Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimization of a Mass Trapping Method against the Striped Cucumber Beetle Acalymma vittatum in Organic Cucurbit Fields

Simple Summary Striped cucumber beetles are the main pest of cucurbits in North America. Organic cucurbit producers face a great challenge since few effective organic-approved striped cucumber beetle control methods exist. In this study, we evaluated and improved a mass trapping method using perforated yellow jugs with commercially available odorant baits to attract striped cucumber beetles. Our goal was to maximize striped cucumber beetle captures while minimizing unwanted captures of beneficial insects. We found that baited traps attracted more striped cucumber beetles than unbaited traps, and that traps with smaller holes effectively captured striped cucumber beetles while limiting unwanted captures. Finally, we also determined an optimal bait type that should preferentially be used to capture striped cucumber beetles. Abstract The striped cucumber beetle (SCB) Acalymma vittatum (F.) (Coleptera: Chrysomelidae) is a prime problem in North American cucurbit crops. While certain chemical pesticides efficiently control SCB in conventional cucurbit fields, alternative solutions are required due to the ever-evolving regulations on pesticides. For organic producers, very few control methods exist. A novel mass trapping method demonstrates the potential of controlling SCBs using floral-based semiochemical baited traps in cucurbit crops. The goals of this study were to (1) determine whether baited traps capture more SCBs than unbaited ones, and (2) optimize the trapping method by comparing different trap types and different commercially available attractants to maximize SCB captures while minimizing non-target species captures. The results of a first experiment showed that baited traps captured significantly more SCBs than unbaited ones. Baited traps also captured significantly more bees and hoverflies than unbaited ones. In a second experiment these unwanted captures were drastically reduced by using traps with ten 4 mm in diameter holes per side. Finally, a third experiment demonstrated that the attractant 40CT313 was the most efficient at capturing SCB compared to other tested lures. Overall, the optimized mass trapping technique demonstrated a potential to effectively control SCB populations in organic cucurbit crops.
Gel-Based Autologous Chondrocyte Implantation in a Patient with Noncontained Osteochondral Knee Defect at 9-Year Follow-Up

Osteochondritis dissecans (OCD) is a disorder of the subchondral bone affecting the adjacent articular cartilage that may lead to cartilage and bone fragment detachment. It commonly occurs in the knee joint, elbow, wrist, and ankle. Although several surgical concepts have been described to treat OCD (fragment fixation, microfracture, autologous chondrocyte implantation (ACI), and mosaicplasty), no gold standard treatment has been accepted for managing OCD. Multiple factors like age, stability of defect, and defect size should be considered while selecting a specific treatment for OCD. Here, we discuss the case of an 18-year-old patient with horizontal and noncontained OCD. The MRI and CT scan evaluations of condylar notch view showed a defect (23 mm × 19 mm × 8 mm) with ICRS grade IV lateral femoral condyle OCD that was successfully managed by gel-based ACI. After 9 years of ACI, the patient was asymptomatic with full range of motions at the knees. Improvement in visual analog scale score, International Knee Documentation Committee score, and Magnetic Resonance Observation of Cartilage Repair Tissue score was also seen at 9 years post-ACI. No further surgical interventions were needed post-ACI.
Mobile Platforms Supporting Health Professionals: Need, Technical Requirements, and Applications

Mobile computing is beginning defining the future of healthcare. The vast majority of mHealth applications are related to fitness, training and self-monitoring; limited applications are targeting physicians and doctor-patient interactions. However this can change. In this chapter the background of applications related to medical imaging and clinical and laboratory medicine is analyzed. A technological framework supporting mHealth applications in an agnostic manner is also introduced. Within this framework there are implemented two application examples, one application (ImaginX) supporting a health ecosystem (hospitals, radiologists, clinicians, patients) for medical image management. The second application (HPVGuard) supports a divergent but cooperating environment of laboratory and clinical doctors and patients involved in cervical cancer prevention and control. The two applications are analyzed and is-sues related to user acceptance and future directions are presented. mHealth has the potential to shape health future not by just translating existing applications but by inspiring new ideas.
Adherence to a Physical Activity Program Depends on Individual Fitness Purpose in Older Persons

The effect of a long-term program on adherence in older adults seeking to improve low physical fitness compared to a multiactivity practice was studied. Seventy persons (+ 60 years) took part in 10 months program, distributing in three groups: low cardiorespiratory and muscular fitness (n=25, CMF), low coordination and motor skills (n=21, CBM) and free-choice multi-physical activities (n=24, MPA). Adherence was assessed by quantitative indicators and analysis of temporal dynamics. Adherence was 61.3 ± 25.8% for the CMF group, 49.7 ± 25.0% for the CBM and 33.3 ± 25.8 for the MPA. Only about 42% of the participants in MPA would continue the program for 10 consecutive months. The curve of adherence decreased regularly during the 10-month program: after 6 months adherence had fallen by 20% for CMF and by 14% for CBM, and after 10 months by 24% for CMF and by 19% for CBM. When physical activity program was supervised by the same instructor and when the participant’s individual goal was clear, adherence was significantly higher (p<0.05) in the range 76-81%.
Vibration mechanism of arm system of concrete pump truck

In order to analyze the vibration problem of arm system of concrete pump truck in consideration of the fluid-solid interaction,its dynamic equation was established based on cantilever conveying pipe theory,in which the fluctuating velocity of concrete flow and vibration boundary conditions of arm system were experimentally measured.The simulated vibration responses of arm system under constant speed as well as under fluctuating speed were calculated.Simulation results show that the calculated displacement responses in both cases are in agreement with each other.So the velocity fluctuation has little influence on the time history of arm stress.When the swivel table of concrete pump truck is in stationary state,the vibration responses of arm system under both speeds were also achieved by the method of simulation calculation.The results show that the car-body vibration as a result of cylinder impact action has great influence on arm system vibration.Therefore,it is proposed that the vibration of swivel table should be mainly considered.
A new perleidid neopterygian fish from the Early Triassic (Dienerian, Induan) of South China, with a reassessment of the relationships of Perleidiformes

Neopterygii is the largest clade of ray-finned fishes, including Teleostei, Holostei, and their closely related fossil taxa. This clade was first documented in the Early Carboniferous and underwent rapid evolutionary radiation during the Early to Middle Triassic. This article describes a new perleidid neopterygian species, Teffichthys elegans sp. nov., based on 13 well-preserved specimens from the lower Daye Formation (Dienerian, Induan) in Guizhou, China. The new species documents one of the oldest perleidids, providing insights into the early diversification of this family. The results of a phylogenetic analysis recover Teffichthys elegans sp. nov. as the sister taxon to Teffichthys madagascariensis within the Perleididae. T. elegans sp. nov. shares three derived features of Perleididae: the length of the anteroventral margin of the dermohyal nearly half the length of the anterodorsal margin of the preopercle; the anteroventral margin of the preopercle nearly equal to the anterior margin of the subopercle in length; and the anteroventral margin of the preopercle one to two times as long as the anterodorsal margin of the preopercle. It possesses diagnostic features of Teffichthys but differs from T. madagascariensis by the following features: presence of three supraorbitals; six pairs of branchiostegal rays; relatively deep anterodorsal process of subopercle; absence of spine on the posterior margin of the jugal; and pterygial formula of D26/P14, A22, C36/T39-41. The Perleidiformes are restricted to include only the Perleididae, and other previously alleged ‘perleidiform’ families (e.g., Hydropessidae and Gabanellidae) are excluded to maintain the monophyly of the order. Similar to many other perleidids, T. elegans sp. nov. was likely a durophagous predator with dentition combining grasping and crushing morphologies. The new finding also may indicate a relatively complex trophic structure of the Early Triassic marine ecosystem in South China.
Multifractal analysis on the cross-correlation between China and WTI crude oil futures prices

Recently, many studies prove that financial markets are characterized by multifractality. Therefore, under the framework of fractal market hypothesis, this paper uses multifractal detrended cross-correlation analysis (MF-DCCA), a method used to reveal the multifractal properties in the power-law cross-correlations between two non-stationary time series, to investigate the nonlinear correlations between China and West Texas Intermediate (WTI) crude oil futures prices. Based on data from March 26, 2018, the first launch day of crude oil futures in China, we find that the time series of the Shanghai International Energy Exchange (INE) crude oil futures prices and WTI crude oil futures prices are highly cross-correlated with multifractal properties. Moreover, there is a persistent cross-correlation between INE crude oil futures prices and WTI crude oil futures prices.
FRBF: A Fuzzy Rule Based Framework for Heart Disease Diagnosis

Heart disease is also known as cardiovascular disease. It is one of the most dangerousand deadly disease in all over the globe. Cardiovascular disease was deemed as amajor illness in old and middle age, but recent trends shown that now cardiovasculardisease is also a deadly disease in young age group due to irregular habit. However,Angiography is one of the way to diagnose heart disease, but it is very expensive andalso has major side effect. The aim of this research paper is to design a fuzzy rulebased framework to diagnosis of the risk level of the heart disease. Our proposedframework used a Mamdani interface system and used UCI machine repositorydataset for heart disease diagnosis. In this proposed study, we have used 10 Inputattribute and one output attribute with 554 rules. Besides, a comparative table is alsopresented, where proposed methodology is better than other methodology. Accordingto the proposed methodology results, that the performance is highly successful and itis a promising tool for identification of a heart disease patient at an early stage. Wehave achieved accuracy, sensitivity rates of 95.2% and 87.04 respectively, on the UCIdataset.
Making Maximally Ethical Decisions via Cognitive Likelihood & Formal Planning

This chapter attempts to give an answer to the following question: Given an obligation and a set of potentially-inconsistent, ethically-charged beliefs, how can an artiﬁcially-intelligent agent ensure that its actions maximize the likelihood that the obligation is satisﬁed? Our approach to answering this question is in the intersection of several areas of research, including automated planning, reasoning with uncertainty, and argumentation. We exemplify our reasoning framework in a case study based on the famous, heroic ditching of US Airways Flight 1549, an event colloquially known as the “Miracle on the Hudson. ”
Pair Distribution Function Analysis of the Short-Range Magnetic and Atomic Correlations in Manganese Telluride

Pair The antiferromagnetic semiconductor MnTe has recently been identiﬁed as a candidate high-performance thermoelectric, with its short-range magnetic correlations playing a crucial role in this technological application. Previous research has shown that these correlations are a signiﬁcant contributor to the high thermoelectric ﬁgure of merit zT in MnTe through a mechanism known as paramagnon drag. However, a clear picture of the nature of these correlations has not been developed up until this point. Here, we present three-dimensional atomic and magnetic pair distribution function (PDF) analysis of neutron total scattering data collected from a single crystal of MnTe, along with PDF data obtained from pure and doped MnTe powders. These complementary data sets allow us to analyze the nanometer-scale magnetic and atomic correlations directly in real space, revealing the behaviors of paramagnons in a unique and intuitive way. The three-dimensional PDF reconstructed the MnTe atomic structure and visually showed that the magnetic correlations exhibit anisotropy, with longer correlation lengths along the crystallographic c axis than within the ab plane. The one-dimensional PDF conﬁrmed and quantiﬁed these results, demonstrating that the enhancement to zT will be higher along the c axis where paramagnon drag is the strongest. Additionally, we present magnetic models in real space which reproduce the observed atomic and magnetic PDF patterns with quantitative accuracy. The signiﬁcance of these results is discussed in the context of existing work on MnTe and other magnetically enhanced thermoelectric materials.
EFFECT OF RESILIENT CONNECTION ON SOUND TRANSMISSION LOSS OF METAL STUD DOUBLE PANEL PARTITIONS

Existing techniques for predicting sound TL of double panel partitions are based on the assumption that the mechanical connection of the stud is a rigid sound bridge, but they provide unrealistic estimates of the TL in the ease of metal stud partitions. The TL of the latter is significantly improved at mid and higher frequencies owing to the lateral resilient effect of the stud itself. A modified expression for predicting the TL of metal stud partition is thus given in this paper, which is in good agreement with experimental results. The effects of additional resilient pad strip on both sides of the stud are discussed in the latter portion of this paper. It is now shown that even for such a complex structure the TL can also be determined by means of a set of simple expressions.
Chaotic Numbers and It’s uses on millennium prize problems. ⋆,⋆⋆

mathematicalproblemstheunsolvedmillenniumprizeproblemsnamely1.RiemannHypothesis,2.NavierStokesEquations,3.YangMillsTheoryandMassGap. ThesearesomeofthenamesofproblemswhichwewillseeinthispapercanbesolvedIdon’tclaimthatIhavesolvedtheseproblemsbutcertainlyIhavegivenanewperspectiveonthem.Weusechaoticnumbersandaxiomaticpropertiesofthesenumberswhichisdenotedby
Scheduling Constrained-Deadline Tasks in Precise Mixed-Criticality Systems on a Varying-Speed Processor

Real-time systems usually require guarantees in all possible scenarios including the worst case. As a result, when each system parameter is specified by a single estimate, significant pessimism is inevitably introduced. To mitigate such pessimism, mixed-criticality (MC) design has been proposed, where a single system parameter is provided multiple estimates. Most existing work on MC scheduling is directed to (fully or partially) sacrifice low-critical workloads in the event of high-critical workloads overrunning their normal-case estimate. Recently, another approach called precise MC scheduling has been investigated, where no low-critical workload is sacrificed in such situation but the speed of the processor is boosted to accommodate the extra execution requirement by high-critical workloads. Prior work on precise MC scheduling has focused on implicit-deadline tasks only. In this work, we extend the efforts in precise MC scheduling to constrained-deadline tasks by developing demand-based schedulability analysis in place of the utilization-based ones in prior work. This new analysis also enables more flexible virtual-deadline settings. The synthetic experiments have shown that significant schedulability improvements are achieved by this new analysis and by the flexibility in setting virtual deadlines.
Accurate Generation of Trigger-Action Programs with Domain-Adapted Sequence-to-Sequence Learning

Trigger-action programming allows end users to write event-driven rules to automate smart devices and internet services. Users can create a trigger-action program (TAP) by specifying triggers and actions from a set of predefined functions along with suitable data fields for the functions. Many trigger-action programming platforms have emerged as the popularity grows, e.g., IFTTT, Microsoft Power Automate, and Samsung SmartThings. Despite their simplicity, composing trigger-action programs (TAPs) can still be challenging for end users due to the domain knowledge needed and enormous search space of many combinations of triggers and actions. We propose RecipeGen, a new deep learning-based approach that leverages Transformer sequence-to-sequence (seq2seq) architecture to generate TAPs on the fine-grained field-level granularity from natural language descriptions. Our approach adapts autoencoding pre-trained models to warm-start the encoder in the seq2seq model to boost the generation performance. We have evaluated RecipeGen on real-world datasets from the IFTTT platform against the prior state-of-the-art approach on the TAP generation task. Our empirical evaluation shows that the overall improvement against the prior best results ranges from 9.5%-26.5%. Our results also show that adopting a pre-trained autoencoding model boosts the MRR@3 further by 2.8%-10.8%. Further, in the field-level generation setting, RecipeGen achieves 0.591 and 0.575 in terms of MRR@3 and BLEU scores respectively.
OW-DETR: Open-world Detection Transformer Supplementary Material

where PK is the model precision for known classes when evaluated on known class instances alone and PK∪U denotes the same when evaluated with unknown class instances included. On the other hand, the A-OSE metric measures the total number of unknown instances detected as one of the known classes. Both these two (WI and A-OSE) indicate the degree of confusion in predicting the known classes in the presence of unknown instances. Furthermore, we also show the comparison in terms of U-Recall for ease of comparison. It is worth mentioning that U-Recall directly relates to the unknown class and measures the model’s ability to retrieve the unknown instances. The standard object detectors (Faster R-CNN and DDETR) in the top part of Tab. A1 are inherently not suited for the OWOD setting since they cannot detect any unknown object. Thereby, for these frameworks, only WI and A-OSE can be computed but not U-Recall. Since the energy-based unknown identifier (EBUI) in the recently introduced ORE [4] is learned using a held-out validation
Rootkit detection with memory snapshot inspection on embedded IoT devices

IoT systems are subject to cyber attacks, including infecting embedded IoT devices with rootkits. Rootkits are malicious software that typically run with elevated privileges, which makes their detection challenging. In this paper, we address this challenge: we propose a rootkit detection approach for embedded IoT devices that takes advantage of a trusted execution environment (TEE), which is often supported on popular IoT platforms, such as ARM based embedded boards. The TEE provides an isolated environment for our rootkit detection algorithms, and prevents the rootkit from interfering with their execution even if the rootkit has root privileges on the untrusted part of the IoT device. Our rootkit detection algorithms identify modiﬁcations made by the rootkit to the code of the operating system kernel, to system programs, and to data inﬂuencing the control ﬂow (e.g., hooking system calls), as well as inconsistencies created by the rootkit in certain kernel data structures (e.g., those responsible to handle process related information). We also use algorithms to detect rootkit components in the persistent storage of the device. Besides describing our approach and algorithms in details, we also report on a prototype implementation and on the evaluation of our design and implementation, which is based on testing our prototype with rootkits that we developed for this purpose.
LinkGuardian: Mitigating the impact of packet corruption loss with link-local retransmission

Packet corruption loss is a serious problem in datacenter networks. A large-scale study by Microsoft reported that the number of packets lost due to corruption is comparable to those lost due to congestion. Previous attempts to mitigate the impact of packet corruption loss seek to avoid the faulty links by routing around them, at the cost of reduced link capacities and disruption to the rest of the network. In this paper, we investigate the feasibility and tradeoffs of the classical loss recovery strategy of link-local retransmissions in the context of datacenter networks. We present the design and implementation of LinkGuardian, a dataplane-based protocol that detects the packets lost due to corruption and simply retransmits them out-of-order. Our preliminary results show that a naïve out-of-order retransmission strategy is effective in mitigating the impact of packet corruption loss for both throughput-sensitive and latency-sensitive flows. Our long-term goal is to extend LinkGuardian so that the end hosts can be made completely oblivious to packet corruption losses in the network.
A homozygous p.(Arg371Ser) mutation in FICD de-regulates AMPylation of the human endoplasmic reticulum chaperone BiP causing infancy-onset diabetes and severe neurodevelopmental delay

Dysfunction of the endoplasmic reticulum (ER) in insulin-producing beta cells results in cell loss and diabetes mellitus. Here we report on 5 individuals from three different consanguineous families with infancy-onset diabetes mellitus and severe neurodevelopmental delay caused by a homozygous p.(Arg371Ser) mutation in FICD. The FICD gene encodes a bifunctional Fic domain-containing enzyme that regulates the ER Hsp70 chaperone, BiP, via catalysis of two antagonistic reactions: inhibitory AMPylation and stimulatory deAMPylation of BiP. Arg371 is a conserved residue in the Fic domain active site. The FICDR371S mutation partially compromises BiP AMPylation in vitro but eliminates all detectable deAMPylation activity. Overexpression of FICDR371S or knock-in of the mutation at the FICD locus of stressed CHO cells result in inappropriately elevated levels of AMPylated BiP. These findings, guided by human genetics, highlight the destructive consequences of de-regulated BiP AMPylation and raise the prospect of tuning FICDs antagonistic activities towards therapeutic ends.