Miracle-dz/UniFAR-FTUs huggingface dataset:
BA-Net: Dense Bundle Adjustment Network

This paper introduces a network architecture to solve the structure-from-motion (SfM) problem via feature-metric bundle adjustment (BA), which explicitly enforces multi-view geometry constraints in the form of feature-metric error. The whole pipeline is differentiable so that the network can learn suitable features that make the BA problem more tractable. Furthermore, this work introduces a novel depth parameterization to recover dense per-pixel depth. The network first generates several basis depth maps according to the input image and optimizes the final depth as a linear combination of these basis depth maps via feature-metric BA. The basis depth maps generator is also learned via end-to-end training. The whole system nicely combines domain knowledge (i.e. hard-coded multi-view geometry constraints) and deep learning (i.e. feature learning and basis depth maps learning) to address the challenging dense SfM problem. Experiments on large scale real data prove the success of the proposed method.
Developing and evaluating a probabilistic event detector for non-intrusive load monitoring

In this paper we present and evaluate probabilistic event detection algorithm for Non-Intrusive Load Monitoring. Like the other probabilistic event detectors, this algorithm also calculates the likelihood of a power event happening at each sample of the power signal. However, unlike the previous algorithms that threshold or employ voting schemes on the event likelihood, this algorithm employs a maxima/minima (i.e., the extrema) locator algorithm to identify potential power events. The proposed algorithm was evaluated against four public datasets, and its performance was compared to that of other four alternative solutions. The obtained results show that this new algorithm is competitive with the other alternatives in the four datasets. Furthermore, the results also suggest that using an extrema locator instead of a voting scheme, increases the performance of one of the state-of-the art algorithms.
Trading strategy for decentralized energy resources in sequential electricity markets: A swiss case study

This paper derives optimal day-ahead trading strategies for an aggregator of a decentralized energy resources' mix, who participates in a multi-market environment, including a day-ahead, an intraday and a balancing market. The optimization problem is solved using multi-stage stochastic programming, which is subject to different levels of uncertainties such as variable generation output, day-ahead and intraday market prices. Risk management is conducted to investigate the effect of risk exposure on the total revenue of the aggregator. A case study based on the data from the Swiss electricity market demonstrates the effectiveness of the proposed model.
Premature leaf senescence 3, encoding a methyltransferase, is required for melatonin biosynthesis in rice

Premature leaf senescence in rice is one of the most common factors affecting the plant's development and yield. Although methyltransferases are involved in diverse biological functions, their roles in rice leaf senescence have not been previously reported. In this study, we identified the premature leaf senescence 3 (pls3) mutant in rice, which led to early leaf senescence and early heading date. Further investigations revealed that premature leaf senescence was triggered by the accumulation of reactive oxygen species. Using physiological analysis, we found that chlorophyll content was reduced in the pls3 mutant leaves, while hydrogen peroxide (H2 O2 ) and malondialdehyde levels were elevated. Consistent with these findings, the pls3 mutant exhibited hypersensitivity to exogenous hydrogen peroxide. The expression of other senescence-associated genes such as Osh36 and RCCR1 was increased in the pls3 mutant. Positional cloning indicated the pls3 phenotype was the result of a mutation in OsMTS1, which encodes an O-methyltransferase in the melatonin biosynthetic pathway. Functional complementation of OsMTS1 in pls3 completely restored the wild-type phenotype. We found leaf melatonin content to be dramatically reduced in pls3, and that exogenous application of melatonin recovered the pls3 mutant's leaf senescence phenotype to levels comparable to that of wild-type rice. Moreover, overexpression of OsMTS1 in the wild-type plant increased the grain yield by 15.9%. Our results demonstrate that disruption of OsMTS1, which codes for a methyltransferase, can trigger leaf senescence as a result of decreased melatonin production.
Misalignment-aware delay modeling of narrow on-chip interconnects considering variability

The continuous scaling of process technologies into the nanometeric regime has placed interconnect as a key challenge to achieve overall chip performance. The worst-case delay of an interconnect is drastically influenced by the intrinsic misalignment originated by the unequal effective capacitances seen by each driver and by the extrinsic technology variability. The analysis and high-level modeling of these effects are essential to explore and optimize the interconnect architecture early in the design phase, using techniques such as coding. In this paper, we propose an analytical high-level delay model for multi-segment narrow interconnects. The proposed model accounts for misalignment effect, statistical variations and noise. It establishes the connection between delay of the coupled interconnects and transmitted signal patterns; thus, it enables efficiency characterization of Coupling Avoidance Codes (CAC) and can be used to study precisely stochastic approaches.
The association between periodontal disease severity and metabolic syndrome in Vietnamese patients

OBJECTIVE To investigate the association between periodontal disease severity and metabolic syndrome (MetS) in a group of Vietnamese patients. METHODS A total of 412 participants (114 males, 298 females, average age 57.8 ± 5.7 years) including 206 patients with MetS and 206 participants without MetS were selected for this study. Information on sociodemographic characteristics, dental behaviours and smoking status was collected from a self-administrated questionnaire. Periodontal status including plaque index (PI), gingival index (GI) pocket depth (PD) and clinical attachment level (CAL) was recorded. Logistic regression analyses were used to evaluate the association between severity of periodontal disease and MetS with adjustments for related confounders. RESULTS The prevalence of moderate and severe periodontitis assessed by GI, PD and CAL was all significantly higher in the MetS group than in the control group and was significantly increased by a number of MetS components. Logistic regression, adjusted for confounders, showed that people with mean PI ≥2.51 or GI ≥1.01 or number of teeth with bleeding on probing of ≥20 teeth or PD ≥3.66 or CAL ≥3.66 showed a significant association with greater OR for MetS compared to counterparts (P < .05). The OR for MetS was 4.06 (95% CI 2.11-7.84) in severe periodontitis patients compared to non-periodontitis participants (P < .001). CONCLUSION Much severe and extensive periodontal disease was found in MetS participants and increased with number of MetS components. Participants with higher periodontal parameters had a higher risk of MetS.
Impact of service and feeder cable upgrade on hosting capacity for single phase connected photovoltaics

The addition of photovoltaics (PV) to a grid impacts the performance of that grid in a number of ways. These impacts limit how much PV can be connected, termed ‘hosting capacity (HC)’. The impacts include overvoltage and overloading. Mitigation of impacts can be achieved in different ways: in this paper, upgrade of service cable and feeder cable has been considered, one of the classical solutions. Cable size upgrades to 16, 25 and 35 mm2 from 10 mm2 have been studied to mitigate overvoltages in a 28-customer Swedish suburban grid. A stochastic planning-based approach has been used to obtain a performance parameter that can be used to compare the mitigation methods. The results showed an improvement in overvoltage and hosting capacity with cable upgrade. The hosting capacity is also shown to be sensitive to the risk chosen and to the PV size.
Optimal Network Service Chain Provisioning

Service chains consist of a set of network services, such as firewalls or application delivery controllers, which are interconnected through a network to support various applications. While it is not a new concept, there has been an extremely important new trend with the rise of software-defined network (SDN) and Network Function Virtualization (NFV). The combination of SDN and NFV can make the service chain and application provisioning process much shorter and simpler. In this paper, we study the provisioning of service chains jointly with the number/location of virtual network functions (VNFs). While chains are often built to support multiple applications, the question arises as how to plan the provisioning of service chains in order to avoid data passing through unnecessary network devices or servers and consuming extra bandwidth and CPU cycles. It requires choosing carefully the number and the location of the VNFs. We propose an exact mathematical model using decomposition methods whose solution is scalable in order to conduct such an investigation. We conduct extensive numerical experiments, and show we can solve exactly the routing of service chain requests in a few minutes for networks with up to 50 nodes, and traffic requests between all pairs of nodes. Detailed analysis is then made on the best compromise between minimizing the bandwidth requirement and minimizing the number of VNFs and optimizing their locations using different data sets.
Enthalpy-entropy compensation based on isotherms of mango

SUMMARY ENTHALPY-ENTROPY COMPENSATION BASED ON ISOTHERMS OF MANGO. Moisture equilibrium data of mango pulp were determined using the static gravimetric method. Adsorption and desorption isotherms were obtained in the range of 30-70 C, to water activities (a ) from 0.02 to 0.97. The application of the GAB model to the experimental results, using direct nonlinear regression analysis, provided agreement between experimental and calculated values. The net isosteric heat of sorption was estimated from equilibrium sorption data, using the Clausius-Clapeyron equation. Isosteric heats of sorption were found to increase with increasing temperature and could be well adjusted by an exponential relationship. The enthalpy-entropy compensation theory was applied to sorption isotherms and plots of H versus S provided the isokinetic temperatures, indicating an enthalpy controlled sorption process. moisture content; thermodynamic properties; mango. o w ∆∆
A Probabilistic U-Net for Segmentation of Ambiguous Images

Many real-world vision problems suffer from inherent ambiguities. In clinical applications for example, it might not be clear from a CT scan alone which particular region is cancer tissue. Therefore a group of graders typically produces a set of diverse but plausible segmentations. We consider the task of learning a distribution over segmentations given an input. To this end we propose a generative segmentation model based on a combination of a U-Net with a conditional variational autoencoder that is capable of efficiently producing an unlimited number of plausible hypotheses. We show on a lung abnormalities segmentation task and on a Cityscapes segmentation task that our model reproduces the possible segmentation variants as well as the frequencies with which they occur, doing so significantly better than published approaches. These models could have a high impact in real-world applications, such as being used as clinical decision-making algorithms accounting for multiple plausible semantic segmentation hypotheses to provide possible diagnoses and recommend further actions to resolve the present ambiguities.
Physical layer security of wireless communication systems affected by LOS blockage

We investigate the problem of wireless physical-layer security in the presence of blockages, which is a key propagation effect in millimeter wave bands. We obtain analytical expressions for the strictly positive secrecy capacity and outage probability of secrecy capacity in a scenario in which the legitimate peers have a direct LOS path with a certain blockage probability, whereas the eavesdropper observes the communication from a NLOS link. We also analyze the effect of using a blocking-aware adaptive transmission method to overcome the LOS blockage, which significantly improves the secrecy performance.
Safety of Electromagnetic Navigation Bronchoscopy in Patients With COPD: Results From the NAVIGATE Study

Background: Electromagnetic navigation bronchoscopy (ENB) aids in the localization of lung lesions for biopsy and/or to guide fiducial or dye marking for stereotactic radiation or surgical localization. This study assessed ENB safety in patients with chronic obstructive pulmonary disease (COPD) and/or poor lung function. Methods: NAVIGATE is a prospective, multicenter, observational study of ENB. This substudy analyzed the 1-month follow-up of the first 1000 enrolled subjects. COPD was determined by medical history. Pulmonary function testing (PFT) results were collected if available within 30 days of the procedure. Procedure-related complications were captured. Results: The analysis included 448 subjects with COPD and 541 without COPD (COPD data missing in 11). One-month follow-up was completed in 93.3%. Subjects with COPD tended to be older, male, and have history of tobacco exposure, asthma, and recent pneumonia. Nodule size, location, and procedure time were similar between groups. There was no statistically significant difference in the procedure-related composite complication rate between groups (7.4% with COPD, 7.8% without COPD, P=0.90). Common Terminology Criteria for Adverse Events scale grade ≥2 pneumothorax was not different between groups (2.7% with COPD, 3.7% without COPD, P=0.47). COPD was not a significant multivariate predictor of complications. Severity of forced expiratory volume in 1 second (FEV1) or diffusing capacity of the lung for carbon monoxide impairment was not associated with increased composite procedure-related complications (ppFEV1 P=0.66, ppDLCO P=0.36). Conclusion: In this analysis, complication rates following ENB procedures were not increased in patients with COPD or poor pulmonary function. Because pneumothorax risk is not elevated, ENB may be the preferred method to biopsy peripheral lung lesions in patients with COPD and/or poor pulmonary function testing.
Operator-Theoretic Characterization of Eventually Monotone Systems

Eventually monotone systems are dynamical systems whose solutions preserve a partial order in the initial condition after some initial transient. While monotone systems have a characterization in terms of their vector fields, eventually monotone systems have not been characterized in such an explicit manner. In order to provide a characterization, we drew inspiration from the results for linear systems, where eventually monotone (positive) systems are studied using the spectral properties of the system. We extend this spectral characterization to nonlinear systems by employing the Koopman operator framework. We also present a method to certify strong eventual monotonicity with respect to an unknown cone, a tool which to our best knowledge does not exist for monotone systems. These results are illustrated on biologically inspired numerical examples, which highlight the potential applicability of eventual monotonicity.
Modeling packet loss rate of IEEE 802.15.4 links in diverse environmental conditions

Modeling and prediction of Packet Loss Rate (PLR) of wireless links using hardware information is essential for the design of higher-layer protocols in Wireless Sensor Networks. While many previous studies revealed the spatio-temporal variation of various link quality metrics, how environment impacts on the mapping between PLR and hardware indicators still remains unclear. Without a comprehensive understanding of such environmental impact, the acquired empirical PLR models are severely limited to specific scenarios. In this paper, we present the results of indoor and outdoor experimental campaigns focusing on the impact of various environmental factors (e.g., obstacles, human activities, climate conditions) on the dependency between the link PLR, signal to noise ratio (SNR) and packet length. Rich observations are made on the spatio-temporal characteristics of the PLR-SNR relationship and our analysis shows that link PLR can be modeled, in all experimented scenarios, as an exponential function of SNR and packet length with two model parameters that may vary over space and time. Besides, implications of the observations are summarized, providing guidelines to construct and adapt PLR models in different environments.
Is Sarcopenia a Potential Risk Factor for Distal Radius Fracture? Analysis Using Propensity Score Matching

Background Cases of low-energy-induced distal radius fracture (DRF) are increasing. Sarcopenia is considered to be an independent risk factor for fragility fractures. We compared body appendicular lean muscle mass (ALM) and bone mineral density (BMD) in patients with DRF and a comparable control population. This study aimed to investigate the correlation between skeletal muscle mass and DRF. Methods We performed a retrospective review of patients diagnosed with fragility DRF. The DRF group included 87 patients treated at our institute. The control group comprised data for 87 individuals in the general population from among 2,124 selected using nearest-neighbor propensity scoring, based on age, weight, height, and body mass index. All medical conditions and past history were also compared between the two groups. Results The relative overall ALM, combining arm and leg lean body mass divided by height squared, was not significantly different (DRF group, 6.093 kg/m2; controls, 5.945 kg/m2). T-score, a parameter of BMD, was significantly different between groups (DRF, −2.42; controls, −2.05). The proportion of patients with osteoporosis was significantly different (DRF, 44 [50.6%] vs. control, 29 [33.3%], respectively). Conclusions Patients with DRF did not have significantly lower average lean body mass. BMD was significantly lower in patients with DRF than in controls.
Increased CAIDE dementia risk, cognition, CSF biomarkers, and vascular burden in healthy adults

Objective To investigate the cognitive profile of healthy individuals with increased Cardiovascular Risk Factors, Aging and Dementia (CAIDE) dementia risk score and to explore whether this association is related to vascular burden and CSF biomarkers of amyloidosis and neurodegeneration. Method Cognitively normal participants (mean age 57.6 years) from the Gipuzkoa Alzheimer Project study were classified as having high risk (HR; n = 82) or low risk (LR; n = 293) for dementia according to a CAIDE score cutoff of 9. Cognitive composites were compared between groups. We explored using generalized linear models the role of APOE genotype, MRI white matter hyperintensities (WMH), and CSF (n = 218) levels of β-amyloid1-42 (Aβ1-42), total tau (t-tau), and phosphorylated tau (p-tau) in the association between CAIDE score and cognition. Results HR participants obtained lower scores on executive function (EF) (p = 0.001) and visual perception and construction (VPC) (p < 0.001) composites. EF composite was associated with CAIDE score × p-tau (p = 0.001), CAIDE score × t-tau (p = 0.001), and WMH (p = 0.003). VPC composite was associated with APOE (p = 0.001), Aβ1–42 (p = 0.004), the interaction APOE × Aβ1–42 (p = 0.003), and WMH (p = 0.004). Performance on global memory was associated with Aβ1–42 (p = 0.006), APOE (p = 0.008), and their interaction (p = 0.006). Analyses were adjusted for age, education, sex, premorbid intelligence, and stress. Conclusion Healthy participants at increased dementia risk based on CAIDE scores show lower performance in EF and VPC. This difference is related to APOE, WMH, and Alzheimer biomarkers.
Eco-friendly dual-band AULOS® passive radar for air and maritime surveillance applications

The last results obtained with the Eco-friendly dual-band AULOS® passive radar sensor carried out within the long-term collaboration between Sapienza University of Rome and Leonardo S.p.A. are here reported. Specifically, FM and DVB-T signals are parasitically exploited for air and maritime surveillance applications. A significant effort concerned the development of signal processing techniques to be efficient in both the investigated applications. To this purpose, the recent processing techniques developed by the research group of Sapienza have been applied. We show that the FM-based AULOS is able to detect with great continuity the typical aerial traffic as well as aircrafts with low RCS. In contrast, the DVB-T based sensor can be successfully employed for monitoring vessel of different dimensions both in the proximity of a port that travel during the day. The reported results confirm that the considered sensor can be usefully employed for improving safety and security of public areas, such as airports and harbors, preserving both the landscape integrity and the electromagnetic health of the population.
Geant4‐DNA example applications for track structure simulations in liquid water: A report from the Geant4‐DNA Project

This Special Report presents a description of Geant4-DNA user applications dedicated to the simulation of track structures (TS) in liquid water and associated physical quantities (e.g., range, stopping power, mean free path…). These example applications are included in the Geant4 Monte Carlo toolkit and are available in open access. Each application is described and comparisons to recent international recommendations are shown (e.g., ICRU, MIRD), when available. The influence of physics models available in Geant4-DNA for the simulation of electron interactions in liquid water is discussed. Thanks to these applications, the authors show that the most recent sets of physics models available in Geant4-DNA (the so-called "option4" and "option 6" sets) enable more accurate simulation of stopping powers, dose point kernels, and W-values in liquid water, than the default set of models ("option 2") initially provided in Geant4-DNA. They also serve as reference applications for Geant4-DNA users interested in TS simulations.
IDENTIFICATION AMONG FIRST‐GENERATION CITIZEN STUDENTS AND FIRST‐GENERATION COLLEGE STUDENTS: AN EXPLORATION OF SCHOOL SENSE OF COMMUNITY

The current study explored the relationships within a higher education institution between school sense of community among first-generation U.S. citizen students and first-generation college students compared to students of non-first generation studentship and citizenship (N = 3,025; M age = 27.21), and of varied racial backgrounds. Students at a large, urban, and faith-based university completed a measure of belongingness on campus. In terms of generational status, results found a significant interaction such that students who were both first-generation U.S. citizen students and first-generation college students reported the highest school sense of community. However, the combined first-generation U.S. citizen students and non-first-generation college student group reported the lowest scores. Despite these significant findings, sense of community scores were very similar with few differences between groups, which is further discussed in the discussion and limitation sections. Significant racial differences were not found. Implications for community psychology and higher education policy are discussed.