Miracle-dz/UniFAR-FTUs huggingface dataset:
FedDBO: A Novel Federated Learning Approach for Communication Cost and Data Heterogeneity Using Dung Beetle Optimizer

As an emerging distributed machine learning technology, federated learning has gained widespread attention due to its critical privacy protection mechanism. However, it also faces challenges such as high communication costs and heterogeneous client data.In order to address the above issues. This paper proposes a federated learning approach based on the dung beetle optimizer, named FedDBO. In this method, the model parameters uploaded from clients to the server are transformed into model scores. In each round of training, only some of the clients with high model scores need to be selected to upload their parameters to the server, thus reducing communication costs; Simultaneously, a model retraining strategy is introduced. After aggregating the model parameters sent by clients, the server performs a second iterative training on the aggregated model using its own metadata, thereby reducing data heterogeneity and improving model performance. In addition, a proof of convergence is provided, demonstrating that the model aggregated by FedDBO converges to the aggregated model of FedAvg after each training round. Finally, experiments indicate that when simulating various data heterogeneous environments on datasets, FedDBO exhibits higher accuracy and better stability compared to three other algorithms: FedAvg, FedShare, and FedPSO.
Resistance training improves body composition and increases matrix metalloproteinase 2 activity in biceps and gastrocnemius muscles of diet-induced obese rats

OBJECTIVE: We investigated the influence of resistance training on body composition and matrix metalloproteinase 2 activity in skeletal muscles of rats fed a high-fat diet. METHODS: Thirty-two Wistar rats were divided into four experimental groups (n = 8/each) according to diet and exercise status: Control (standard diet), Obese Control (high-fat diet), Resistance Training (standard diet) and Obese Resistance Training (high-fat diet) groups. Animals were fed a high-fat diet for 12 weeks to promote excessive weight gain. Resistance Training groups performed 12 weeks of training periods after this period in a vertical ladder three times/week. Fat percentage, fat-free mass and fat mass were assessed using dual-energy X-ray absorptiometry, and matrix metalloproteinase 2 activity in biceps and gastrocnemius muscles was analyzed using zymography. RESULTS: Resistance training significantly reduced body and fat masses and fat percentages in both trained groups (p<0.05). The maximal carrying load between trained groups was not different, but relative force was higher in the Resistance Training group (p<0.05). Of note, increased matrix metalloproteinase 2 activity was noted in the tested muscles of both trained groups (p<0.05). CONCLUSION: In conclusion, altered body composition and muscle matrix metalloproteinase 2 activity promoted by excessive weight gain were positively modified by resistance training.
Barcoded NS31/AML2 primers for sequencing of arbuscular mycorrhizal communities in environmental samples1

Premise of the study: Arbuscular mycorrhizal fungi (AMF) are globally important root symbioses that enhance plant growth and nutrition and influence ecosystem structure and function. To better characterize levels of AMF diversity relevant to ecosystem function, deeper sequencing depth in environmental samples is needed. In this study, Illumina barcoded primers and a bioinformatics pipeline were developed and applied to study AMF diversity and community structure in environmental samples. Methods: Libraries of small subunit ribosomal RNA fragment amplicons were amplified from environmental DNA using a singlestep PCR reaction with barcoded NS31/AML2 primers. Amplicons were sequenced on an Illumina MiSeq sequencer using version 2, 2 × 250-bp paired-end chemistry, and analyzed using QIIME and RDP Classifier. Results: Sequencing captured 196 to 6416 operational taxonomic units (OTUs; depending on clustering parameters) representing nine AMF genera. Regardless of clustering parameters, ∼20 OTUs dominated AMF communities (78–87% reads) with the remaining reads distributed among other OTUs. Analyses also showed significant biogeographic differences in AMF communities and that community composition could be linked to specific edaphic factors. Discussion: Barcoded NS31/AML2 primers and Illumina MiSeq sequencing provide a powerful approach to address AMF diversity and variations in fungal assemblages across host plants, ecosystems, and responses to environmental drivers including global change.
Fatty acids differentially regulate hepatic cholesteryl ester formation and incorporation into lipoproteins in the liver of the mouse DOI 10.1194/jlr.M200146-JLR200

These experiments tested the hypothesis that fatty acids (FAs) that drive cholesterol esterification also enhance sterol secretion and were undertaken using a mouse model where lipoprotein-cholesterol output by the liver could be assessed in vivo. The turnover of sterol in the animals was kept constant (∼160 mg/d per kg) while the liver was enriched with the single FAs 8:0, 14:0, 18:1, or 18:2. Under these conditions, the steady-state concentration of cholesteryl ester in the liver varied 6-fold, from 1.2 to 7.9 mg/g, and the expansion of this pool was directly related to the specific FA enriching the liver (FA 18:1>18:2>8:0> 14:0). Secretion of lipoprotein-cholesterol varied 5-fold and was a linear function of the concentration of cholesteryl ester in the liver. These studies demonstrate that unsaturated FAs drive the esterification reaction and enhance lipoprotein cholesterol secretion by the liver under conditions where cholesterol balance across this organ is constant. Thus, individual FAs interact with cholesterol to profoundly regulate both the output and uptake of sterol by the liver, and these effects are articulated through the esterification reaction.
Multiple-Color Optical Activation, Silencing, and Desynchronization of Neural Activity, with Single-Spike Temporal Resolution

The quest to determine how precise neural activity patterns mediate computation, behavior, and pathology would be greatly aided by a set of tools for reliably activating and inactivating genetically targeted neurons, in a temporally precise and rapidly reversible fashion. Having earlier adapted a light-activated cation channel, channelrhodopsin-2 (ChR2), for allowing neurons to be stimulated by blue light, we searched for a complementary tool that would enable optical neuronal inhibition, driven by light of a second color. Here we report that targeting the codon-optimized form of the light-driven chloride pump halorhodopsin from the archaebacterium Natronomas pharaonis (hereafter abbreviated Halo) to genetically-specified neurons enables them to be silenced reliably, and reversibly, by millisecond-timescale pulses of yellow light. We show that trains of yellow and blue light pulses can drive high-fidelity sequences of hyperpolarizations and depolarizations in neurons simultaneously expressing yellow light-driven Halo and blue light-driven ChR2, allowing for the first time manipulations of neural synchrony without perturbation of other parameters such as spiking rates. The Halo/ChR2 system thus constitutes a powerful toolbox for multichannel photoinhibition and photostimulation of virally or transgenically targeted neural circuits without need for exogenous chemicals, enabling systematic analysis and engineering of the brain, and quantitative bioengineering of excitable cells.
A k-Anonymization Algorithm on Social Network Data that Reduces Distances between Nodes

To provide social network data (SN) data to researchers for data analysis, protecting user privacy via anonymization is necessary. One anonymization metric for SN data called k-neighbor focuses on the neighborhood subgraphs, which, for each node, consists of the node's neighbor nodes. This metric ensures that the neighborhood subgraph of every node in the anonymized graph is isomorphic to at least k other neighborhood subgraphs, however, the existing algorithm to realize k-neighbor does not consider case that adding noise edges for anonymization may drastically change the distances of some pairs of nodes, which in turn may alter the structure of the original graph. To solve this problem, we propose an algorithm that focuses on a method to add noise edges such that the change of the distances of the pairs of nodes is suppressed. Through our experiments, we have confirmed that our algorithm maintains the given distances between nodes in the anonymized graph.
Controlled growth and shape-directed self-assembly of gold nanoarrows

Shape-directed self-assembly of unique gold nanoarrows into supercrystals with unprecedented architectures is realized. Self-assembly of colloidal nanocrystals into complex superstructures offers notable opportunities to create functional devices and artificial materials with unusual properties. Anisotropic nanoparticles with nonspherical shapes, such as rods, plates, polyhedra, and multipods, enable the formation of a diverse range of ordered superlattices. However, the structural complexity and tunability of nanocrystal superlattices are restricted by the limited geometries of the anisotropic nanoparticles available for supercrystal self-assembly. We show that uniform gold nanoarrows (GNAs) consisting of two pyramidal heads connected by a four-wing shaft are readily synthesized through controlled overgrowth of gold nanorods. The distinct concave geometry endows the GNAs with unique packing and interlocking ability and allows for the shape-directed assembly of sophisticated two-dimensional (2D) and 3D supercrystals with unprecedented architectures. Net-like 2D supercrystals are assembled through the face-to-face contact of the GNAs lying on the pyramidal edges, whereas zipper-like and weave-like 2D supercrystals are constructed by the interlocked GNAs lying on the pyramidal {111} facets. Furthermore, multilayer packing of net-like and weave-like 2D assemblies of GNAs leads to non–close-packed 3D supercrystals with varied packing efficiencies and pore structures. Electromagnetic simulation of the diverse nanoarrow supercrystals exhibits exotic patterns of nanoscale electromagnetic field confinement. This study may open new avenues toward tunable self-assembly of nanoparticle superstructures with increased complexity and unusual functionality and may advance the design of novel plasmonic metamaterials for nanophotonics and reconfigurable architectured materials.
Recognition of mid-Paleozoic volcanism in New Zealand

ABSTRACT Two felsic volcanic clasts from conglomerates in Fiordland and northwest Nelson provide U–Pb zircon ages of 359 and c. 362 Ma respectively; ages that occur within the interval between voluminous Western Province plutonic S-type magmatism of the Karamea and Ridge suites. Both volcanic clasts have inherited zircon populations, and trace element signatures suggesting derivation from crustal melts. The dacitic clast from the mid-Cretaceous Seek Cove Formation in southwest Fiordland has whole-rock chemistry and an O–Hf–zircon isotopic signature consistent with derivation from the Takaka Terrane. A rhyolite clast from the Pupu Conglomerate in northwest Nelson also has chemistry consistent with derivation from a Takaka Terrane source. We therefore correlate both volcanic clasts to the S-type Ridge Suite. No comparable S-type plutonic source of the same age has been recognised in the northwest Nelson section of the Takaka Terrane. These volcanic clasts represent the oldest recognised episode of S-type Ridge Suite magmatism in the Takaka Terrane.
A DPLL Algorithm for Solving DQBF

Dependency Quantified Boolean Formulas (DQBF) comprise the set of propositional formulas which can be formulated by adding Henkin quantifiers to Boolean logic. We are not aware of any published attempt in solving this class of formulas in practice. However with DQBF being NEXPTIME-complete, efficient ways of solving it would have many practical applications. In this paper we describe a DPLL-style approach (DQDPLL) for solving DQBF. We show how methods successfully applied in similar algorithms for SAT/QBF can be lifted to this richer logic. This enables to reuse efficient SAT and QBF solving techniques.
A Reactive Cross Collision Exclusionary Backoff Algorithm in IEEE

An inseparable challenge associated with every random access network is the design of an efficient Collision Resolution Algorithm (CRA), since collisions cannot be completely avoided in such network. To maximize the collision resolution efficiency of a popular CRA, namely Binary Exponential Backoff (BEB), we propose a reactive backoff algorithm. The proposed backoff algorithm is reactive in the sense that it updates the contention window based on the previously selected backoff value in the failed contention stage to avoid a typical type of collision, referred as cross-collision. Cross-collision would occur if the contention slot pointed by the currently selected backoff value appeared to be present in the overlapped portion of the adjacent (the previous and the current) windows. The proposed reactive algorithm contributes to significant performance improvements in the network since it offers a supplementary feature of Cross Collision Exclusion (XCE) and also retains the legacy collision mitigation features. We formulate a Markovian model to emulate the characteristics of the proposed algorithm. Based on the solution of the model, we then estimate the throughput and delay performances of WLAN following the signaling mechanisms of the Distributed Coordination Function (DCF) considering IEEE 802.11b system parameters. We validate the accuracy of the analytical performance estimation framework by comparing the analytically obtained results with the results that we obtain from the simulation experiments performed in ns-2. Through the rigorous analysis, based on the validated model, we show that the proposed reactive cross collision exclusionary backoff algorithm significantly enhances the throughput and reduces the average packet delay in the network.
Model-Based Test Criteria for Validating Annotated Web Applications

In this paper we present a method the uses classical test coverage criteria for graphs, such as, all-edges, all nodes, and simple paths, to guide the testing of PageFlow graphs. The coverage criteria of the PageFlow graphs are applied to Actions/Pages and Forwards/Links of a web application.
Agreement Between Ambulance Paramedic- and Physician-Recorded Neurological Signs With Face Arm Speech Test (FAST) in Acute Stroke Patients

Background and Purpose— Patients with suspected stroke first assessed by ambulance paramedics require early recognition to facilitate appropriate triage and early treatment. We determined paramedic's accuracy in detecting acute stroke signs by comparing agreement between neurological signs recorded in the Face Arm Speech Test (FAST), a stroke recognition instrument, by paramedics on the scene and by stroke physicians after admission. Methods— Suspected stroke patients admitted by ambulance paramedics directly to an acute stroke unit through a rapid ambulance protocol were examined by a trainee stroke neurologist or admitting stroke physician over a 1-year period. Recorded neurological signs (facial weakness, arm weakness, speech disturbance) in confirmed acute stroke/transient ischemic attack (TIA) cases were compared between paramedics and the stroke neurologist/physician. Results— Ambulance crews referred 278 suspected stroke patients of whom 217 (78%) had confirmed stroke (n=189) or TIA (n=28); 95% were examined by the stroke neurologist (median 18 hours after paramedic assessment). Recorded signs and agreement between paramedics and stroke physicians in confirmed stroke group were: facial weakness, 68% versus 70% (κ=0.49; 95% CI: 0.36 to 0.62); arm weakness, 96% versus 95% (κ=0.77; 95% CI: 0.55 to 0.99); and speech disturbance, 79% versus 77% (κ=0.69; 95% CI: 0.56 to 0.82). Interrater agreement was complete for arm weakness in 98% cases. Conclusions— Recognition of neurological deficits by ambulance paramedics using FAST shows good agreement with physician assessment, even allowing for temporal evolution of deficits. The high prevalence and good agreement for arm weakness suggest that this sign may have the greatest usefulness for prehospital ambulance triage and paramedic-based neuroprotective trials.
Performance of Routing Protocols in WiMAX Networks

The selection of an appropriate routing protocol is a key issue when designing a scalable and efficient wireless networks. Various routing protocols have been used in wireless networks. In this paper, we investigate different routing protocols and evaluate their performances on 802.16 WiMAX networks. Using simulation, different routing protocols have been tested with various network parameters. Results show that DSDV in general outperforms other routing protocols.
Difficulty of Cooperation in Iterated Multi-Prisoner's Dilemma Situation-experimental Evidence

It is popular that two players face with each other repeatedly in different phases [1]. Workers usually have relationship with their colleagues not only at work but also privately. Governments make negotiations on agricultural trade in addition to industrial trade. A hotel chain competes with the rival in various areas. Do these situations facilitate cooperation? What kind of decision makings should players offer to keep mutual cooperation in such situations? Using the laboratory ex ime t and simple multi –Prisoner’s dilemma, we explore the effect of the change in the number of contacts and in the payoff structure, and then the characteristics of the strategy that leads players to reach mutual cooperation. When the number of contacts increases from one to two, players face with the more complicated situation and their behavior may be different from the single contact. The change of payoff structure will also affect their behavior. In such a case, finding the decision making to facilitate cooperation may be a hint for solving real problems.
Enhanced Water Demand Analysis via Symbolic Approximation within an Epidemiology-Based Forecasting Framework

Epidemiology-based models have shown to have successful adaptations to deal with challenges coming from various areas of Engineering, such as those related to energy use or asset management. This paper deals with urban water demand, and data analysis is based on an Epidemiology tool-set herein developed. This combination represents a novel framework in urban hydraulics. Specifically, various reduction tools for time series analyses based on a symbolic approximate (SAX) coding technique able to deal with simple versions of data sets are presented. Then, a neural-network-based model that uses SAX-based knowledge-generation from various time series is shown to improve forecasting abilities. This knowledge is produced by identifying water distribution district metered areas of high similarity to a given target area and sharing demand patterns with the latter. The proposal has been tested with databases from a Brazilian water utility, providing key knowledge for improving water management and hydraulic operation of the distribution system. This novel analysis framework shows several benefits in terms of accuracy and performance of neural network models for water demand.
Flat vs. hierarchical phrase-based translation models for cross-language information retrieval

Although context-independent word-based approaches remain popular for cross-language information retrieval, many recent studies have shown that integrating insights from modern statistical machine translation systems can lead to substantial improvements in effectiveness. In this paper, we compare flat and hierarchical phrase-based translation models for query translation. Both approaches yield significantly better results than either a token-based or a one-best translation baseline on standard test collections. The choice of model manifests interesting tradeoffs in terms of effectiveness, efficiency, and model compactness.
Motion Control Strategies based on PD Control for a Four Degree-of-Freedom Serial Robotic Manipulator to Mimic Human Index Finger Articulations

The present study is based on motion control of an articulated model of a human index finger that has been modeled as a four-degree-of-freedom serial robotic manipulator. Preliminary studies on position and tracking control have been carried out by testing various control strategies based on proportional-derivative (PD) control in a simulation environment wherein the manipulator has been modeled and simulated with a certain input signal and responses to various controllers have been shown. Model free and model based controllers have been designed simulated using MATLAB®/ Simulink®. Strategies like model free PD control have been improved upon by introducing auto-tuning and learning capabilities. A virtual plant modeled using Simmechanics® toolbox has been set up and used for simulation purposes. General Terms Degree of freedom, human hand articulations, serial manipulators
The impact of two different think-aloud instructions in a usability test: a case of just following orders?

The instructions used in think-aloud studies can range from a simple request to think-aloud, to an explicit instruction to include certain types of content. The present study compared two think-aloud instructions: the classic neutral think-aloud instruction and an explicit instruction requesting explanations and content that is relevant to the user experience. Data from task performance, mental workload, think-aloud protocols and usability problems were collected from 16 participants, equally distributed between the two think-aloud instruction conditions. No differences were found in task performance, however, participants in the explicit instruction condition reported higher mental workload and a focus on finding interface problems. The explicit instruction condition also yielded more utterances about the user experience, expectations and explanations of behaviour than the neutral condition. An analysis of the resultant usability problems revealed that the explicit instruction led to a larger number of dialogue, navigation, layout and functionality problems, but that the problems which were unique to this condition were, in the main, at a low level of severity.
Spatial Scales in Topography and Strain Rate Magnitude in the Western United States

Spatial spectral analyses of topography and strain rate magnitude across the western United States reveal the presence of at least two separable spectral peaks, representative of characteristic length scales, one short (~10–50 km) and one long (~150–250 km). Less spectral power at intermediate wavelengths aside from that expected for a red, or power law, spectrum occurs in either data set. These results quantify previous qualitative observations that the topography of western North America contains both short and long characteristic wavelength features. Comparing the spectral results to simplified bounding solutions for elastic, viscous, and layered models under tension shows that multiple spectral peaks of comparable power can be reproduced only by mechanical models with more than one layer. Therefore, the simplest model of lithospheric architecture capable of generating the observed dominant characteristic length scales is an elastoplastic lid over a viscous layer.