Miracle-dz/UniFAR-FTUs huggingface dataset:
An Agricultural Data Platform iStar Model

Organizations increasingly rely on external data and service exchange within business networks in order to fuel their analytics and artificial intelligence needs. In Industry 4.0 practices, new ecosystems have evolved, where data and service provisioning often happens within dedicated platforms. Hereby, the challenge lies in ensuring the data sovereignty of enterprises in terms of self-determination with regard to the use of their data. While conceptual modeling of these platforms inhabits a large number of opportunities, for instance, including automated generation of access policies, research in this area is scarce. To this end, we propose a bottom-up approach using the iStar 2.0 modeling language. In this paper, we first introduce a model describing the market participants of a data and service exchange platform in the realm of smart farming. We then generalize and provide a formalization of relevant aspects in a broader context. The resulting models serve both as a basis for discussion on the requirements analysis level and as fundamental groundwork for further value generation in the area of data sovereignty in complex cross-organizational settings.
Can Applications Recover from fsync Failures?

We analyze how file systems and modern data-intensive applications react to fsync failures. First, we characterize how three Linux file systems (ext4, XFS, Btrfs) behave in the presence of failures. We find commonalities across file systems (pages are always marked clean, certain block writes always lead to unavailability) as well as differences (page content and failure reporting is varied). Next, we study how five widely used applications (PostgreSQL, LMDB, LevelDB, SQLite, Redis) handle fsync failures. Our findings show that although applications use many failure-handling strategies, none are sufficient: fsync failures can cause catastrophic outcomes such as data loss and corruption. Our findings have strong implications for the design of file systems and applications that intend to provide strong durability guarantees.
Administration of crizotinib via jejunostomy tube: A case report

Crizotinib is an orally available tyrosine kinase inhibitor, approved for treatment of anaplastic lymphoma kinase (ALK) and c-ros oncogene 1 (ROS1) rearrangement-positive non-small cell lung cancer (NSCLC). According to the product leaflet, crizotinib capsules should be swallowed whole, and should not be crushed, dissolved or opened. However, this manner of administration is not always possible. At present, literature is lacking regarding the absorption of crizotinib via percutaneous endoscopic jejunostomy (PEJ) tube. We report a case of a patient with ALK+ NSCLC who was administered crizotinib via PEJ tube. An adequate steady state crizotinib trough concentration was reached, resulting in a metabolic response. Safety for the caregiver was ensured since the administration of crizotinib was made without crushing or opening the capsule. This case supports the option for providing crizotinib via PEJ tube in patients who have ALK+ NSCLC and are unable to swallow whole capsules. This option might also apply to the administration of other ALK inhibitors. Keywords: Crizotinib, ALK inhibitor, percutaneous endoscopic jejunostomy tube, pharmacokinetics, non-small cell lung cancer.
Indoor Positioning Using PnP Problem on Mobile Phone Images

As people grow accustomed to effortless outdoor navigation, there is a rising demand for similar possibilities indoors as well. Unfortunately, indoor localization, being one of the requirements for navigation, continues to be a problem without a clear solution. In this article, we are proposing a method for an indoor positioning system using a single image. This is made possible using a small preprocessed database of images with known control points as the only preprocessing needed. Using feature detection with the SIFT (Scale Invariant Feature Transform) algorithm, we can look through the database and find an image that is the most similar to the image taken by a user. Such a pair of images is then used to find coordinates of a database of images using the PnP problem. Furthermore, projection and essential matrices are determined to calculate the user image localization—determining the position of the user in the indoor environment. The benefits of this approach lie in the single image being the only input from a user and the lack of requirements for new onsite infrastructure. Thus, our approach enables a more straightforward realization for building management.
Extended Reality in Spatial Sciences: A Review of Research Challenges and Future Directions

This manuscript identifies and documents unsolved problems and research challenges in the extended reality (XR) domain (i.e., virtual (VR), augmented (AR), and mixed reality (MR)). The manuscript is structured to include technology, design, and human factor perspectives. The text is visualization/display-focused, that is, other modalities such as audio, haptic, smell, and touch, while important for XR, are beyond the scope of this paper. We further narrow our focus to mainly geospatial research, with necessary deviations to other domains where these technologies are widely researched. The main objective of the study is to provide an overview of broader research challenges and directions in XR, especially in spatial sciences. Aside from the research challenges identified based on a comprehensive literature review, we provide case studies with original results from our own studies in each section as examples to demonstrate the relevance of the challenges in the current research. We believe that this paper will be of relevance to anyone who has scientific interest in extended reality, and/or uses these systems in their research.
The Construction of a Virtual Backbone with a Bounded Diameter in a Wireless Network

We usually use a digraph to represent a wireless network (WN). Correspondingly, a connected dominating set (CDS) of the digraph is usually used to denote a virtual backbone (VB) of the corresponding WN. In this article, focusing on the problem of a minimum strongly connected dominating and absorbing set (MSCDAS) with a bounded diameter (or guaranteed routing cost) for a digraph, which is strongly connected, we introduce two algorithms. One is called the guaranteed routing cost strongly connected dominating and absorbing set (GOC-SCDAS), which can generate a strongly connected dominating and absorbing set (SCDAS) with a performance ratio 14:4ðk + ð1/2ÞÞ in respect of the optimal solution. Another is called the α guaranteed routing cost strongly connected bidirectional dominating and absorbing set (α-GOC-SCBDAS), which can generate a strongly connected bidirectional dominating and absorbing set (SCBDAS) with a performance ratio 8:844ð3k + ð1/2ÞÞðk + ð1/2ÞÞ in respect of the optimal solution and a better routing cost, where k = rmax/rmin and 1⁄2rmin, rmax is the transmission range of nodes in the network. Through the simulation experiments, we obtain the conclusion that in terms of the diameter and average routing path length (ARPL) of CDS, the outputs of our algorithms are better than those of the algorithm in (Du et al. 2006).
Biot-Granier Sensor: A Novel Strategy to Measuring Sap Flow in Trees

The Biot-Granier (Gbt) is a new thermal dissipation-based sap flow measurement methodology, comprising sensors, data management and automatic data processing. It relies on the conventional Granier (Gcv) methodology upgraded with a modified Granier sensor set, as well as on an algorithm to measure the absolute temperatures in the two observation points and perform the Biot number approach. The work described herein addresses the construction details of the Gbt sensors and the characterization of the overall performance of the Gbt method after comparison with a commercial sap flow sensor and independent data (i.e., volumetric water content, vapor pressure deficit and eddy covariance technique). Its performance was evaluated in three trials: potted olive trees in a greenhouse and two vineyards. The trial with olive trees in a greenhouse showed that the transpiration measures provided by the Gbt sensors showed better agreement with the gravimetric approach, compared to those provided by the Gcv sensors. These tended to overestimate sap flow rates as much as 4 times, while Gbt sensors overestimated gravimetric values 1.5 times. The adjustments based on the Biot equations obtained with Gbt sensors contribute to reduce the overestimates yielded by the conventional approach. On the other hand, the heating capacity of the Gbt sensor provided a minimum of around 7 °C and maximum about 9 °C, contrasting with a minimum around 6 °C and a maximum of 12 °C given by the Gcv sensors. The positioning of the temperature sensor on the tip of the sap flow needle proposed in the Gbt sensors, closer to the sap measurement spot, allow to capture sap induced temperature variations more accurately. This explains the higher resolution and sensitivity of the Gbt sensor. Overall, the alternative Biot approach showed a significant improvement in sap flow estimations, contributing to adjust the Granier sap flow index, a vulnerability of that methodology.
Robust Proportionate Adaptive Filter Architectures Under Impulsive Noise

This brief proposes robust adaptive filtering algorithms and their VLSI architectures for sparse system identification under impulsive noise. Several robust algorithms are derived by combining error nonlinear adaptive filtering algorithms with proportionate adaptation. We make a comparative study of the derived algorithms and their VLSI architectures in terms of convergence rate and hardware complexity to show that the hardware overhead is negligible for the achieved improvement in robustness.
Spatial and temporal variation in the light environment of developing Scots pine stands: the basis for a quick and efficient method of characterizing light

Spatial and temporal variations in photosynthetic photon flux density (PPFD) at 1 m above the forest floor were measured under and between dominant pines and in 21- to 52-m2 gaps under developing Scots pine (Pinussylvestris L.) stands in southern Finland. For each stand, PPFD data were collected continuously every 10-s and then averaged for every 5-min period during 4-6 days under completely clear and overcast sky conditions. Measurements were made during 102 consecutive days within two different areas in each of 10 different Scots pine stands ranging in age from 7 to 105 years. Mean daily percent PPFD in the understory varied from 7.5% in the 20-year-old stands to 38% in the 7-year-old stands, and did not differ significantly between completely clear and overcast sky conditions. Mean daily percent PPFD did not vary significantly between the different sensor locations within closed pine stands, indicating that at high latitudes mean daily percent PPFD does not vary much spatially under closed Scots pine f.
A Logistic Regression Analysis of Factors Affecting Enrollment Decisions of Prospective Students of Distance Education Programs in Anadolu University

Some prospective students placed by the Assessment, Selection and Placement Center (OSYM) to associate and undergraduate programs in the Faculty of Open Education of Anadolu University enroll in these programs, while others do not. A decision to enroll may be affected by the following variables: the prospective student’s gender, educational status, plans for retaking the university entrance exam, the number of times they took the entrance exam, marital status, employment status, household income, parents’ level of education, and age. The aim of this study is to use the above-mentioned variables to develop a model that will help classify prospective students placed on the distance education programs of Anadolu University into two groups, i.e. students who are more likely to enroll and those who are not; and to discuss the potential benefits of the model in the administrative processes. Students assigned by OSYM in the 2015-2016 academic year to the distance education programs of Anadolu University comprise the population of this study, which is a finite population consisting of 178.229 people. Data were collected via an online survey. The survey included items on demographics, enrollment status, and the above-mentioned variables. A total of 1.829 students completed the survey, of which 1.117 enrolled and 712 did not. Data were analyzed using the SPSS 22.0 software package. Binary logistic regression analysis was used to develop a model to classify the students as enrollees and non-enrollees. Education status, marital status, plans to retake the university entrance exam, the number of times the entrance exam was taken, employment status, and age were found to affect the prospective students’ decision to enroll.
Nitrate assimilation and translocation by higher plants: Comparative physiology and ecological consequences

Revue des resultats recents obtenus sur le role des nitrates en tant que compose osmotique intracellulaire, sur le bilan energetique de l'assimilation des nitrates par les tiges ou les racines et sur le cout energetique comparatif en tant que facteur de l'ecophysiologie des vegetaux
CompoundFS: Compounding I/O Operations in Firmware File Systems

We introduce CompoundFS, a ﬁrmware-level ﬁle system that combines multiple ﬁlesystem I/O operations into a single compound operation to reduce software overheads. The overheads include frequent interaction (e.g., system calls), data copy, and the VFS overheads between user-level application and the storage stack. Further, to exploit the compute capability of modern storage, CompoundFS also provides a capability to ofﬂoad simple I/O data processing operations to the device-level CPUs, which further provides an opportunity to reduce interaction with the ﬁlesystem, move data, and free-up host CPU for other operations. Preliminary evaluation of Com-poundFS against the state-of-the-art user-level, kernel-level, and ﬁrmware-level ﬁle systems using microbenchmarks and a real-world application shows up to 178% and 75% performance gains, respectively.
BASTION: A Security Enforcement Network Stack for Container Networks

In this work, we conduct a security analysis of container networks, identifying a number of concerns that arise from the exposure of unnecessary network operations by containerized applications and discuss their implications. We then present a new high-performance security enforcement network stack, called BASTION, which extends the container hosting platform with an intelligent container-aware communication sandbox. BASTION introduces (i) a network visibility service that provides fine-grained control over the visible network topology per container application, and (ii) a traffic visibility service, which securely isolates and forwards inter-container traffic in a point-to-point manner, preventing the exposure of this traffic to other peer containers. Our evaluation demonstrates how BASTION can effectively mitigate several adversarial attacks in container networks while improving the overall performance up to 25.4% within single-host containers, and 17.7% for cross-host container communications.
go-pmem: Native Support for Programming Persistent Memory in Go

Persistent memory offers persistence and byte-level ad-dressability at DRAM-like speed. Operating system support and some user-level library support for persistent memory programming has emerged. But we think lack of native programming language support is an impediment to a programmer’s productivity. This paper contributes go-pmem , an open-source extension to the Go language compiler and runtime that natively supports programming persistent memory. go-pmem extends Go to introduce a runtime garbage collected persistent heap. Often persistent data needs to be updated in a transactional (i.e., crash consistent) manner. To express transaction boundaries, go-pmem introduces a new txn block which can include most Go statements and function calls. go-pmem compiler uses static type analysis to log persistent updates and avoid logging volatile variable updates whenever possible. To guide our design and validate our work, we developed a feature-poor Redis server go-redis-pmem using go-pmem . We show that go-redis-pmem offers more than 5x through-put than unmodiﬁed Redis using a high-end NVMe SSD on memtier benchmark and can restart up to 20x faster than unmodiﬁed Redis after a crash. In addition, using compiler microbenchmarks, we show go-pmem ’s persistent memory allocator performs up to 40x better and transactions up to 4x faster than commercial libraries like PMDK and previous work like Mnemosyne.
Anti-Proliferative Activity of Extracts from Thai Plantsin Guttiferae and Schisandraceae Families on HumanCancer Cell Lines

Abstract Twenty-two methanol and chloroform crude extracts from Guttiferae (Hypericum hookerianum. Wight & Arn; Garcinia speciosa. Wall; Garcinia xanthochymus. Hook. F. ex T. Anderson; Cratoxylum formosum. subsp. pruniflorum. (Kurz) Gogel; and Calophyllum polyanthum. Wall ex Choisy) and Schisandraceae families (Schisandra verruculosa. Gagnap) collected from the northern region of Thailand were tested for antiproliferative activity on B16F10 (melanoma), HeLa (cervical carcinoma), and KB (epidermoid carcinoma) human cancer cell lines using the sulforhodamine-B (SRB) binding assay. All crude extracts showed an interesting antiproliferative activity with a dose-response relationship. The chloroform extract from leaves of G. speciosa. was the most potent in inhibiting cancer cell growth with the GI50 of 4, 6.6, and 3.7 µg/mL in HeLa, KB, and B16F10 cell lines, which were 13-, 20- and 142-fold less potent than doxurubicin, respectively. The information from this study can explain the use of these plants in Thai traditional medicine and suggests the potential for further development of these extracts to new pharmaceuticals.
Brain Lipid Peroxidation and Antioxidant Status After Acute Methacrylonitrile Intoxication

The status of brain antioxidant enzymes and glutathione in methacrylonitrile (MeAN)-intoxicated Wistar rats was correlated with the levels of lipid peroxidation products. Optimum changes were observed 30 min and 60 min after oral administration of MeAN at dosages of 50 mg/kg body weight per day (0.25 LD50) and 100 mg/kg body weight per day (0.5 LD50). An increase in lipid peroxidation products, decrease in the activity of antioxidant enzymes such as superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPX), glutathione reductase (GR), glutathione S-transferase (GST), and decrease in reduced glutathione (GSH) were observed. These studies suggest that the membrane lipid peroxidation observed in MeAN intoxication is related, in part, to a compromised antioxidant defense system.
An Efficient Algorithm for Extracting High-Utility Hierarchical Sequential Patterns

High-utility sequential pattern mining (HUSPM) is an emerging topic in data mining, where utility is used to measure the importance or weight of a sequence. However, the underlying informative knowledge of hierarchical relation between different items is ignored in HUSPM, which makes HUSPM unable to extract more interesting patterns. In this paper, we incorporate the hierarchical relation of items into HUSPM and propose a two-phase algorithm MHUH, the first algorithm for high-utility hierarchical sequential pattern mining (HUHSPM). In the first phase named Extension, we use the existing algorithm FHUSpan which we proposed earlier to efficiently mine the general high-utility sequences (g-sequences); in the second phase named Replacement, we mine the special high-utility sequences with the hierarchical relation (s-sequences) as high-utility hierarchical sequential patterns from g-sequences. For further improvements of efficiency, MHUH takes several strategies such as Reduction, FGS, and PBS and a novel upper bounder TSWU, which will be able to greatly reduce the search space. Substantial experiments were conducted on both real and synthetic datasets to assess the performance of the two-phase algorithm MHUH in terms of runtime, number of patterns, and scalability. Conclusion can be drawn from the experiment that MHUH extracts more interesting patterns with underlying informative knowledge efficiently in HUHSPM.
Terrain Analysis in Google Earth Engine: A Method Adapted for High-Performance Global-Scale Analysis

Terrain analysis is an important tool for modeling environmental systems. Aiming to use the cloud-based computing capabilities of Google Earth Engine (GEE), we customized an algorithm for calculating terrain attributes, such as slope, aspect, and curvatures, for different resolution and geographical extents. The calculation method is based on geometry and elevation values estimated within a 3 × 3 spheroidal window, and it does not rely on projected elevation data. Thus, partial derivatives of terrain are calculated considering the great circle distances of reference nodes of the topographic surface. The algorithm was developed using the JavaScript programming interface of the online code editor of GEE and can be loaded as a custom package. The algorithm also provides an additional feature for making the visualization of terrain maps with a dynamic legend scale, which is useful for mapping different extents: from local to global. We compared the consistency of the proposed method with an available but limited terrain analysis tool of GEE, which resulted in a correlation of 0.89 and 0.96 for aspect and slope over a near-global scale, respectively. In addition to this, we compared the slope, aspect, horizontal, and vertical curvature of a reference site (Mount Ararat) to their equivalent attributes estimated on the System for Automated Geospatial Analysis (SAGA), which achieved a correlation between 0.96 and 0.98. The visual correspondence of TAGEE and SAGA confirms its potential for terrain analysis. The proposed algorithm can be useful for making terrain analysis scalable and adapted to customized needs, benefiting from the high-performance interface of GEE.
Taxonomy of plant genetic resources - use of morphological, molecular and phytochemical data in order to verify existing classifications.

Summary Taxonomy of plant genetic resources is an important input in characterising and evaluating cultivated plants and it is essential for identifi cation and documentation of the diversity of genebank collections. In former times taxonomical determination was based only on morphological characters. Nowadays, new molecular and chemical methods and techniques are available for providing additional information. As examples of the interaction of morphological, molecular and phytochemical data, investigations of a parsley (Petroselinum crispum [Mill.] Nyman, Apiaceae) and an opium poppy (Papaver somniferum L., Papaveraceae) collection of the German genebank are demonstrated. 220 parsley and 300 opium poppy accessions were cultivated and described morphologically. In addition, the molecular distance and the phylogenetic relationship of the accessions were performed with molecular marker analysis. Essential oil compound and content for parsley and the content of the fi ve main alkaloids (morphine, codeine, thebaine, noscapine, papaverine) for opium poppy were measured with GC (gas chromatography) and HPLC (high pressure liquid chromatography), respectively. For parsley the results of the three methods support the existing taxonomy partly, a separation of root and leaf parsley was confi rmed. However, the taxonomy of opium poppy should be revised because molecular and chemical data do not verify the morphological results. But nevertheless taxonomy of cultivated plants is an important tool to describe the variability of plant genetic resources.