Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of Data Compromises on Internet Users: A Review on Financial Implication of the Elderly in the United States

Data compromises, specifically personal data breach, in recent years, have become one of the issues that have caught the attention of the government as well as the relevant agencies because of their negative impact on elderly people in the U.S. as regard the amount of finance lost yearly to internet crime activities. The inability to effectively curb the level of internet criminal activities in the country has also resulted in financial loss trending for a few years among elderly people who are also the primary victims. The objective of the article is to review the financial implications of data compromises on elderly people concerning personal data breaches as well as to make a few recommendations to relevant bodies. The article adopted a descriptive-analytical method in the study to review data compromises while focusing on personal data breaches among elderly people. Data was collected through secondary means that focused on personal data breaches and financial loss between the years 2018 and 2022. The study review found that personal data breaches have become a trend among elderly people through which internet criminal activities were common in the U.S. The trended outcome of the data compromises have resulted in the financial loss among elderly people in the country. The article suggested a few recommendations to government and concerned agencies on the measures they could take to protect elderly people against falling victim to personal data breaches that prey on their finances.
Wenchuan Earthquake Deformation 3D Modelling based on ALOS/PALSAR Data

3 Abstract A devastating earthquake of magnitude Mw 7.9 occurred in Wenchuan area of Sichuan Province, China on 12 th May 2008 and caused great casualties and economic damage. This study is aiming to investigate the faulting geometry and motion of the major seismic faults in Longmenshan fault thrust belt that caused this earthquake, based on the surface rupture displacement data measured using differential interferometric synthetic aperture radar (DInSAR) and SAR amplitude pixel-offset techniques. The cross-event Japanese ALOS PALSAR data have been used for this study. First, the methodology for recovering the missing data in the decoherence zone of the DInSAR line-of-sight (LOS) surface motion maps was developed. In the area along the seismic fault zone, the coherence between preand post-event SAR images is completely lost because of the earthquake induced violent and chaotic destruction on the land surface and as the result, no surface displacement can be measured using the DInSAR technique. An Adaptive Local Kriging (ALK) technique has then been developed to retrieve the interferometric fringe patterns in the decoherence zone. The novel ALK operating in a multistep approach enables to retrieve and interpolate the values with high fidelity to the original dataset. Thus a map of continuous radar LOS displacement was generated. Then, the horizontal displacement motion maps in ground range and azimuth direction were derived from cross-event SAR amplitude image pairs using advanced sub-pixel offset technique, Phase Correlation based Image Analysis System (PCIAS). Though the ground range pixel-offset is proportional to the LOS displacement, the azimuth pixel-offset data provide extra information of the coseismic motion. Thus the horizontal displacement vector field can be obtained in order to constrain the faulting motions in key areas. Finally, with the constraints of the ALK refined DInSAR data and the horizontal displacement data together with the published seismic focal mechanism solutions, seismic reflection profiles and field observations, forward modelling was proceeded using the Poly3D software to decide the most likely faulting geometry based on the optimal matching between the simulated and the measured surface displacement. In the much disputed Beichuan – Pengguan area, the best fit is achieved only when the Pengguan fault is set as the main fault that intercept the Yingxiu-Beichuan fault at a depth of about 13 kilometres. This geometric relationship between the two faults and the distribution of slip is compatible with them being two adjacent splay faults on a propagating thrust.
The Aquila Digital Community The Aquila Digital Community

The Gulf Coast tick, Amblyomma maculatum , is a vector of several tick-borne pathogens, including Rickettsia parkeri . The ability of R . parkeri to persist within the tick population through transovarial and transstadial transmission, without apparently harming the ticks, contributes to the pathogen’s perpetuation in the tick population. Previous studies have shown that the R . parkeri load in A . maculatum is regulated by the tick tissues’ oxidant/antioxidant balance and the non-pathogenic tick microbiome. To obtain further insights into the interaction between tick and pathogen, we performed a bulk RNA-Seq for differential transcriptomic analysis of ovaries and salivary glands from R . parkeri -infected and uninfected ticks over the feeding course on a host. The most differentially expressed functional category was of bacterial origin, exhibiting a massive overexpression of bacterial transcripts in response to the R . parkeri infection. Candidatus Midichloria mitochondrii and bacteria from the genus Rickettsia were mainly responsible for the overexpression of bacterial transcripts. Host genes were also modulated in R . parkeri -infected tick organs. A similar number of host transcripts from all analyzed functional categories was negatively and positively modulated, revealing a global alteration of the A . maculatum transcriptome in response to pathogen infection. R . parkeri infection led to an increase in salivary transcripts involved in blood feeding success as well as a decrease in ovarian immune transcripts. We hypothesize that these transcriptional alterations facilitate pathogen persistence and
Markov average-based weighted fuzzy time series model to predict PT Kimia farma Tbk stock price

The COVID-19 pandemic impacted various activities in Indonesia, including the stock market. Despite the declining economic condition, people are increasingly interested in investing. Among other companies available on the Indonesia Stock Exchange, companies in the health sector have a particular appeal to potential investors, one of which is pharmaceutical companies. This research used a Markov Average-Based Weighted Fuzzy Time Series model applied to PT Kimia Farma Tbk stock price data. This model develops the previous Markov chain–Fuzzy Time Series model, which has not calculated the weights for recurring events and used the Sturgess rule to determine the interval length. In this research, each recurring event has given a different weight that provides different probability values for transitions from one state to another. The Average-Based method is used to determine the interval length that can reflect the fluctuation of the data used. The stock price prediction of PT Kimia Farma Tbk using this model is categorized as very accurate with a MAPE of 2.632%.
The evolution of river valleys in Lithuania from deglaciation to recent changes and data from the sediment infill of oxbow lakes

Abstract Generalized analysis of geological-geomorphological structures of river valleys in Lithuania has been carried-out. Lithuania’s fluvial topography results from the retreat of the Scandinavian Nemunas (= Vistulian and/or Valdaian) Glaciation, as is shown by the study of geomorphological structures in the recent river valleys (representing the last 15,000 years), which were formed as the ice sheets progressively retreated and ice-barrier lakes were drained. Oxbows in the river valleys are most often located on the floodplain itself and on the first terrace above the floodplain. The oxbow lakes are subdivided into two groups: (1) formed in the near-river stage and (2) formed in the lake-bog stage. Separate development phases can be recognized within both groups of oxbow lakes. The more organic components of oxbow deposits provide specific information for palaeoecological reconstructions. Anthropogenic changes to the natural landscapes of Lithuania have resulted in considerable geological transformation of rivers. Increased sediment volume, shallowing, silting and overgrowing of channels, lateral erosion of floodplains and the spread of ravine erosion on valley-side slopes are all phenomena characteristic of all the valleys in Lithuania. At present the natural components of river valleys and their ecosystems are being changed, mainly with negative consequences for humans.
Influence of PVA resin and cross-linking agent on the structure and properties of semi-refined carrageenan-based packaging films

For the high content of carrageenan in some seaweed and the low cost and easy availability of semi refined carrageenan (SRC), SRC resin powder was selected as our research object. Due to its water solubility, a solution casting method was adopted to form film, hoping to prepare food packaging materials that partially replace petroleum based resin. The pure SRC resin casting film is very brittle and cannot be formed. Therefore, 40wt% glycerol was added to the formula to plasticize and improve the flexibility and demoulding ability of SRC. The plasticized SRC film still has limitations. Soluble petroleum based polymer poly(vinyl alcohol) (PVA) resin was used as a blending modifier, cinnamaldehyde (CIN) as a crosslinking agent for acetal reaction with hydroxyl groups, boric acid (BA) as a provider of acidic environment and an auxiliary agent for generating partial hydrogen bonds with hydroxyl groups. Eight experimental research formulas were designed and FTIR, XRD, thermodynamic properties and mechanical properties of the modified films were analyzed. Both microscopic and macroscopic analyses have shown that under the acidic conditions of BA, CIN undergoes an acetal reaction with SRC and PVA, therefore mass ratio of the formula that SRC/glycerol/PVA/CIN/BA is 100/40/33.3/10/10, the film has the best tensile strength of 34.85Mpa, higher than that of other films. It has been proven that CIN does indeed act as a crosslinking agent in the formula, forming a network structure that enhances it.
Carbapenemase-producing Enterobacterales colonisation status does not lead to more frequent admissions: a linked patient study

Background . Hospitals in any given region can be considered as part of a network, where facilities are connected to one another – and hospital pathogens potentially spread – through the movement of patients between them. We sought to describe the hospital admission patterns of patients known to be colonised with carbapenemase-producing Enterobacterales (CPE), and compare them with CPE-negative patients. Methods . We performed a linkage study in Victoria, Australia, including datasets with notifiable diseases (CPE notifications) and hospital admissions (admission dates and diagnostic codes) for the period 2011 to 2020. Where the CPE notification date occurred during a hospital admission for the same patient, we identified this as the ‘index admission’. We determined the number of distinct health services each patient was admitted to, and time to first admission to a different health service. We compared CPE-positive patients with four cohorts of CPE-negative patients, sampled based on different matching criteria.
Low-Resource Vision Challenges for Foundation Models

Low-resource settings are well-established in natural language processing, where many languages lack sufficient data for machine learning at scale. However, low-resource problems are under-explored in computer vision. In this paper, we strive to address this gap and explore the challenges of low-resource image tasks with vision foundation models. Thus, we first collect a benchmark of genuinely low-resource image data, covering historic maps, circuit diagrams, and mechanical drawings. These low-resource settings all share the three challenges of data scarcity, fine-grained differences, and the distribution shift from natural images to the specialized domain of interest. While existing foundation models have shown impressive generalizability, we find they cannot transfer well to our low-resource tasks. To begin to tackle the challenges of low-resource vision, we introduce one simple baseline per challenge. Specifically, we propose to i) enlarge the data space by generative models, ii) adopt the best sub-kernels to encode local regions for fine-grained difference discovery and iii) learn attention for specialized domains. Experiments on the three low-resource data sources in our benchmark demonstrate our proposals already provide a better baseline than common transfer learning, data augmentation, and fine-grained methods. This highlights the unique characteristics and challenges of low-resource vision for foundation models that warrant further investigation. Project website: https://xiaobai1217.github. io/Low-Resource-Vision/.
Consumption, Trade and Innovation: Exploring the Botanical Remains from the Roman and Islamic Ports at Quseir Al-Qadim, Egypt

Foreword and Acknowledgements Chronology Table 1 INTRODUCTION 1.1 Aims and Research Questions 1.2 The Indian Ocean Trade Roman period trade Islamic period trade 1.3 Quseir al-Qadim - Myos Hormos/Kusayr 1.4 Data Collection and Methods Sampling strategy Identification Quantification and data presentation Preservation 1.5 Chronology (Marijke van der Veen and Derek Hamilton) Dating the Islamic assemblage - ceramics, coins and texts Dating the Islamic assemblage - radiocarbon dates Chronology of the Islamic assemblage Summary 1.6 Contexts and Botanical Dataset Contextual information - Roman Contextual information - Islamic The botanical assemblage 2 SPICES - CULINARY AND MEDICINAL COMMODITIES (Marijke van der Veen, Alison Cox & Jacob Morales) 2.1 Introduction 2.2 Spices at the Ports Pepper Rice Coconut Mung bean Myrobalans Ginger Turmeric Cardamom Fagara Betelnut Summary: patterns of trade at the ports 2.3 The Luxury of Long-Distance Trade Spices as preservatives Spices as commodities Spices as articles of desire 3 SUMMER CROPS - FROM TRADE TO INNOVATION (Marijke van der Veen & Jacob Morales) 3.1 Introduction 3.2 Summer Crops at the Ports Rice Citrus fruits Cotton Sugar cane Aubergine Taro Banana Sorghum Pearl millet Cowpea Watermelon Summary 3.3 Dispersal of Summer Crops into the Islamic World Pre-Islamic dispersal Islamic-period dispersal Patterns of dispersal 3.4 Agricultural Innovation Types of agricultural innovation Nature of agricultural innovation Agricultural innovation in Egypt COLOUR PLATES 4 FOOD AND FOODWAYS - PATTERNS OF EVERYDAY LIFE (Marijke van der Veen, Alison Cox & Jacob Morales) 4.1 Introduction 4.2 Food Consumption at the Ports Cereals Pulses Fruits Nuts Oilseeds Vegetables Herbs and spices Others Preservation - desiccation versus carbonization Summary 4.3 Animals, Fodder and Dung 4.4 Identifying Foodways Watermelon - fruit flesh versus seeds Citrus fruits - rind versus juice Grapes and pomegranates - fresh versus dried fruits Pulses - cooked dish versus snack food Aubergine - overcoming bitterness Others 4.5 Spatial Distribution of Waste Disposal Cereals - food versus fodder Food in the Roman port (1st-early-3rd centuries AD) Food in the Islamic port (mid-11th-13th centuries AD) Food in the Late Islamic port (14th and 15th centuries AD) 4.6 Patterns of Everyday Life Nutrition and health Eating as practice 5 WOODWORKING AND FIREWOOD - RESOURCE EXPLOITATION (Marijke van der Veen, Rowena Gale & Dirk A bel) 5.1 Introduction 5.2 Maritime Artefacts Roman ship-rigging artefacts Islamic ship timbers Pegs and wood shavings 5.3 Everyday Objects Individual artefact classes Summary 5.4 Firewood 5.5 Changing Resource Exploitation Ship-building Wood selection in everyday objects Firewood 6 MYOS HORMOS AND KUSAYR - DIFFERENT WORLDS 6.1 Commodities and Trade 6.2 Agricultural Crops and Innovation 6.3 Food and Consumption 6.4 Myos Hormos and Kusayr - Different Worlds Appendices List of figures List of Tables List of colour plates List of Appendices Bibliography Index
Sectored DRAM: A Practical Energy-Efficient and High-Performance Fine-Grained DRAM Architecture

We propose Sectored DRAM, a new, low-overhead DRAM substrate that reduces wasted energy by enabling fine-grained DRAM data transfers and DRAM row activation. Sectored DRAM leverages two key ideas to enable fine-grained data transfers and row activation at low chip area cost. First, a cache block transfer between main memory and the memory controller happens in a fixed number of clock cycles where only a small portion of the cache block (a word) is transferred in each cycle. Sectored DRAM augments the memory controller and the DRAM chip to execute cache block transfers in a variable number of clock cycles based on the workload access pattern with minor modifications to the memory controller's and the DRAM chip's circuitry. Second, a large DRAM row, by design, is already partitioned into smaller independent physically isolated regions. Sectored DRAM provides the memory controller with the ability to activate each such region based on the workload access pattern via small modifications to the DRAM chip's array access circuitry. Activating smaller regions of a large row relaxes DRAM power delivery constraints and allows the memory controller to schedule DRAM accesses faster. Compared to a system with coarse-grained DRAM, Sectored DRAM reduces the DRAM energy consumption of highly-memory-intensive workloads by up to (on average) 33% (20%) while improving their performance by up to (on average) 36% (17%). Sectored DRAM's DRAM energy savings, combined with its system performance improvement, allows system-wide energy savings of up to 23%. Sectored DRAM's DRAM chip area overhead is 1.7% the area of a modern DDR4 chip. We hope and believe that Sectored DRAM's ideas and results will help to enable more efficient and high-performance memory systems. To this end, we open source Sectored DRAM at https://github.com/CMU-SAFARI/Sectored-DRAM.
The Effects of Abiotic Climate Change Factors on Aphid Life History and Populations

iii ACKNOWLEDGMENTS . iv LIST OF TABLES . vi LIST OF FIGURES . vii CHAPTER 1. THE MANY FACES OF CLIMATE CHANGE: THE BIOLOGICAL RESPONSE TO CHANGING ABIOTIC FACTORS APART FROM AVERAGE TEMPERATURE .
Semi-Supervised Deep Sobolev Regression: Estimation, Variable Selection and Beyond

We propose SDORE, a semi-supervised deep Sobolev regressor, for the nonparametric estimation of the underlying regression function and its gradient. SDORE employs deep neural networks to minimize empirical risk with gradient norm regularization, allowing computation of the gradient norm on unlabeled data. We conduct a comprehensive analysis of the convergence rates of SDORE and establish a minimax optimal rate for the regression function. Crucially, we also derive a convergence rate for the associated plug-in gradient estimator, even in the presence of significant domain shift. These theoretical findings offer valuable prior guidance for selecting regularization parameters and determining the size of the neural network, while showcasing the provable advantage of leveraging unlabeled data in semi-supervised learning. To the best of our knowledge, SDORE is the first provable neural network-based approach that simultaneously estimates the regression function and its gradient, with diverse applications including nonparametric variable selection and inverse problems. The effectiveness of SDORE is validated through an extensive range of numerical simulations and real data analysis.
Timeline-based Process Discovery

A key concern of automatic process discovery is to provide insights into performance aspects of business processes. Waiting times are of particular importance in this context. For that reason, it is surprising that current techniques for automatic process discovery generate directly-follows graphs and comparable process models, but often miss the opportunity to explicitly represent the time axis. In this paper, we present an approach for automatically constructing process models that explicitly align with a time axis. We exemplify our approach for directly-follows graphs. Our evaluation using two BPIC datasets and a proprietary dataset highlight the benefits of this representation in comparison to standard layout techniques.
Hold 'em and Fold 'em: Towards Human-scale, Feedback-Controlled Soft Origami Robots

An underdeveloped capability in soft robotics is proprioceptive feedback control, where soft actuators can be sensed and controlled using only sensors on the robot's body. Additionally, soft actuators are often unable to support human-scale loads due to the extremely compliant materials in use. Developing both feedback control and the ability to actuate under large loads (e.g. 500 N) are key capacities required to move soft robotics into everyday applications. In this work, we independently demonstrate these key factors towards controlling and actuating human-scale loads: proprioceptive (embodied) feedback control of a soft, pneumatically-actuated origami robot; and actuation of these origami origami robots under a person's weight in an open-loop configuration. In both demonstrations, the actuators are controlled by internal fluidic pressure. Capacitive sensors patterned onto the robot provide position estimation and serve as input to a feedback controller. We demonstrate position control of a single actuator during stepped setpoints and sinusoidal trajectory following, with root mean square error (RMSE) below 4 mm. We also showcase the actuator's potential towards human-scale robotics as an"origami balance board"by joining three actuators into an open-loop controlled system with a platform that varies its height, roll, and pitch. This work contributes to the field of soft robotics by demonstrating closed-loop feedback position control without visual tracking as an input and lightweight, soft actuators that can support a person's weight. The project repository, including videos, CAD files, and ROS code, is available at https://parses-lab.github. io/kresling_control.
On The Potential of The Fractal Geometry and The CNNs Ability to Encode it

The fractal dimension provides a statistical index of object complexity by studying how the pattern changes with the measuring scale. Although useful in several classification tasks, the fractal dimension is under-explored in deep learning applications. In this work, we investigate the features that are learned by deep models and we study whether these deep networks are able to encode features as complex and high-level as the fractal dimensions. Specifically, we conduct a correlation analysis experiment to show that deep networks are not able to extract such a feature in none of their layers. We combine our analytical study with a human evaluation to investigate the differences between deep learning networks and models that operate on the fractal feature solely. Moreover, we show the effectiveness of fractal features in applications where the object structure is crucial for the classification task. We empirically show that training a shallow network on fractal features achieves performance comparable, even superior in specific cases, to that of deep networks trained on raw data while requiring less computational resources. Fractals improved the accuracy of the classification by 30% on average while requiring up to 84% less time to train. We couple our empirical study with a complexity analysis of the computational cost of extracting the proposed fractal features, and we study its limitation.