Miracle-dz/UniFAR-FTUs huggingface dataset:
FloreView: An Image and Video Dataset for Forensic Analysis

Linking a digital image or video to its originating device, or checking the content integrity still represent challenging forensic tasks. Even though several technologies based on metadata, file format, and sensor noise have been developed to address these problems, current methods are frequently made obsolete by new customized acquisition pipelines implemented by manufacturers. Therefore, to assess the performance of the available tools and push the research activity, researchers continuously need new datasets containing contents captured with recent technologies. In this paper, we present a new image and video dataset for forensic analysis. Data, acquired by the most recent acquisition devices, were collected under strictly controlled procedures designed to limit the bias induced by differences in the acquisition process between different devices. The dataset includes over 9000 media contents captured by 46 smartphones of 11 major brands. For each device, we collected at least 100 unique natural images, 30 unique natural videos, 30 flat images, and 4 flat videos. Great care has been taken in collecting data that can be used for multiple forensic tasks; moreover, images and videos have been carefully organized so that FloreView could be used by the community immediately and effortlessly. Finally, two case studies related to image source identification and video brand identification have been performed, using state-of-the-art methods, to show how the proposed dataset can be effectively used for forensic tasks.
Polyetheretherketone Material in Dentistry

A polyaromatic nearly-crystalline thermoplastic polymer, polyetheretherketone (PEEK), has become a useful biomaterial and its use has increased in dentistry because of its properties. PEEK is scientifically approved and is among the safest material used to restore lost orofacial tissues at present. PEEK has a property of high biocompatibility, therefore there is increased utilization of PEEK in orthopaedic and trauma cases. PEEK has several excellent properties due to which it has been used in several fields of dentistry such as orthodontic wires, implants, removable dentures, fixed partial dentures, finger prostheses, temporary abutments, implant-supported provisional crowns, healing caps, maxillofacial prostheses, etc. Due to its modification, PEEK material is used more frequently in clinical dentistry. PEEK can be used as a material that is not traditional in the realm of dental care. Modification of PEEK has led to an increase in its use in the field of dentistry.
Photonic integrated circuit model for phased antenna array beam steering

The up-to-the-date electrical systems for beamsteering of the phased antenna arrays are widely used; however, possessing significant drawbacks, including high losses, electromagnetic interference, and high power consumption. To overcome these challenges, microwave photonic systems, both discrete and integrated, have demonstrated outstanding potential. In this context, we discuss the two primary methods for beamsteering, i.e., true time delay (TTD) and phase shift (PS). This paper provides simulation results for a four-channel photonic integrated circuit (PIC) for beamsteering based on the TTD method. The PIC design could be implemented on any fabrication platform. The results demonstrate the approach’s feasibility and its potential to improve the performance of phased array antenna systems.
The Importance of Semen Quality in AI Programs and Advances in Laboratory Analyses for Semen Characteristics Assessment

In the last decades, livestock sector has undergone a process of biotechnology incorporation with the main goal of enhancing productivity and improving the genetic makeup. In this sense, artificial insemination (AI) is considered as the most important biotechnology incorporated into livestock production systems because it implies the use and/or globalization of proven bulls, which represent a key tool in obtaining animals with higher genetic merit [1].
ANALISIS PENGARUH HARI PERDAGANGAN TERHADAP RETURN SAHAM PADA PERUSAHAAN MANUFAKTUR DI BURSA EFEK JAKARTA

Day of the week effect merupakan suatu bentuk fenomena yang merupakan bentuk penyimpangan terhadap bentuk pasar modal yang efisien, di mana rata-rata return antara hari-hari dalam satu minggu berbeda. Tujuan penelitian ini adalah untuk mengetahui apakah terdapat pengaruh hari perdagangan pada perusahaan manufaktur di Bursa Efek Jakarta periode 2004. Penelitian ini menggunakan data sekunder yang berupa data harga saham per hari perusahaan manufaktur yang go public di Bursa Efek Jakarta yang diperoleh dari Indonesian Capital Market Directory. Sampel yang diambil sebanyak 58 perusahaan. Untuk menguji hipotesis yang ditetapkan digunakan alat analisis regresi berganda dengan menggunakan dummy variable. Berdasar uji regresi berganda dengan menggunaan dummy variable diperoleh hasil konstanta (α) bernilai positif sedangkan kofisien regresi (β1 … β11) bernilai negatif atau lebih kecil konstanta (α), hal ini menunjukkan bahwa return rata-rata di bulan Januari memang lebih tinggi dibandingkan dengan return rata-rata di bulan-bulan yang lain. Pada bulan November diperoleh nilai koefisien regresi (β10) bernilai > nilai konstanta (α), hal ini disebabkan pada bulan November pengaruh hari raya Idul Fitri didukung dengan stabilitas ekonomi, iklim politik yang stabil, melemahnya dolar Amerika Serikat atas mata uang dunia, serta turunnya harga minyak dunia sehingga membuat para investor bersemangat untuk melakukan transaksi di Bursa Jakarta. Dengan demikian hipotesis yang menyatakan terdapat January Effect pada perusahaan manufaktur di Bursa Efek Jakarta terbukti pada penelitian ini.
Poseidon-3 Radar Altimeter: New Modes and In-Flight Performances

On June 20, 2008, the altimetry satellite Jason-2 was launched from the Vandenberg site in California. Dedicated to the measure of ocean surface topography, one of the main instruments on-board is a radar altimeter, Poseidon-3, which essentially measures the altimetric range between the spacecraft and the surface. Poseidon-3 is a dual frequency radar altimeter operating in Ku and C bands, very similar to its predecessor Poseidon-2 on-board Jason-1. However some significant improvements have been implemented to improve its tracking capabilities over coastal and inland waters, that is, its capacity to maintain data acquisition over land or mixed land-sea terrain. The performance assessment is excellent: the range measurement accuracy is close to 1.5 cm for 1s averaging and the significant wave height (SWH) noise is less than 12 cm (for a 2m SWH at 1σ). In terms of range, the short-term drift (along an orbit) is around 1 mm, and the long-term drift is negligible so far. The tracking success is close to 100% over oceans and 80% over land surfaces, the new acquisition and tracking modes inducing significantly higher data availability in comparison with Poseidon-2. We assess Poseidon-3 main improvements, with the presentation of the new modes of echo acquisition and tracking: the median tracking algorithm, DIODE/DORIS acquisition, and the coupling between DIODE and digital elevation model (DEM) information. The median tracking algorithm is shown to reinforce the robustness of the altimetry echoes outside the standard Brown conditions. DIODE acquisition mode increases data availability in land-to-water transitions, providing up to 5 km of extra measurements along track, which constitutes an asset for coastal and small water areas (lakes, rivers) observations. Both are now implemented as the default mode on Jason-2. DIODE/DEM mode remains experimental and requires further adjustments but shows promising features such as acquisition of water surfaces in rough terrain.
Motion Sickness in Self-Driving Vehicles

Motion sickness is expected to be more of an issue in self-driving vehicles than in conventional vehicles. The reason is that the three main factors contributing to motion sickness (conflict between vestibular and visual inputs, inability to anticipate the direction of motion, and lack of control over the direction of motion) are elevated in self-driving vehicles. However, the frequency and severity of motion sickness is influenced by the activity that one would be involved in instead of driving. This report calculates the expected frequency and severity of motion sickness in fully self-driving vehicles based on the expected frequencies of different activities from a recent survey of what individuals would be likely to do in a fully self-driving vehicle—a survey performed in the U.S., China, India, Japan, the U.K., and Australia. The results indicate that, for example, 6%-10% of American adults riding in fully self-driving vehicles would be expected to often, usually, or always experience some level of motion sickness. Analogously, 6%-12% of American adults riding in fully self-driving vehicles would be expected to experience moderate or severe motion sickness at some time. Calculations for the other five countries are also presented. The report concludes with a discussion of ways to minimize the frequency and severity of motion sickness in self-driving vehicles.
Exploring Psychological Constructs in People Receiving Treatment for Addictive Eating Behaviours: “I Hate Loving Food as Much as I Do”

Research into the complexities of addictive eating behaviours continues to develop, as a deeper understanding of this construct beyond self-report diagnostic tools emerges. In this study, we undertook structured interviews with 40 participants engaged in a personality-based management program for addictive eating, to gain insight into what situations lead people with addictive eating behaviours to overeat, and how they believe their lives would be different if they had control over their eating. A phenomenological analysis to explore compulsion and control in the context of food experiences for participants was used to construct two main themes of the addictive eating paradox and striving to transition from ‘other’ to ‘normal’. The addictive eating paradox identified multiple contradictory experiences of a situation, e.g., ‘loving food’ but ‘hating food’. Striving to transition from ‘other’ to ‘normal’ encompassed the idea that participants envisaged that by gaining control over their eating they could become ‘normal’. This study emphasises the need to provide support and strategies to help people navigate paradoxical thoughts and presents new ideas to increase the effectiveness of interventions for individuals struggling with the complex self-beliefs held by those with addictive eating behaviours.
Integrating In Vitro and In Silico Approaches to Assess Monotheca buxifolia Plant Extract against Rhipicephalus (Boophilus) microplus and Sarcoptes scabiei

Tick and mite infestations pose significant challenges to animal health, agriculture, and public health worldwide. The search for effective and environmentally friendly acaricidal agents has led researchers to explore natural alternatives. In this study, we investigated the acaricidal potential of the Monotheca buxifolia plant extract against Rhipicephalus microplus ticks and Sarcoptes scabiei mites. Additionally, we employed a computational approach to identify phytochemicals from the extract that could serve as drug candidates against these ectoparasites. The contact bioassay results demonstrated that the M. buxifolia plant extract exhibited significant efficacy against R. microplus and S. scabiei, with higher concentrations outperforming the positive control acaricide permethrin in terms of mite mortality. Time exposure to the extract also showed a positive correlation with better lethal concentration (LC50 and LC90) values. Similarly, the adult immersion test revealed a notable inhibition of tick oviposition via the plant extract, especially at higher concentrations. The two-protein primary structure, secondary structure and stability were predicted using the Expasy’s ProtParam server, SOPMA and SUSUI server, respectively. Using Homology modeling, the 3D structure of the protein was obtained and validated through the ERRAT server, and active sites were determined through the CASTp server. The docking analysis revealed that Alpha-Amyrenyl acetate and alpha-Tocopherol exhibited the highest docking scores for S. scabiei and R. microplus aspartic protease proteins, respectively. These phytochemicals demonstrated strong binding interactions, suggesting their potential as acaricidal drug candidates. In conclusion, the M. buxifolia plant extract displayed significant acaricidal activity against R. microplus and S. scabiei. Moreover, the computational approach identified promising phytochemicals that could serve as potential drug candidates for controlling these ectoparasites.
The problematic nature of agriculture: understanding the perils and pitfalls of improving on nature.

It is our contention that agriculture as an economic activity has not been adequately theorized. As a consequence, the social and ecological roots of agriculture’s accelerating ecological difficulties are misunderstood. They key to theorizing agriculture is the recognition that farming is an effort to create and sustain artificial (man-arranged) ecosystems, of varying degrees of instability, in order to increase what liberal economists would call “the productivity of natural capital. ” This article attempts to develop a systematic model of agriculture which will incorporate 1) a clear delineation of the work processes involved, 2) their particular form of dependence on the biosphere, 3) the source of social pressure towards expansion of production, 4) the particular reasons for the forms of environmental degradation which these cause, and 5) the ecological consequences of this degradation for the continuance of farming itself.
A Real-World Dataset Generator for Specific Emitter Identification

Generating high-quality, real-world, well-labeled datasets for radio frequency machine learning (RFML) applications often proves prohibitively cumbersome and expensive, leading to the low availability of high-fidelity, low-cost datasets. Specific emitter identification (SEI) in particular requires a hardware setup capable of supporting transmitting using many different radios, while automated modulation classification (AMC) performance is primarily driven by SNR, channel effects, and the similarity of modulation types. These factors give rise to the need for scalable methods of inexpensive dataset generation. This paper describes the design considerations and a proof-of-concept implementation of a blind user reconfigurable platform capable of creating SEI and AMC datasets throughout a variety of real-world conditions. This paper additionally describes the reliability and performance of the platform relative to existing real-world data generation methods and compares generated datasets to those already present in the literature. This work also describes the software post-processing steps taken to isolate, label, and cull captured data and transform these into a high-quality dataset.
America's new market geography : nation, region, and metropolis

The age of the great explorers of the New World is long past; its sole remnants are the surveillance satellites which graph the final remaining area uncertainties. The equivalent in our own time of the early geographers' and naturalists' target is the increasing effort to comprehend the dynamics of a society whose complexity makes description, much less prediction, increasingly difficult. Our central cities have suffered enormously in potency and scale. A continuing area phenomenon is the force which has reduced the role of central city in favor of an expanding suburban ring. The regional future is increasingly obscure and the relative status of the United States within the world economy is challenged in every sector. The demand for a vision of the future has never been so great. A whole new economic reality is gradually coming home. How do we place America's prospects in a world context? What regions and cities will win? Lose? Is there a new economic geography or just a pause before the next energy crunch? Is there really a technological imperative? And if so, what are its shape and potency? What does it mean to the developer of real estate, the municipal official, the marketer trying to come to grips with tomorrow's growth dynamics? The collection of papers incorporated into this volume provides data insights generated by some of the best analysts of our time.
Guidelines for Secure Process Control: Harnessing the Power of Homomorphic Encryption and State Feedback Control

The paper presents applications of homomorphic cryptographic schemes in process control. Homomorphic encryption is a particular type of encryption that allows performing mathematical operations over encrypted data. Therefore the user can use third-party services as controllers without revealing any vulnerable information, like process data. Homomorphic properties make it possible to perform data aggregation or evaluate control actions without having any knowledge about the process data. Our paper explores two fully homomorphic cryptographic schemes, namely Brakerski/Fan-Vercauteren (BFV) and Cheon-Kim-Kim-Song (CKKS) cryptosystems. Each scheme is briefly described with its advantages and drawbacks, conditions, and applications. We present a case study involving hl linear-quadratic (LQ) control strategy implemented in an encrypted setup. This serves for comparison and a step-by-step guide for implementing encrypted process control.
Two new Oxynoemacheilus species in western Anatolia (Teleostei, Nemacheilidae)

Oxynoemacheilus sakaryaensissp. nov., is restricted to the Sakarya River basin, and O. melenicussp. nov., is distributed in both the Sakarya River and Büyükmelen Stream. Oxynoemacheilus sakaryaensis is distinguished by having a flank plain or with numerous irregularly shaped pale brownish bars and a caudal-peduncle depth 2.8–3.2 times in its length. Oxynoemacheilus melenicus is distinguished by having a flank with 10–13 irregular shaped brownish bars or blotches and the caudal peduncle depth 1.9–2.8 times in its length. Oxynoemacheilus banarescui, O. samanticus, O. simavicus, O. fatsaensis, O. sakaryaensis, and O. melenicus are valid, which belong to the O. bergianus species group. O. melenicus and O. sakaryaensis were differentiated from all other Oxynoemacheilus species in western Anatolia by two diagnostic and unique nucleotide substitution sites in the COI barcoding region. Also, species delineation tests (ABGD, GMYC, ASAP) and phylogenetic analyses support the validity of O. melenicus and O. sakaryaensis as distinct species.
A prognostic mathematical model based on tumor microenvironment-related genes expression for breast cancer patients

Background Tumor microenvironment (TME) status is closely related to breast cancer (BC) prognosis and systemic therapeutic effects. However, to date studies have not considered the interactions of immune and stromal cells at the gene expression level in BC as a whole. Herein, we constructed a predictive model, for adjuvant decision-making, by mining TME molecular expression information related to BC patient prognosis and drug treatment sensitivity. Methods Clinical information and gene expression profiles were extracted from The Cancer Genome Atlas (TCGA), with patients divided into high- and low-score groups according to immune/stromal scores. TME-related prognostic genes were identified using Kaplan-Meier analysis, functional enrichment analysis, and protein-protein interaction (PPI) networks, and validated in the Gene Expression Omnibus (GEO) database. Least absolute shrinkage and selection operator (LASSO) Cox regression analysis was used to construct and verify a prognostic model based on TME-related genes. In addition, the patients’ response to chemotherapy and immunotherapy was assessed by survival outcome and immunohistochemistry (IPS). Immunohistochemistry (IHC) staining laid a solid foundation for exploring the value of novel therapeutic target genes. Results By dividing patients into low- and high-risk groups, a significant distinction in overall survival was found (p < 0.05). The risk model was independent of multiple clinicopathological parameters and accurately predicted prognosis in BC patients (p < 0.05). The nomogram-integrated risk score had high prediction accuracy and applicability, when compared with simple clinicopathological features. As predicted by the risk model, regardless of the chemotherapy regimen, the survival advantage of the low-risk group was evident in those patients receiving chemotherapy (p < 0.05). However, in patients receiving anthracycline (A) therapy, outcomes were not significantly different when compared with those receiving no-A therapy (p = 0.24), suggesting these patients may omit from A-containing adjuvant chemotherapy. Our risk model also effectively predicted tumor mutation burden (TMB) and immunotherapy efficacy in BC patients (p < 0.05). Conclusion The prognostic score model based on TME-related genes effectively predicted prognosis and chemotherapy effects in BC patients. The model provides a theoretical basis for novel driver-gene discover in BC and guides the decision-making for the adjuvant treatment of early breast cancer (eBC).
Association between Uncertainties in Meteorological Variables and Water-Resources Planning for the State of Texas

Because of the complexity and rapidly occurring changes in the dynamics of human demography and water demands, it is difficult to assess the future adequacy of limited freshwater resources. The planning of water resources largely depends on the meteorological variables (precipitation and evaporation) in terms of their distribution in space and time. Considering precipitation and evaporation as natural input and output without any human intervention for water-resources systems that can be perceived to represent the potential water-resources availability of an area, an uncertainty study was carried out for different water-resources regions in Texas. The entropy method was used for measuring the uncertainty in meteorological variables. It was observed that critical water-deficit regions based on meteorological variables are mostly located in the western part of Texas. The Mann-Kendall test was employed to understand the trend in precipitation, evaporation, and the meteorological excess index (MEI) in deficit.
A spectral library for a semi-arid wetland and its application to studies of wetland degradation using hyperspectral and multispectral data

Semi-arid wetland areas in Central Spain are especially sensitive ecosystems and are considered to be one of the most important areas for the migration and wintering of waterfowl in Europe. Many of these wetland areas are saline or sub saline and are subjected to natural (seasonal) as well as human induced changes. Factors causing changes that significantly alter or modify the ecological function of these wetlands are considered to be degradation processes. The use of hyperspectral and multispectral data together with ground spectra and field studies has a great potential for monitoring wetland conditions. In this work spectral and analytical information concerning soil, vegetation and land use, contained in a site specific spectral library, is linked with the spectral characteristics of components from an anthropogenic influenced wetland area in La Mancha Alta. This information forms the basis for determining and selecting end members from hyperspectral data (DAIS 7915), which are then extrapolated to lower spatial and spectral resolution multispectral Landsat ETM+ and TM data. A spectral unmixing is carried out to obtain a multitemporal analysis for evaluating wetland degradation. Results show that the approach is successful in determining rapid surface change due to anthropogenic influences. Spectral unmixing results present an increase of salt-affected soil and a redistribution of saline pasture. This is further supported with a post classification change detection assessment and ground data confirm that principal causes are changes in wetland use together with water regulation of the Cigüela river.