Miracle-dz/UniFAR-FTUs huggingface dataset:
Real-Time and Deep Learning Based Vehicle Detection and Classification Using Pixel-Wise Code Exposure Measurements

One key advantage of compressive sensing is that only a small amount of the raw video data is transmitted or saved. This is extremely important in bandwidth constrained applications. Moreover, in some scenarios, the local processing device may not have enough processing power to handle object detection and classification and hence the heavy duty processing tasks need to be done at a remote location. Conventional compressive sensing schemes require the compressed data to be reconstructed first before any subsequent processing can begin. This is not only time consuming but also may lose important information in the process. In this paper, we present a real-time framework for processing compressive measurements directly without any image reconstruction. A special type of compressive measurement known as pixel-wise coded exposure (PCE) is adopted in our framework. PCE condenses multiple frames into a single frame. Individual pixels can also have different exposure times to allow high dynamic ranges. A deep learning tool known as You Only Look Once (YOLO) has been used in our real-time system for object detection and classification. Extensive experiments showed that the proposed real-time framework is feasible and can achieve decent detection and classification performance.
Active Normal Faulting, Diking, and Doming Above the Rapidly Inflating Laguna del Maule Volcanic Field, Chile, Imaged With CHIRP, Magnetic, and Focal Mechanism Data

The Laguna del Maule volcanic field (LdMVF) in Chile, a rapidly inflating silicic volcanic system without historical eruption, is intersected by active regional faults. The LdMVF provides an opportunity to observe how faults influence, accommodate, or are driven by an actively deforming large silicic system. Here we use Compressed High Intensity Radar Pulse (CHIRP) acoustic reflection data to map the fault network in sediments captured within the eponymous lake at the LdMVF and combine our fault maps with the volcanic history, earthquake locations, focal mechanisms, and lacustrine magnetic data to interpret how faults and magmatism interact. Our seismic data image dominantly dip‐slip faults forming grabens within the lake, subparallel to regional faults. No indications exist in the seismic data to suggest that fault patterns were created by the volcanic system, either ring or radial faults. Fault strikes interpreted from seismic and magnetic data are consistent with mapped dike and fault orientations on land. We therefore interpret that active faults at the LdMVF are tectonic rather than volcanic in origin, forming a transtensional zone that hosts the magmatic system. However, vertical motion along a NS‐striking fault near the center of uplift suggests trapdoor‐style faulting above the volcanic center in which tectonic faults are reactivated to accommodate magmatic inflation and overlying deformation. Magnetic anomalies follow regional faults, suggesting that faults also provide migration pathways. Depositional patterns indicate a prior episode of uplift followed by quiescence, indicating that significant magmatically related uplift at the LdMVF can occur without an associated major eruption.
Spatiotemporal variability of elemental and organic carbon in
Svalbard snow during 2007–2018

Abstract. Light-absorbing carbonaceous aerosols emitted by biomass or fossil fuel combustion can contribute to amplify Arctic climate warming by lowering the albedo of snow. The Svalbard archipelago, being near to Europe and Russia, is particularly affected by these pollutants, and improved knowledge of their distribution in snow is needed to assess their impact. Here we present and synthesize new data obtained on Svalbard between 2007 and 2018, comprising 324 measurements of elemental (EC) and organic carbon (OC) in snow from 49 sites. We used these data, combined with meteorological and aerosol data and snowpack modelling, to investigate the variability of EC and OC deposition in Svalbard snow across latitude, longitude, elevation and time. Overall, EC concentrations (CsnowEC) ranged from
Feeding habits of the seahorse Hippocampus patagonicus (Actinopterygii: Syngnathiformes: Syngnathidae) on the southern coast of Brazil

The feeding habits of the seahorse Hippocampus patagonicus Piacentino et Luzzatto, 2004 on the southern Brazilian coast was evaluated through the gut content analysis of 82 individuals (28–110 mm in height, HT) obtained through a fish landing monitoring program (July 2011 to November 2012). Results showed that H. patagonicus feed mainly on small benthic and pelagic zooplankton organisms, mainly amphipods, decapods postlarvae (megalopa), and isopods. In the warm season (>20°C, from November to April) the diet was dominated by amphipods, and in the cold season (<19°C, from May to October) by decapods post-larvae and isopods. No significant differences were observed on the diet composition of juveniles (<48.5 mm HT) and adults (>48.5 mm HT) and also among sites. The importance of amphipods and decapod larvae as a food source is well known for seahorses, all explained by their highly specialized prey-capture mechanism and foraging behaviour.
A ‘R-to-H’ Mesh Adaptation Approach for Moving Immersed Complex Geometries Using Parallel Computers

ABSTRACT In this work, we propose an efficient ‘r-to-h’ adaptation algorithm for moving boundary problems using only vertex displacements and some local h-adaptation operations. Moving boundary algorithms usually require the regeneration of the mesh to avoid his invalidation in particular when the motion is large and/or several bodies are involved. The proposed approach aims to move the mesh nodes, using the Inverse Distance Weighting interpolation method, while conserving the mesh connectivity until the mesh elements quality deteriorate. At this point, a selective h-adaptation involving local mesh modifications such as edge flipping, local refinement and local coarsening are performed only on the submeshes containing badly shaped elements. The developed approach is valid for multi-body simulations and is able to handle their simultaneous independent displacements. The algorithm implemented is extended to parallel computers to speed-up large 3D moving geometries.
Single‐incision laparoscopic repair for a Morgagni hernia: A case report

A Morgagni hernia is a rare type of congenital diaphragmatic hernia. Here, a case of a Morgagni hernia repaired by SILS is presented. A 78‐year‐old woman was admitted to our hospital with nausea and vomiting. On CT, the transverse colon and antrum of the stomach were prolapsed into the right thoracic cavity. The herniated stomach was repositioned by emergency endoscopy, and SILS repair was performed electively. Laparoscopy showed the hernial orifice, which was 75 × 50 mm in diameter, on the right side and behind the sternum. Although the transverse colon had herniated through the defect into the right diaphragm, it was easily reduced into the abdominal cavity. Composite mesh was sutured to cover the hernial orifice. No perioperative complications or hernia recurrence have been observed in the 8 months since the surgery.
Creating a Hope Narrative for Veterans in Recovery Using Photography and Written Expression

ABSTRACT Hope is critical for mental health recovery. The study evaluated a program using photography and writing to explore hope in recovery and analyzed psycho-social-spiritual themes related to hope. Veterans (n = 89) from multiple war periods completed a 4-week photography workshop. Hope photo book narratives were created using 10 photographs that were paired with 10 hope words used in a descriptive sentence. Questionnaire mean differences for class efficacy and hope status were statistically significant using paired samples t-test. Of 890 hope words categorized by thesaurus definition, 5 multidimensional themes emerged. Love, support, strength, future, and focus were the most chosen words within each theme. Creating a hope photo book narrative can help build hope and improve hope during recovery.
Regions and Sub-regions Dysfunctions in Alzheimer’s during Rest

Aims: Alterations in the cerebrum structurally and functionally are triggered largely due to an increase in neuro depressive brain disorders like Alzheimer’s. This study aims is to determine these alterations in the regions of the cerebrum which are significant and distinguishing in Alzheimer’s disease subjects compared to healthy. We employ the most potential resting-state functional Magnetic Resonance Imaging (rs-fMRI) modality for this analysis. Methodology: 24 Alzheimer’s disease (AD) and 25 Healthy Controlled (HC) subjects were evaluated with rs-fMRI which is more efficient in anticipating neuronal activity changes. Thus, obtained data of all subjects were preprocessed and components of larger networks to smaller regions were extracted by independent component analysis (ICA) method. Differences in resting-state connectivity were examined for 6 networks of interest viz., Auditory network, Central Executive network, Default mode network, Silence mode network, Sensory-motor network and Visual network and their regions, which are affected due to the common symptoms of Alzheimer’s disease-like memory, thinking and behavioral changes. Statistical analysis was done with one sample t-test to check the functional connectivity activations in Resting-State Networks (RSNs) and regions of both AD & HC groups at a threshold of T>2. Finally, to obtain the abnormal sub-regions in each of the RSNs of AD a two-sample t-test was carried out at a threshold of P < . 03. Results: Our method potentially identifies the functional connectivity alterations and core regions dysfunction amongst the major 6 RSNs in AD compared to HC subjects. The results also showed decreased connectivity in regions of sensory-motor and default mode networks increased connectivity in regions of central executive and silence mode network along with some of the sub-regions dysfunctions in AD. Conclusion: Modifications in functional connectivity within the major RSNs and regions have been detected which serves as a capability to determine an early biomarker and examining the disease progression.
Reward-driven changes in striatal pathway competition shape evidence evaluation in decision-making

Cortico-basal-ganglia-thalamic (CBGT) networks are critical for adaptive decision-making, yet how changes to circuit-level properties impact cognitive algorithms remains unclear. Here we explore how dopaminergic plasticity at corticostriatal synapses alters competition between striatal pathways, impacting the evidence accumulation process during decision-making. Spike-timing dependent plasticity simulations showed that dopaminergic feedback based on rewards modified the ratio of direct and indirect corticostriatal weights within opposing action channels. Using the learned weight ratios in a full spiking CBGT network model, we simulated neural dynamics and decision outcomes in a reward-driven decision task and fit them with a drift-diffusion model. Fits revealed that the rate of evidence accumulation varied with inter-channel differences in direct pathway activity while boundary height varied with overall indirect pathway activity. This multi-level modeling approach demonstrates how complementary learning and decision computations emerge from corticostriatal plasticity. Author summary Cognitive process models like reinforcement learning (RL) and the drift-diffusion model (DDM) have helped to elucidate the basic information algorithms underlying error-corrective learning and the evaluation of accumulating decision evidence leading up to a choice. While these relatively abstract models help to guide experimental and theoretical probes into associated phenomena, they remain uninformative about the actual physical mechanics by which learning and decision algorithms are carried out in a neurobiological substrate during adaptive choice behavior. Here, we present an “upwards mapping” approach to bridging neural and cognitive models of value-based decision making, showing how dopaminergic feedback alters the network-level dynamics of cortico-basal-ganglia-thalamic (CBGT) pathways during learning to bias behavioral choice towards more rewarding actions. By mapping “up” the levels of analysis, this approach yields specific predictions about aspects of neuronal activity that map to the quantities appearing in the cognitive decision-making framework.
Genetic evidence that the latency III stage of Epstein-Barr Virus infection is a therapeutic target for Multiple Sclerosis

Genome wide association studies have identified >200 susceptibility loci accounting for much of the heritability of Multiple Sclerosis (MS). Epstein Barr virus (EBV), a memory B cell tropic virus, has been identified as necessary but not sufficient for development of MS, with evidence for disease causation. The molecular and immunological basis for this has not been established. LCL proliferation is driven by signalling through the EBV produced cell surface protein LMP1, a homologue of the MS risk gene CD40. We show that the CD40 ligand, CD40L, potentially through competitive signalling with LMP1, reduces LCL proliferation (p<0.001). The MS risk variants of the LMP1 signalling inhibitor, TRAF3, had altered expression in B cells and LCLs. Both CD40 and TRAF3 risk SNPs are in binding sites for the EBV transcription factor EBNA2. We have investigated transcriptomes of B cells and EBV infected B cells at Latency III (LCLs) and identified 47 MS risk genes with altered expression, associated with the risk genotype. Overall these MS risk SNPs were overrepresented in target loci of the EBV transcription factor EBNA2 (p<10−16), in genes dysregulated between B and LCLs (p<10−5), and as targets for EBV miRNAs (p<10−4). The risk gene ZC3HAV1 is the putative target for multiple EBV miRNAs. It amplifies the interferon response, and was shown to have reduced expression in LCLs for the risk allele. These data indicate targeting EBV EBNA2, miRNAs, and MS risk genes on the LMP1/LMP2 pathways, and the pathways themselves, may be of therapeutic benefit in MS.
Identifying the needs of postgraduate students: The first step of academic writing courses

Academic writing practices constitute central processes through which students learn the conventions of their disciplines to meet the expectations of their academic communities. Therefore, academic writing courses should touch on the specific dimensions of it. One of the most prominent requirement of these courses is to identify the needs of students and to implement a program based on the negotiation between the needs of students and the expectations of academic communities. The present study aimed to explore the academic writing needs of post-graduate students attending at departments related to English language. The analysis revealed that the participants (30 postgraduate students of English) obtain a clear idea of the disciplinary conventions and the importance communication with readers in academic genres but they did not seem to develop an awareness of building stance in academic genres. There was not a statistical difference between MA and PhD students’ academic writing needs. Apparently, academic writing courses in post-graduate programs should place heavy demands on more specific needs-based curriculum to meet their students’ target needs.
Set-Valued Feedback Control and Its Application to Event-Triggered Sampled-Data Systems

Motivated by challenges in feedback control with event-triggered control input updates, this article studies an ellipsoidal set-valued feedback control problem for linear time-invariant (LTI) discrete-time (DT) systems, and its application to event-triggered control systems. First, a state feedback controller based on the set-valued information is designed for LTI DT systems with disturbances. Then, the stability of the closed-loop system is analyzed, and the state of the closed-loop system is shown to be uniformly ultimately bounded in an ellipsoidal set. Based on the proposed set-valued feedback controller, we consider the case when the event-triggering condition (ETC) is described by an ellipsoidal set for an event-triggered control system. To ensure the requirements on control performance and communication rates simultaneously, an optimal ETC design problem is formulated and its optimal solution is provided. Finally, simulation examples are given to show the effectiveness of the proposed method.
RADIOCARBON DATING AND DIET: THE JIAOJIA SITE IN CHINA

ABSTRACT The Jiaojia site is the earliest city in the Haidai area of China, about 5000 years old. To obtain more accurately the beginning and end of this site, radiocarbon accelerator mass spectrometry (14C AMS) measurements, along with stable carbon and nitrogen isotope data, were collected from 13 bone samples. According to the measured dates, human diet was dominated by C4-based plants, and the Jiaojia site appeared before 2900 BC.
Condensate-Banking Removal and Gas-Production Enhancement Using Thermochemical Injection: A Field-Scale Simulation

Condensate-liquid accumulation in the vicinity of a well is known to curtail gas production up to 80%. Numerous approaches are employed to mitigate condensate banking and improve gas productivity. In this work, a field-scale simulation is presented for condensate damage removal in tight reservoirs using a thermochemical treatment strategy where heat and pressure are generated in situ. The impact of thermochemical injection on the gas recovery is also elucidated. A compositional simulator was utilized to assess the effectiveness of the suggested treatment on reducing the condensate damage and, thereby, improve the gas recovery. Compared to the base case, represented by an industry-standard gas injection strategy, simulation studies suggest a significantly improved hydrocarbon recovery performance upon thermochemical treatment of the near-wellbore zone. For the scenarios investigated, the application of thermochemicals allowed for an extension of the production plateau from 104 days, as determined for the reference gas injection case, to 683 days. This represents a 6.5-fold increase in production plateau time, boosting gas recovery from 25 to 89%. The improved recovery is attributed to the reduction of both capillary pressure and condensate viscosity. The presented work is crucial for designing and implementing thermochemical treatments in tight-gas reservoirs.
Diversity and Distribution of Vascular Epiphytic Flora in Sub-temperate Forests of Darjeeling Himalaya, India

Aims: This communication deals with the diversity and distribution including host species distribution of vascular epiphytes also reflecting its phenological observations. Study Design: Random field survey was carried out in the study site to identify and record the taxa. Host species was identified and vascular epiphytes were noted. Study Site and Duration: The study was conducted in the sub-temperate forests of Darjeeling Himalaya which is a part of the eastern Himalaya hotspot. The zone extends between 1200 to 1850 m amsl representing the amalgamation of both sub-tropical and temperate vegetation. The study was conducted during the year 2018-2019. Methodology: Process of random sampling collection was followed. Host trees with CBH >30 cm were identified and percentage of distribution of epiphytes in the host tree was analyzed and divided into two zones depending on the abundance of epiphytes. Data for the epiphytic plant specimens were collected in the field. Exsiccates were made with the collected voucher specimens and were deposited at the Calcutta University Herbarium (CUH) following the conventional methodology. Study on the taxa are based on their host tree distribution, micro-habitat and phenological status. The location and altitude of the study sites were recorded by global positioning system. Results: A total number of 115 species under 70 genera and 31 families have been identified with 65% other vascular angiosperms (basal angiosperms and eudicots) and 16% monocots. Orchidaceae among the monocots represented 36% with 41 species and 18 genera. Ferns and lycophytes include 25% of the diversity with 29 taxa under 6 families. Most favorable host trees were Ficus auriculata Lour. , Ficus neriifolia Sm. , Saurauia nepalensis DC. , Erythrina variegata L. , Macaranga denticulata (Blume) Müll. Arg. , Cryptomeria japonica (Thunb. ex L.f.) D. Don and Engelhardia spicata Lechen ex Blume. Conclusion: The other vascular angiosperms preferred wet monsoon for flowering whereas spring season was most favourable for Orchidaceae. Although a healthy number of vascular epiphytes have been identified, a number of threats are still prevailing in the regions which are mostly anthropogenic. Proper collaborative strategies have to be maintained for its conservation.
Influence of Verbal Behavior Training on Performance for Sustainable Development in Childhood and Early Adolescence

The effective teaching of language is an aspect of special relevance regarding the good adjustment of children in contexts such as school, family, or community. This article performs an experimental procedure to check which language teaching methodology is most effective in a sample of children. The objective was to analyze the influence of training, Condition 1 (pure tacts more intraverbal) or Condition 2 (pure tacts more impure tacts), on emergence of two tests involving impure tacts (AB-C, AB-D) and four new complex intraverbals (BC-D, BD-C) for each of two sets of stimuli (Set 1 and Set 2). The sample comprised 54 children aged between 6 and 12 years, divided into two groups of different experimental conditions. The results revealed statistically significant differences in performance on the tests of impure tacts and complex intraverbal, obtaining highly effective results in Condition 2. This teaching method using compound stimuli (impure tacts) clearly favors the expansion of language. The practical implications of this work can be more effective language teaching methodologies implemented that favor the good psychosocial adjustment of children in contexts such as family, school, or the community in general.
Convergence and stability analysis of the half thresholding based few-view CT reconstruction

Abstract The projection data obtained using the computed tomography (CT) technique are often incomplete and inconsistent owing to the radiation exposure and practical environment of the CT process, which may lead to a few-view reconstruction problem. Reconstructing an object from few projection views is often an ill-posed inverse problem. To solve such problems, regularization is an effective technique, in which the ill-posed problem is approximated considering a family of neighboring well-posed problems. In this study, we considered the ℓ1/2{\ell_{1/2}} regularization to solve such ill-posed problems. Subsequently, the half thresholding algorithm was employed to solve the ℓ1/2{\ell_{1/2}} regularization-based problem. The convergence analysis of the proposed method was performed, and the error bound between the reference image and reconstructed image was clarified. Finally, the stability of the proposed method was analyzed. The result of numerical experiments demonstrated that the proposed method can outperform the classical reconstruction algorithms in terms of noise suppression and preserving the details of the reconstructed image.
CODING TECHNIQUES THROUGH TWO STAR GRAPHS AND MEAN LABELING

A BSTRACT . In this paper, a method of coding technique is developed using graph labeling and GMJ code. There are two illustrations for coding a text messages using two star graphs K 1 ,λ ∧ K 1 ,µ by applying Mean labeling on it for two different cases µ = λ + 1 and µ = λ + 4 . Pictorial message is presented to induce secrecy by transforming text message into picture code through Mean graph.