Miracle-dz/UniFAR-FTUs huggingface dataset:
CONSEL: Connectivity-based segmentation in large-scale 2D/3D sensor networks

A cardinal prerequisite for the system design of a sensor network, is to understand the geometric environment where sensor nodes are deployed. The global topology of a large-scale sensor network is often complex and irregular, possibly containing obstacles/holes. A convex network partition, so-called segmentation, is to divide a network into convex regions, such that traditional algorithms designed for a simple geometric region can be applied. Existing segmentation algorithms highly depend on concave node detection on the boundary or sink extraction on the medial axis, thus leading to quite sensitive performance to the boundary noise. More severely, since they exploit the network's 2D geometric properties, either explicitly or implicitly, so far there has been no general 3D segmentation solution. In this paper, we bring a new view to segmentation from a Morse function perspective, bridging the convex regions and the Reeb graph of a network. Accordingly, we propose a novel distributed and scalable algorithm, named CONSEL, for CONnectivity-based SEgmentation in Large-scale 2D/3D sensor networks. Specifically, several boundary nodes first perform flooding to construct the Reeb graph. The ordinary nodes then compute mutex pairs locally, thereby generating the coarse segmentation. Next the neighbor regions which are not mutex pair are merged together. Finally, by ignoring mutex pairs which leads to small concavity, we provide the constraints for approximately convex decomposition. CONSEL is more desirable compared with previous studies: (1) it works for both 2D and 3D sensor networks; (2) it only relies on network connectivity information; (3) it guarantees a bound for the regions' deviation from convexity. Extensive simulations show that CONSEL works well in the presence of holes and shape variation, always yielding appropriate segmentation results.
Regulation of the Adaptive Immune Response by the IκB Family Protein Bcl-3

Bcl-3 is a member of the IκB family of proteins and an important regulator of Nuclear Factor (NF)-κB activity. The ability of Bcl-3 to bind and regulate specific NF-κB dimers has been studied in great depth, but its physiological roles in vivo are still not fully understood. It is, however, becoming clear that Bcl-3 is essential for the proper development, survival and activity of adaptive immune cells. Bcl-3 dysregulation can be observed in a number of autoimmune pathologies, and Bcl3-deficient animals are more susceptible to bacterial and parasitic infection. This review will describe our current understanding of the roles played by Bcl-3 in the development and regulation of the adaptive immune response, including lymphoid organogenesis, immune tolerance, lymphocyte function and dendritic cell biology.
A new approach to the design of flexible cloud management platforms

Current cloud management platforms have been designed to deal mainly with computing and storage resources. Networking, on the other hand, is often focused only on ensuring basic connectivity between virtual machines. That means, advanced requirements, such as delay and bandwidth guarantees or handing of network control to the customer, are not supported in today's platforms. Another important shortcoming is that resource management strategies are mostly implemented as part of the core of platforms, leaving little or no room for personalization by the operator or the customer. Therefore, in this paper we present the building blocks of a new conceptual architecture of a cloud platform aiming to add advanced yet robust network configuration support and more flexibility at the core of the platform to better fit the needs of each cloud environment.
The Endocannabinoid 2-Arachidonylglycerol Decreases the Immunological Activation of Guinea Pig Mast Cells: Involvement of Nitric Oxide and Eicosanoids

The antigen-induced release of histamine from sensitized guinea pig mast cells was dose-dependently reduced by endogenous (2-arachidonylglycerol; 2AG) and exogenous [(1R,3R,4R)-3-[2-hydroxy-4-(1,1-dimethylheptyl)phenyl]-4-(3-hydroxypropyl)cyclohexan-1-ol (CP55,940)] cannabinoids. The inhibitory action afforded by 2AG and CP55,940 was reversed by N-[(1S)-endo-1,3,3-trimethylbicyclo[2.2. 1]heptan-2-yl]5-(4-chloro-3-methylphenyl)-1-(4-methylbenzyl)pyrazole-3-carboxamide (SR144528), a selective cannabinoid 2 (CB2) receptor antagonist, and left unchanged by the selective CB1 antagonist N-(piperidin-1-yl)-5-(4-iodophenyl)-1-(2,4-dichlorophenyl)-4-methyl-1H-pyrazole-3-carboxamide (AM251). The inhibitory action of 2AG and CP55,940 was reduced by the unselective nitric-oxide synthase (NOS) inhibitor N-monomethyl-l-arginine methylester (l-NAME) and reinstated by l-arginine, the physiological substrate. The inhibitory action of 2AG and CP55,940 was also reduced by the unselective cyclooxygenase (COX) inhibitor indomethacin and the selective COX-2 blocker rofecoxib. Both 2AG and CP55,940 significantly increased the production of nitrite from mast cells, which was abrogated by l-NAME and N-(3-(aminomethyl)benzyl)acetamidine (1400W), a selective inducible NOS (iNOS) inhibitor. Nitrite production consistently paralleled a CP55,940-induced increase in the expression of iNOS protein in mast cells. Both 2AG and CP55,940 increased the generation of prostaglandin E2 from mast cells, which was abrogated by indomethacin and rofecoxib and parallel to the CP55,940-induced expression of COX-2 protein. Mast cell challenge with antigen was accompanied by a net increase in intracellular calcium levels. Both cannabinoid receptor ligands decreased the intracellular calcium levels, which were reversed by SR144528 and l-NAME. In unstimulated mast cells, both ligands increased cGMP levels. The increase was abrogated by SR144528, l-NAME, indomethacin, and rofecoxib. Our results suggest that 2AG and CP55,940 decreased mast cell activation in a manner that is susceptible to a CB2 receptor antagonist and to inhibition of nitric oxide and prostanoid pathways.
Prevalence, Pathophysiology, Screening and Management of Osteoporosis in Gastric Cancer Patients

Osteoporosis in gastric cancer patients is often overlooked or even neglected despite its high prevalence in these patients. Considering that old age, malnutrition, chronic disease, chemotherapy, decreased body mass index and gastrectomy are independent risk factors for osteoporosis, it is reasonable that the prevalence of osteoporosis in gastric cancer patients would be high. Many surviving patients suffer from back pain and pathological fractures, which are related to osteoporosis. Fractures have obvious associated morbidities, negative impact on quality of life, and impose both direct and indirect costs. In the era of a >55.6% 5-year survival rate of gastric cancer and increased longevity in gastric cancer patients, it is very important to eliminate common sequelae such as osteoporosis. Fortunately, the diagnosis of osteoporosis is well established and many therapeutic agents have been shown to be effective and safe not only in postmenopausal females but also in elderly males. Recently, effective treatments of gastric cancer patients with osteoporosis using bisphosphonates, which are commonly used in postmenopausal woman, were reported.
Complex mixture toxicity for single and multiple species: Proposed methodologies

Methods for the assessment of ecological risks associated with exposure to defined mixtures of toxicants are reviewed and formalized for single‐species toxicity. Depending on the modes of action of toxicants in a mixture, these methods apply either the model for concentration additivity (CA) or the model for response additivity (RA). For complex mixtures, the present paper advocates the use of a new, two‐step, mixed‐model approach as a logical extension of model selection: Mixture toxicity for individual modes of action is evaluated with the CA model, and the toxicities of different modes of action are combined using the RA model. Using comparable mixture toxicity strategies in combination with the concept of species‐sensitivity distributions, we develop a method to address and predict the risk for direct effects on the composition of species assemblages and biodiversity. The data needed for modeling can be obtained from existing databases, and lack of data can, in part, be addressed by the use of toxicity patterns in those databases. Both single‐ and multiple‐species methods of mixture risk prediction are useful for risk management, because they allow ranking of polluted sites and affected species as well as identification of the most hazardous contaminants, at least in a comparative way. Validation of the proposed methods is feasible but currently limited because of a lack of appropriate data.
The role of enterprise systems in supply chain networks: a taxonomy of supply chain strategies

This paper proposes a taxonomy for supply chain integration strategies. The taxonomy is based on the contingencies of supply chain network coupling and the Extended Enterprise Systems (EES) architecture in the supply chain. The purpose of this model is to map the portfolio of relations in the supply chain and to choose the right supply chain strategy. The work is based on a comprehensive study of the Supply Chain Management (SCM) and Enterprise Resource Planning (ERP) literature and the study suggests that there is an emerging new research potential for Enterprise Systems (ES) in the supply chain.
Stable dynamic walking of a quadruped robot “Kotetsu” using phase modulations based on leg loading/unloading

In this study, we intend to show the basis of a general legged locomotion controller with the ability to integrate both posture and rhythmic motion controls and shift continuously from one control method to the other according to the walking speed. The rhythmic motion of each leg in the sagittal plane is generated by a single leg controller which controls the swing-to-stance and stance-to-swing phase transitions using respectively leg loading and unloading information. Since rolling motion induced by inverted pendulum motion during the two-legged stance phases results in the transfer of the load between the contralateral legs, leg loading/unloading involves posture information in the frontal plane. As a result of the phase modulations based on leg loading/unloading, rhythmic motion of each leg is achieved and leg coordination (resulting in a gait) emerges, even without explicit coordination among the leg controllers, allowing to realize dynamic walking in the low- to medium-speed range. But an additional ascending coordination mechanism between ipsilateral leg controllers helps to improve the stability. In this paper, we report the result of experiments using a newly constructed quadruped robot “Kotetsu” in order to verify the results of simulations. Details of trajectory generation and movies can be seen at: http://robotics.mech. kit.ac. jp/kotetsu/.
First Jurassic dinosaur tracksite from Guizhou Province, China: morphology, trackmaker and paleoecology

Abstract Sauropod tracks from the Early Jurassic Maanshan Member of the Ziliujing Formation in the Dazhuanwan area of Guizhou represent the first Jurassic dinosaur track record for this province. The best preserved and longest trackway is narrow gauge (Brontopodus type), and indicates a relatively small trackmaker (footprint length ~35.0 cm). In conjunction with sauropodomorph skeletal remains these tracks suggest that basal sauropodomorphs and primitive sauropods coexisted in this region during the Early Jurassic. This pattern is same in the Lufeng and Sichuan basins. Thus, sauropod tracks from southwest China are diverse in the Early Jurassic, and include narrow gauge Parabrontopodus, wide gauge Brontopodus-type, and basal sauropodomorph tracks.
In Situ Monitoring of Temperature inside Lithium-Ion Batteries by Flexible Micro Temperature Sensors

Lithium-ion secondary batteries are commonly used in electric vehicles, smart phones, personal digital assistants (PDA), notebooks and electric cars. These lithium-ion secondary batteries must charge and discharge rapidly, causing the interior temperature to rise quickly, raising a safety issue. Over-charging results in an unstable voltage and current, causing potential safety problems, such as thermal runaways and explosions. Thus, a micro flexible temperature sensor for the in in-situ monitoring of temperature inside a lithium-ion secondary battery must be developed. In this work, flexible micro temperature sensors were integrated into a lithium-ion secondary battery using the micro-electro-mechanical systems (MEMS) process for monitoring temperature in situ.
Grammaticality, Acceptability, and Probability: A Probabilistic View of Linguistic Knowledge

The question of whether humans represent grammatical knowledge as a binary condition on membership in a set of well-formed sentences, or as a probabilistic property has been the subject of debate among linguists, psychologists, and cognitive scientists for many decades. Acceptability judgments present a serious problem for both classical binary and probabilistic theories of grammaticality. These judgements are gradient in nature, and so cannot be directly accommodated in a binary formal grammar. However, it is also not possible to simply reduce acceptability to probability. The acceptability of a sentence is not the same as the likelihood of its occurrence, which is, in part, determined by factors like sentence length and lexical frequency. In this paper, we present the results of a set of large-scale experiments using crowd-sourced acceptability judgments that demonstrate gradience to be a pervasive feature in acceptability judgments. We then show how one can predict acceptability judgments on the basis of probability by augmenting probabilistic language models with an acceptability measure. This is a function that normalizes probability values to eliminate the confounding factors of length and lexical frequency. We describe a sequence of modeling experiments with unsupervised language models drawn from state-of-the-art machine learning methods in natural language processing. Several of these models achieve very encouraging levels of accuracy in the acceptability prediction task, as measured by the correlation between the acceptability measure scores and mean human acceptability values. We consider the relevance of these results to the debate on the nature of grammatical competence, and we argue that they support the view that linguistic knowledge can be intrinsically probabilistic.
Health Co-Benefits of Climate Change Mitigation Policies

Policies to reduce greenhouse gas emissions in a number of sectors can result in ancillary (co-benefits) for health. In the case of electricity generation, for example, reduced combustion of coal would result in lowered fine particulate air pollution. Improved housing insulation with efficient ventilation systems can reduce indoor air pollution while also reducing exposure to heat and cold extremes. In low-income settings, improved efficiency cookstoves can reduce black carbon emissions and other climate-active pollutants while reducing exposure to hazardous indoor air pollution. Urban transport policies that support active travel and access to affordable public transport can increase physical activity and reduce air pollution. Increased fruit and vegetable consumption and reduced consumption of animal products (particularly from ruminants) in highconsuming populations can improve health and reduce greenhouse gas (GHG) emissions. Finally, addressing reproductive health rights in countries where the need for modern contraception is not fully met can improve the prospects for child and maternal survival and ultimately reduce GHG emissions. Taking into account the value of the health gains and other co-benefits of policies to mitigate climate change can help to offset the costs of such policies and make them more acceptable to decision makers.
Apocynin decreases AGEs-induced stimulation of NF-κB protein expression in vascular smooth muscle cells from GK rats

Abstract Context: Elevated oxidative stress plays a key role in diabetes-associated vascular disease. Excessive production of reactive oxygen species via advanced glycation end products (AGEs) activates peroxisome proliferator-activated receptor gamma (PPARγ) and the transcription factor nuclear factor-kB (NF-κB) in aortic vascular smooth muscle cells (VSMCs). Apocynin, a drug with an antioxidant effect, has also been proposed as a therapeutic agent for atherosclerotic disease. Objectives: This work investigates the effects of apocynin on the PPARγ and NF-κB protein expression evoked by AGEs in cultured VSMCs from Goto–Kakisaki (GK) rats, a non-obese insulin model of both insulin resistance and type 2 diabetes. Materials and methods: VSMCs, isolated from aortas of GK and non-diabetic rats, were cultured. The expression of proteins was evaluated by Western blot. The blood glucose concentration was measured with a blood glucose test meter. The diabetes of GK rats was controlled by blood glucose and insulin determinations (non-fasting values). The serum insulin concentration was determined by radioimmunoassay. Results: In VSMCs from non-diabetic and GK rats, apocynin (1 and 10 µM) abolished the protein overexpression of NF-κB induced by glycated bovine serum albumin (AGEs-BSA) incubation. However, apocynin (1 and 10 µM) enhanced the expression of PPARγ protein in the presence of AGEs-BSA (100 μg/mL) in VSMCs from non-diabetic, but not from GK rats. Conclusion: These findings suggest that apocynin decreases the incidence of alterations in VSMCs induced by AGEs through the reduction of NF-κB and may represent an attractive therapeutic approach to treat diabetes mellitus.
Culinary Herbs and Spices: Their Bioactive Properties, the Contribution of Polyphenols and the Challenges in Deducing Their True Health Benefits

Herbs and spices have been used for both culinary and medicinal purposes for centuries. Over the last decade, research into their role as contributors of dietary polyphenols, known to possess a number of properties associated with reducing the risk of developing chronic non-communicable diseases, has increased. However, bearing in mind how these foods are consumed, normally in small quantities and in combination with other foods, it is unclear what their true benefit is from a health perspective. The aim of this review is to use the literature to discuss how preparative and digestive processes, bioavailability and interactions between foods may influence the bioactive properties of these foods, and whether or not polyphenols are responsible for these properties. Furthermore, this review aims to highlight the challenges that need to be addressed so as to determine the true benefits of these foods and the mechanisms of action that underpin their purported efficacy.
The Grid File: An Adaptable, Symmetric Multikey File Structure

Traditional file structures that provide multikey access to records, for example, inverted files, are extensions of file structures originally designed for single-key access. They manifest various deficiencies in particular for multikey access to highly dynamic files. We study the dynamic aspects of file structures that treat all keys symmetrically, that is, file structures which avoid the distinction between primary and secondary keys. We start from a bitmap approach and treat the problem of file design as one of data compression of a large sparse matrix. This leads to the notions of a grid partition of the search space and of a grid directory, which are the keys to a dynamic file structure called the grid file. This file system adapts gracefully to its contents under insertions and deletions, and thus achieves an upper bound of two disk accesses for single record retrieval; it also handles range queries and partially specified queries efficiently. We discuss in detail the design decisions that led to the grid file, present simulation results of its behavior, and compare it to other multikey access file structures.
Research on clothing product reviews mining based on the maximum entropy

This paper excavated the review theme of clothing products by method of association rules, and built a maximum entropy model for the reviews classification. Then this paper did experimental verification to large-scale clothing product reviews classification, which verified the practical effect that maximum entropy model had in the comment text classification problems. In the process of classification, the maximum entropy model had a good effect, of which accuracy was over 90%.
KOMBINASI PENGOLAHAN CONSTRUCTED WETLAND DAN AERASI UNTUK MENINGKATKAN PENURUNAN BOD DAN TSS PADA LUMPUR TANGKI SEPTIK

Lumpur hasil penyedotan tangki septik memiliki konsentrasi Biogeochemical Oxygen Demand (BOD) dan Total Suspended Solids (TSS) yang belum memenuhi baku mutu sesuai Peraturan Gubernur Jawa Timur Nomor 72 Tahun 2013. Kombinasi pengolahan wetland dan aerasi mampu meningkatkan penurunan BOD dan TSS pada lumpur tangki septik. Tujuan penelitian adalah untuk (i) menentukan efisiensi penurunan BOD dan TSS pada lumpur tangki septik (ii ) menentukan waktu tinggal dan jenis tanaman pada wetland yang paling sesuai untuk mengolah lumpur tangki septik. Penelitian ini dilakukan dalam skala laboratorium dengan operasional reaktor secara kontinyu dengan variasi waktu tinggal 5 hari, 15 hari , dan 25 hari serta variasi jenis tanaman Scirpus lacustris dan Cyperus papyrus. Hasil penelitian menunjukkan bahwa tanaman Scirpus lacustris menghasilkan penurunan BOD dan TSS lebih tinggi dari tanaman Cyperus papyrus dengan waktu tinggal terbaik pada 25 hari. Penurunan BOD dan TSS lumpur tangki septik yang dihasilkan adalah 98% dan 87% pada tanaman Scirpus lacustris serta 97% dan 83% pada tanaman Cyperus papyrus. Tanaman Scirpus lacustris mampu mengolah lumpur tangki septik dengan hasil konsentrasi BOD dan TSS adalah 26 mg/l dan 30 mg/l sehingga telah memenuhi standar baku mutu sesuai Peraturan Gubernur Jawa Timur Nomor 72 Tahun 2013. Kata kunci : constructed wetland, aerasi, BOD 5 , TSS DOI https://doi.org/10.33005/envirotek.v10i2. 1227
Revisiting Visual Pattern Mining

With the progress in deep learning based methods, visual pattern mining has seen a significant improvement in extracting visual patterns in the form of mid-level elements[18] and using these patterns for object recognition tasks. The problem with the previous approaches is that they are fully supervised and requires a large amount of labelled data for pattern mining. But how to make it work when there is little or no labelled data? In this work, we propose an unsupervised pattern mining algorithm which works very well given a large unlabelled dataset. We further extend it to show how it also adapts to include labelled data as well and thus, is able to extract information from both labelled and unlabelled data together. This property makes it very useful for low-shot recognition tasks where the labelled data is present in very small quantities and there is an abundance of unlabelled data. In this work we show the effectiveness of our pattern mining algorithm on the task of low-shot fine grained recognition and image labelling. We show that our unsupervised mining algorithm is able to detect fine grained patterns of good quality even without using any labels and if given a few labelled images there is a significant improvement in quality and diversity of patterns. We also show the ability of our approach in labelling more images from the large unlabelled pool and adding them iteratively to the labelled set in a semi-supervised learning based approach. Our method performs much better than the baselines which include previous state of the art approaches to fine grained recognition.