network can estimate such a semivariogram model with comparable accuracy and precision by training it to recognise the relationship between realisations of Gaussian random fields and the sill and range values that define it, for a Gaussian type semivariance model. We do this by training the network with synthetic data consisting of many such realisations with the sill and range as the target variables. Because training takes time, the method is best suited for cases where many models need to be estimated since the actual estimation itself is about 70 times faster with the neural network than with the traditional approach. We demonstrate the viability of the method in three ways: (1) we test the model’s performance on the validation data, (2) we do a test where we compare the model to the traditional approach and (3) we show an example of an actual application of the method using the Danish national hydrostratigraphic model.
DO FINANCIAL DEVELOPMENT AND ECONOMIC GROWTH MATTER FOR ENVIRONMENTAL SUSTAINABILITY? FRESH EMPIRICAL INSIGHTS FROM VIETNAM

This paper explores the nexus between financial development, economic growth and environmental sustainability in Vietnam from 1990 to 2020. By applying Fully Modified Ordinary Least Square (FMOLS) and Dynamic Ordinary Least Square (DOLS) approaches, some main results are given as follows: (i) a compelling evidence to affirm that financial development contributes positively to environmental sustainability in Vietnam; (ii) a positive association is observed between economic growth, CO 2 emissions, and ecological footprint, resulting in a deterioration of environmental quality. To strengthen the reliability of our conclusions and validate the outcomes generated by FMOLS and DOLS, this article utilizes the Canonical Cointegrating Regression (CCR) estimation method. In the analysis, it is evident that the outcomes are consistent across all three methods. By understanding the Vietnamese context, we aim to glean insights and policy implications that can inform strategies for achieving a more balanced and sustainable future where prosperity and environmental well-being coexist harmoniously. In doing so, we contribute to the broader global conversation on the critical nexus of finance, economy, and sustainability.
StHsfB5 Promotes Heat Resistance by Directly Regulating the Expression of Hsp Genes in Potato

With global warming, high temperatures have become a major environmental stress that inhibits plant growth and development. Plants evolve several mechanisms to cope with heat stress accordingly. One of the important mechanisms is the Hsf (heat shock factor)–Hsp (heat shock protein) signaling pathway. Therefore, the plant transcription factor Hsf family plays important roles in response to heat stress. All Hsfs can be divided into three classes (A, B, and C). Usually, class-A Hsfs are transcriptional activators, while class-B Hsfs are transcriptional repressors. In potato, our previous work identified 27 Hsfs in the genome and analyzed HsfA3 and HsfA4C functions that promote potato heat resistance. However, the function of HsfB is still elusive. In this study, the unique B5 member StHsfB5 in potato was obtained, and its characterizations and functions were comprehensively analyzed. A quantitative real-time PCR (qRT-PCR) assay showed that StHsfB5 was highly expressed in root, and its expression was induced by heat treatment and different kinds of phytohormones. The subcellular localization of StHsfB5 was in the nucleus, which is consistent with the characterization of transcription factors. The transgenic lines overexpressing StHsfB5 showed higher heat resistance compared with that of the control nontransgenic lines and inhibitory lines. Experiments on the interaction between protein and DNA indicated that the StHsfB5 protein can directly bind to the promoters of target genes small Hsps (sHsp17.6, sHsp21, and sHsp22.7) and Hsp80, and then induce the expressions of these target genes. All these results showed that StHsfB5 may be a coactivator that promotes potato heat resistance ability by directly inducing the expression of its target genes sHsp17.6, sHsp21, sHsp22.7, and Hsp80.
Intensive sea urchin harvest rescales Paracentrotus lividus population structure and threatens self-sustenance

The harvest of the edible sea urchin Paracentrotus lividus is intensively practiced in some regions of the Western Mediterranean Sea. The removal of the largest individuals can determine an overall reduction in population size and a size class truncation that can lead to a drastic drop the self-sustenance. The aim of this study is to evaluate the variability of the population reproductive potential across 5 years in one of the main harvest hotspots of Sardinia (Western Mediterranean Sea). The breeding stock consists of commercial and under-commercial size individuals which were sampled on a monthly basis to estimate their GonadoSomatic Index (GSI) and the Individual Gamete Output (IGO). In addition, the reproductive potential of the population—Total Gamete Output (TGO)—was calculated across the 5-year period in relation with the variation of the density of the breeding stock. During the last year, the reproductive potential was also estimated in a well-conserved population of a nearby Marine Protected Area. No significant variability in GSI and IGO was found over the 5 years nor when compared with the ones of protected population in the last year. However, the intensive harvest drastically rescaled the population body-size: although density of the commercial size class remained low, density of the under-commercial size-class halved from the beginning to the end of the study. Accordingly, the proportional decrease of their gamete output contribution led to a 40% loss of the reproductive potential of the whole population in the 5-year period. Interestingly, despite the loss of reproductive potential due to the decrease of the breeding stock density, the average values of IGO slightly increased across the years leading to the highest Annual Gamete Output (AGO) during the fourth year of sampling. This positive pattern could suggest a mechanism of reproductive investments of the survivors in terms of gonad production rate or increase in spawning intensity. This work provides evidence of the direct effect of size-selective harvesting on the rapid loss of population self-sustenance. Furthermore, it lays new prospective for future research of the indirect effects of the rescaling population body-size in functional traits of the sea urchin P. lividus and that could become important for both, sustainable exploitation and ecosystem conservation management.
$\text{IED}_{\text{PUF}}$ Probe: A PUF-Based Hardware Fingerprint Extraction Equipment for IEDs

Intelligent Electronic Devices (IEDs) are vital components in modern electrical substations, collectively responsible for monitoring electrical parameters and performing protective functions. As a result, ensuring the integrity of IEDs is an essential criteria. While standards like IEC 61850 and IEC 60870-5-104 establish cyber-security protocols for secure information exchange in IED-based power systems, the physical integrity of IEDs is often overlooked, leading to a rise in counterfeit and tainted electronic products. This paper proposes a physical unclonable function (PUF)-based device ($\mathbf{IED}_{\mathbf{PUF}}$ probe) capable of extracting unique hardware signatures from commercial IEDs. These signatures can serve as identifiers, facilitating the authentication and protection of IEDs against counterfeiting. The paper presents the complete hardware architecture of the $\mathbf{IED}_{\mathbf{PUF}}$ probe, along with algorithms for signature extraction and authentication. A two-way authentication technique is employed to ensure that only verified requests are granted access for signature extraction. The limited results demonstrate its ability to provide real-time responses possessing randomness while uniquely identifying the IED under investigation. The proposed $\mathbf{IED}_{\mathbf{PUF}}$ probe offers a simple, cost-effective, accurate solution with minimal storage requirements, enhancing the authenticity and integrity of IEDs.
Depression Severity among a Sample of LGBTQ+ Individuals during the COVID-19 Pandemic

Background: The global pandemic of coronavirus disease 2019 (COVID-19) has led to immense impacts on global community health, the public perception of healthcare, and attitudes surrounding mental health during widespread quarantine. Methods: This analysis examines the rates of depressive symptomology among a sample of LGBTQ+-identifying individuals in the United States (n = 1090). The variables examined included socio-demographic factors, the use of mental health medication, access to mental health medication, and experiences of depression symptomology. Results: The findings indicate that depressive symptoms were less severe for older adults, as they reported higher levels of minimal to moderately severe depressive symptoms. Participants who were not working and those who were using substances were less likely to report depressive symptoms. Participants who were employed full-time reported higher levels of depression compared to those who were unemployed. Conclusions: Understanding the mental health of marginalized populations such as the LGBTQ+ community is critical to providing more nuanced preventative healthcare for unique populations, as members of the LGBTQ+ community are non-monolithic and require more personalized approaches to their healthcare needs.