Miracle-dz/UniFAR-FTUs huggingface dataset:
A COMPARISON STUDY ON DEEP LEARNING MODELS FOR BUILDING ROOFTOP CLASSIFICATION

Abstract. The availability of semantic information about a cityscape is essential for understanding and analysing urban processes. Automatic gathering of such information is important due to the enormous amount of data. A great number of building features could be gained solely by visual inspections. Therefore, it is meaningful to utilize recent advancements in automatic image recognition technologies to extract these properties automatically.This paper proposes an optimized solution for the classification of rooftops from aerial imagery based on a deep learning model using Convolutional Neural Networks (CNNs). It describes the architecture of the network, the training procedure and important hypermeters. A model analysis using advanced interpretability and explainability tools is conducted. The model’s superiority is demonstrated by comparing its performance against several state-of-the-art image classification architectures, including CNN-based ones such as Xception and Efficientnet, pure Visual Transformers (ViTs) based architectures such as BEiT, and hybrid architectures.
VAMP7j: A Splice Variant of Human VAMP7 That Modulates Neurite Outgrowth by Regulating L1CAM Transport to the Plasma Membrane

The vesicle-associated membrane protein 7 (VAMP7) is a SNARE protein of the longin family involved in a wide range of subcellular trafficking events, including neurite sprouting and elongation. The expression of the human gene SYBL1, encoding VAMP7, is finely regulated by alternative splicing. Among the minor isoforms identified so far, VAMP7j is the one most expressed and modulated in the human brain. Therefore, we focused on gaining functional evidence on VAMP7j, which lacks a functional SNARE motif but retains both the longin and transmembrane domains. In human SH-SY5Y cells, we found VAMP7j to modulate neuritogenesis by mediating transport of L1CAM toward the plasma membrane, in a fashion regulated by phosphorylation of the longin domain. VAMP7-mediated regulation of L1CAM trafficking seems at least to differentiate humans from rats, with VAMP7j CNS expression being restricted to primates, including humans. Since L1CAM is a central player in neuritogenesis and axon guidance, these findings suggest the species-specific splicing of SYBL1 is among the fine tuners of human neurodevelopmental complexity.
Offshore Migratory Corridors and Aerial Photogrammetric Body Length Comparisons of Southbound Gray Whales, Eschrichtius robustus, in the Southern California Bight, 1988–1990

Through most of their annual migration, gray whales, Eschrichtius robustus, remain within 10 km of shore, but in the Southern California Bight many individuals migrate much farther from shore. This paper summarizes aerial survey and photogrammetric efforts to determine body lengths and temporal and spatial distributions of migratory gray whales in the southern portion of the Southern California Bight. Aerial surveys were flown along 13 east–west transects between lat. 32°35′N and 33°30′N during the southbound gray whale migratory seasons of 1988–90 in the Southern California Bight. Photogrammetry was used to obtain body length estimates of animals during some of the surveys. A total of 1,878 whales in 675 groups were sighted along 25,440 km of transect distance flown and 217 body lengths were measured. Using position and heading data, three major migratory pathways or corridors in the southern portion of the bight are defined. Those migrating offshore were split almost evenly between two corridors along the west sides of Santa Catalina and San Clemente Islands. These corridors converge on the mainland coast between San Diego and the United States–Mexico border. No whales larger than 11.5 m were photographed within 30 km of the mainland coast, suggesting that smaller, and presumably younger, whales use the coastal migratory corridor through the California Bight.
Shariah Framework Based on Qualities of Shariah Scholars Towards Islamic Fatwa Shopping in Nigeria

This study examines the characteristics of Islamic scholars in issuing fatwas, highlighting concerns that financial institutions may seek fatwas aligning with their profit-driven motives, potentially contradicting Islamic principles. Focusing on Nigeria, it assesses the qualifications of advisors and supervisors in Islamic financial institutions and examines their link to the issuance of fatwas. Gathering insights from 250 randomly selected Shariah scholars and students, the research employs structural equation modeling (SEM) for analysis. The reliability of survey responses was assessed using a 5-point Likert scale. The consistency of the data was verified using mean-variance extracted, composite reliability, and Cronbach's alpha. SEM was used to assess the relationship between scholars' qualifications and the issuance of fatwas. The results underscore the importance of attributes such as knowledge, piety, sincerity, honesty, and legal responsibility in the issuance of fatwas, reflecting broader concerns about fatwa shopping. The study's scope was limited to Nigeria, focusing on scholars' perceptions of fatwa shopping
Deep Learning-Based Prediction of Alzheimer’s Disease Using Microarray Gene Expression Data

Alzheimer’s disease is a genetically complex disorder, and microarray technology provides valuable insights into it. However, the high dimensionality of microarray datasets and small sample sizes pose challenges. Gene selection techniques have emerged as a promising solution to this challenge, potentially revolutionizing AD diagnosis. The study aims to investigate deep learning techniques, specifically neural networks, in predicting Alzheimer’s disease using microarray gene expression data. The goal is to develop a reliable predictive model for early detection and diagnosis, potentially improving patient care and intervention strategies. This study employed gene selection techniques, including Singular Value Decomposition (SVD) and Principal Component Analysis (PCA), to pinpoint pertinent genes within microarray datasets. Leveraging deep learning principles, we harnessed a Convolutional Neural Network (CNN) as our classifier for Alzheimer’s disease (AD) prediction. Our approach involved the utilization of a seven-layer CNN with diverse configurations to process the dataset. Empirical outcomes on the AD dataset underscored the effectiveness of the PCA–CNN model, yielding an accuracy of 96.60% and a loss of 0.3503. Likewise, the SVD–CNN model showcased remarkable accuracy, attaining 97.08% and a loss of 0.2466. These results accentuate the potential of our method for gene dimension reduction and classification accuracy enhancement by selecting a subset of pertinent genes. Integrating gene selection methodologies with deep learning architectures presents a promising framework for elevating AD prediction and promoting precision medicine in neurodegenerative disorders. Ongoing research endeavors aim to generalize this approach for diverse applications, explore alternative gene selection techniques, and investigate a variety of deep learning architectures.
How users shape a comfortable indoor climate : a socio-technical analysis of visions in research and daily practice at home : a case study based exploration on complexes underlying differences between calculated and actual energy consumption in housing

Indoor climate technologies are studied by TNO’s research group ‘Energy and Comfort Systems’. The researchers investigate the technical aspects of the dual purpose of the systems: save energy and improve comfort. Problematic is that these systems should reduce energy at home; however calculated energy use in research setting differs from actual energy consumption in housing. Within ECS grows awareness that users and their behavior play an important role in saving energy at home. Yet, social and technical considerations of energy savings are studied separately within TNO institute. An exploratory study into users’ behavior at home with a socio-technical perspective toward the problem was desirable. The following research question is addressed in this thesis: What underlying dynamics can be identified behind the differences between calculated energy use in research and actual energy consumption in housing by comparing (a) how users shape a comfortable indoor climate at home and (b) how researchers anticipate users, their behavior and comfort in research on indoor climate systems? This thesis follows Elisabeth Shove’s perspective, if energy efficiency is the focus, and the goal to stimulate energy saving use behavior of indoor climate systems, what matters is the meaning and realization of comfort that climatic systems provide. These are studied empirically from an STS point of view. The theoretical framework builds upon actor-network, scripting and appropriation theory and is extended with the concepts ‘design logic’ and ‘use logics’ of Jaap Jelsma and ‘everyday practices’ of Elisabeth Shove. These concepts help to place the meaning, realization and underlying reasons of a comfortable indoor climate at the center, and understand indoor climatic technologies, people and the further socio-material environment as part of the practice that they make possible. This framework has been used to analyze the research setting and six case studies of users at home. Within the research setting were user representations, constructions of comfort and design logics behind the research process identified. The cases demonstrated a variety of users’ meanings and realizations of a comfort in relation to the indoor climate, which were analyzed for common dimensions. It was difficult to explain the indoor climate practice only from the logics of the users; also ‘household logics’ and the material home environment were recognized as influencing climatic behavior. The findings were compared to deduce clues for deviation of actual from calculated energy consumption. The main underlying dynamic is the mismatch that researchers understand the shaping of comfortable indoor climate as a technical achievement of technology, but at home this turns out to be a socio-technical achievement. This and further conclusion are translated into recommendations for ECS research.
Are we ready to face the next wave of RSV surge after the COVID-19 Omicron pandemic in China?

Background China had its first wave of COVID-19 in 2020 and second wave of COVID-19 Omicron in 2022. The number of RSV cases decreased sharply in 2020 and 2022. Investigation of the resurge of RSV infections after the first wave of COVID-19 will guide us to take preventive actions before the resurge of RSV infections after the second wave of COVID-19 Omicron. Methods We analysed epidemiological and clinical data of 59934 patients with lower respiratory tract infections (LRTI) from a prospective long-term cohort surveillance programme in Suzhou, China, collected from February 2016 to January 2022. The annual incidence of RSV infection in children aged<16 years in 2020 and 2021 was compared with the pre-pandemic years 2016 to 2019. We also compared the clinical characteristics, and RSV-related ICU admissions between pre-pandemic years and 2021. Results Among children with LRTI, the positive rate of RSV increased by 70.7% in 2021 compared to the average level in the pre-pandemic years. The RSV resurge in 2021 was most prominently in children aged 2-4 years (a significant rise compared with the expected value 149.1%; 95%CI, 67.7% to 378%, P<.01). The percentage of RSV-related ICU admissions decreased in 2021 (3.2% vs 6.7%, P<0.01). The death rate of RSV infections in 2021 was 0.2%, while that in pre-pandemic years was only 0.02%. RSV-associated death in immunocompetent children (complicated by necrotizing encephalitis) was firstly occurred in 2021. Conclusions Our findings raise concerns for RSV control in Southeast China after the COVID-19 pandemic especially for children aged 2-4 years. Although ICU admissions were significantly reduced in this resurgence, we could not ignore the increase of RSV-associated death.
PERENCANAAN COVERAGE AREA FEMTOCELL JARINGAN LONG TERM EVOLUTION (LTE) FREKUENSI 1800MHz PADA GERBONG KERETA API DENGAN PHYSICAL CELL IDENTITY (PCI)

Ketersediaan layanan berkualitas di setiap tempat merupakan hal penting bagi pelanggan.Salah satunya di dalam gerbong kereta api, keterbatasan layanan berkualitas di dalam gerbong kereta api karena adanya efek dopler yang terjadi, performansi jaringan seluler pada saat user bergerak dengan kecepatan tinggi saat berada di atas kereta api, sangatlah tidak stabil. Dan juga adanya redaman yang terjadi oleh gerbong kereta api itu sendiri sehingga layanan yang dapat diberikan sangat terbatas. Pada gerbong kereta api, femtocell digunakan untuk coverage area dan memberikan akses layanan kepada pelanggan di dalam gerbong kereta api. Pada perencanaan ini dilakukan dua perhitungan untuk mendapatkan jumlah antena yang diperlukan pada masing – masing gedung , yaitu perhitungan secara coverage, dan perhitungan secara capacity. Skenario dari perancangan ini adalah menggunakan jumlah perhitungan coverage di setiap gerbong masing – masing sebanyak dua buah antena dan sekenario berikutnya menggunakan perhitungan capacity di setiap gerbong masing - masing sebanyak satu buah antena. Dan menghasilkan nilai receive Signal Level (RSL), nilai rata-rata Signal Interverence Ratio (SIR), dan juga throughtput masing-masing skenario. Dari hasil simulasi di tentukan penomoran PCI tiap cell nya. Hasil nya hasil rekapitulasi percobaan dengan menggunakan simulasi di dapatkan penempatan access point dan yang terpasang di berbagai lokasi dapat melingkupi hampir seluruh daerah dengan kualitas sinyal yang baik yaitu - 43.64 dBm ,- 41.11 dBm dan – 40.44 dBm . Kondisi dengan menggunakan 1 access point memiliki nilai SIR 13.69 dB dan 8.58 karena mendapatkan interferensi sedikit dari access point lainnya sedangkan dengan menggunakan 2 access point mempunyai nilai SIR sebesar 8.31 dBm karena mendapatkan lebih banyak interferensi dari pada 1 acces point. Penggunaan 1 access point dan 2 access point memperlihatkan persentase coverage yang tidak jauh berbeda berbeda. Pada percobaan dengan menggunakan 2 access point dan mempunyai daerah coverage yang terbaik. Kata Kunci : femtocell,PCI, SIR, throughput
Polymer Modeling Reveals Interplay between Physical Properties of Chromosomal DNA and the Size and Distribution of Condensin-Based Chromatin Loops

Transient DNA loops occur throughout the genome due to thermal fluctuations of DNA and the function of SMC complex proteins such as condensin and cohesin. Transient crosslinking within and between chromosomes and loop extrusion by SMCs have profound effects on high-order chromatin organization and exhibit specificity in cell type, cell cycle stage, and cellular environment. SMC complexes anchor one end to DNA with the other extending some distance and retracting to form a loop. How cells regulate loop sizes and how loops distribute along chromatin are emerging questions. To understand loop size regulation, we employed bead–spring polymer chain models of chromatin and the activity of an SMC complex on chromatin. Our study shows that (1) the stiffness of the chromatin polymer chain, (2) the tensile stiffness of chromatin crosslinking complexes such as condensin, and (3) the strength of the internal or external tethering of chromatin chains cooperatively dictate the loop size distribution and compaction volume of induced chromatin domains. When strong DNA tethers are invoked, loop size distributions are tuned by condensin stiffness. When DNA tethers are released, loop size distributions are tuned by chromatin stiffness. In this three-way interaction, the presence and strength of tethering unexpectedly dictates chromatin conformation within a topological domain.
Teaching communication skills with technology: Creating a virtual patient for medical students

Virtual patient (VP) is a concept used in the teaching of communication skills, and like physical examinations and other professional skills, must be taught with utmost care. In Turkey, as VPs are yet to be used in medical training, the usual practice when teaching such skills is to use standardised patients (individuals pretending to be patients). The main purpose of this study was to design, develop and evaluate a 3D VP application that can move, has speech-over lip sync, allows written communication and is supported by a strong scenario to improve the communication skills of students. The study was designed and carried out using developmental research methods. The implementation phase involved a pretest posttest quasi-experimental design. The participants in the study consisted of academics specialising in medicine, software experts, an education technology expert, an assessment and evaluation expert, and medical students. The study found that VP applications were accepted by students and were as effective as standardised patients for the teaching of communication skills. The students reported that the VP application developed was very successful in terms of visual and behavioural reality.
Risk Assessment of Piling Works for Mass Rapid Transit (Mrt) Construction Project

This study focuses on the piling works of Mass Rapid Transit (MRT) line 1 construction project along Sungai Buloh Station to Kajang Station in Malaysia, considering that piling work is one of the high risk construction activities. This study utilizes risk assessment tool using Hazard Identification, Risk Assessment & Risk Control (HIRARC) to create safe construction workplace. The hazard identification is a process of examination work area and task inherent to piling activities. The risk assessment of piling works calculated using likelihood and severity. Based on the hazard identification and risk assessment results, control measures or risk control are taken into action. The risk assessment sheets as the research instrument tool were filled by 30 construction professionals and safety practitioners i.e. safety officers, safety supervisors, site engineers and site supervisors. The results indicated that there were seven hazards that associated with piling works. One of the hazards which caused structure collapse during test pile activity was assessed as the extreme risk. Other six hazards were assessed as high risk. The total 27 risk control measures were resolved in order to eliminate and reduce hazards as well as prevent accident during piling work at the MRT construction project. Key-words: Construction, Mass Rapid Transit (MRT), Piling Work, Risk Assessment.
Cognitively Congruent Color Palettes for Mapping Spatial Emotional Data. Matching Colors to Emotions.

Emotions are touchstones of humans’ everyday life experiences. Maps of emotions inform a variety of research from urban planning and disaster response to marketing studies. Emotions are most often shown on maps with colors. Previous research suggests that humans have subjective associations between colors and emotions that impact objective task performance. Thus, a mismatch between the emotion associated with a color and the emotion it represents may bias the viewer’s attention, perception, and understanding of the map. There are no guidelines that can help cartographers and designers choose matching colors to display spatial emotional data. This study aimed to address this gap by suggesting cognitively congruent color palettes—color sets matched to emotions in a way that is aligned with color-emotion associations. To obtain the set of candidate congruent colors and identify appropriate color-to-emotion assignments, two user experiments were conducted with participants in the United States. In the first, participants picked a representative color for 23 discrete emotions. In the second experiment, for each candidate color from a set derived from the results of the first experiment, participants selected the best-matching emotions. The probability of the emotion being selected served as a measure of how representative the color is of that emotion. Due to the many-to-many nature of associations between colors and emotions, suitable color choices were incorporated into a dynamic palette generation tool. This tool solves the color assignment problem and produces a suitable color palette depending on the combination of selected emotions.
Ground-based ozone profiles over central Europe: incorporating anomalous observations into the analysis of stratospheric ozone trends

Abstract. Observing stratospheric ozone is essential to assess whether the Montreal Protocol has succeeded in saving the ozone layer by banning ozone depleting substances. Recent studies have reported positive trends, indicating that ozone is recovering in the upper stratosphere at mid-latitudes, but the trend magnitudes differ, and uncertainties are still high. Trends and their uncertainties are influenced by factors such as instrumental drifts, sampling patterns, discontinuities, biases, or short-term anomalies that may all mask a potential ozone recovery. The present study investigates how anomalies, temporal measurement sampling rates, and trend period lengths influence resulting trends. We present an approach for handling suspicious anomalies in trend estimations. For this, we analysed multiple ground-based stratospheric ozone records in central Europe to identify anomalous periods in data from the GROund-based Millimetre-wave Ozone Spectrometer (GROMOS) located in Bern, Switzerland. The detected anomalies were then used to estimate ozone trends from the GROMOS time series by considering the anomalous observations in the regression. We compare our improved GROMOS trend estimate with results derived from the other ground-based ozone records (lidars, ozonesondes, and microwave radiometers), that are all part of the Network for the Detection of Atmospheric Composition Change (NDACC). The data indicate positive trends of 1 % decade−1 to 3 % decade−1 at an altitude of about 39 km (3 hPa), providing a confirmation of ozone recovery in the upper stratosphere in agreement with satellite observations. At lower altitudes, the ground station data show inconsistent trend results, which emphasize the importance of ongoing research on ozone trends in the lower stratosphere. Our presented method of a combined analysis of ground station data provides a useful approach to recognize and to reduce uncertainties in stratospheric ozone trends by considering anomalies in the trend estimation. We conclude that stratospheric trend estimations still need improvement and that our approach provides a tool that can also be useful for other data sets.
Sorghum bicolor INDETERMINATE1 is a conserved primary regulator of flowering

Introduction A fundamental developmental switch for plants is transition from vegetative to floral growth, which integrates external and internal signals. INDETERMINATE1 (Id1) family proteins are zinc finger transcription factors that activate flowering in grasses regardless of photoperiod. Mutations in maize Id1 and rice Id1 (RID1) cause very late flowering. RID1 promotes expression of the flowering activator genes Early Heading Date1 (Ehd1) and Heading date 1 (Hd1), a rice homolog of CONSTANS (CO). Methods and results Mapping of two recessive late flowering mutants from a pedigreed sorghum EMS mutant library identified two distinct mutations in the Sorghum bicolor Id1 (SbId1) homolog, mutant alleles named sbid1-1 and sbid1-2. The weaker sbid1-1 allele caused a 35 day delay in reaching boot stage in the field, but its effect was limited to 6 days under greenhouse conditions. The strong sbid1-2 allele delayed boot stage by more than 60 days in the field and under greenhouse conditions. When sbid1-1 and sbid1-2 were combined, the delayed flowering phenotype remained and resembled that of sbid1-2, confirming late flowering was due to loss of SbId1 function. Evaluation of major flowering time regulatory gene expression in sbid1-2 showed that SbId1 is needed for expression of floral activators, like SbCO and SbCN8, and repressors, like SbPRR37 and SbGhd7. Discussion These results demonstrate a conserved role for SbId1 in promotion of flowering in sorghum, where it appears to be critical to allow expression of most major flowering regulatory genes.