Typical Setting Research Articles

Importance of spectrally invariant broadband attenuation of light in indoor photovoltaic characterization

Indoor photovoltaic (IPV) devices are poised to make a significant contribution to the proliferation of the “Internet of Things” (IoT). For the accurate intercomparison of IPVs (and, hence, to advance the rational development of the technology), lighting conditions representative of those in typical indoor settings must be created reproducibly. As indoor lighting is invariably broadband, this will typically require the use of optical attenuation to achieve varying irradiance conditions at the device under test location. However, most forms of optical attenuation will suffer from some degree of spectral dispersion, creating sources of uncertainty for key figures of merit, such as power conversion efficiency. In this work, we examine the contribution of the mode of optical attenuation to the accurate characterization of IPV systems. We discuss requirements for broadband light source attenuation for the accurate characterization of photovoltaic devices under indoor illumination and consider the importance of using suitable reference devices for light intensity calibration. Furthermore, we experimentally verify attenuation methods typically used, including power control of the light source itself, use of neutral density filters, and advanced attenuation based on tandem prism attenuators. Finally, spectral shape alteration-induced uncertainties in performance parameter determination of photovoltaic cells under indoor illumination are quantified for three common broadband light attenuation methods, where we found ∼2%, ∼6%, and up to ∼15% ambiguity in photovoltaic device efficiency when using LED power control, prism attenuators, and neutral density filter-based broadband light attenuation, respectively.

PURE: Passive Multi-Person Identification via Footstep for Mobile Service Networks

Recently, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">passive behavioral biometrics</i> (e.g., gesture or footstep) acquired from wireless networks or mobile services have become promising complements to conventional user identification methods (e.g., face or fingerprint) under special situations, yet existing sensing technologies require lengthy measurement traces and cannot identify multiple users at the same time. To this end, we propose PURE as a passive multi-person identification system leveraging deep learning enabled footstep separation and recognition. PURE passively identifies a user by identifying the unique “footprints” in its footstep. Different from existing gait-enabled recognition systems incurring a long sensing delay to acquire many footsteps, PURE can recognize a person by as few as only one step, substantially cutting the identification latency. To make PURE adaptive to walking pace variations, environmental dynamics, and even unseen targets, we apply an adversarial learning technique to improve its domain generalisability and identification accuracy. Finally, PURE is robust against replay attack, enabled by the richness of footstep and spatial awareness. We implement a PURE prototype using commodity hardware and evaluate it in typical indoor settings. Evaluation results demonstrate a cross-domain identification accuracy of over 90%.

The 28 October 2022 Mw 3.8 Goesan Earthquake Sequence in Central Korea: Stress Drop, Aftershock Triggering, and Fault Interaction

ABSTRACT We identified the causative fault of the 2022 Goesan, Korea, earthquake sequence based on the precise relocation of the sequence that revealed a 0.8 km-long fault plane striking east-southeast–west-northwest. The fault plane encompasses the largest foreshock, the mainshock, and the majority of the aftershocks. The orientation of the fault plane is consistent with the left-lateral strike-slip motion along the east-southeast (106°) striking nodal plane of the focal mechanism. The Jogok fault system recently mapped in the source area runs through the mainshock epicenter with a consistent strike and left-lateral strike-slip motion, which suggests that it is the likely causative fault of the 2022 Mw 3.8 Goesan earthquake sequence. It is a rare case of assigning a causative fault for a small-sized (Mw 3.8) earthquake with some confidence in a typical stable continental region setting, albeit no surface break observed due to deep focal depth (~13 km) and the small size of the event. Aftershocks on the main fault plane, and on the adjacent subparallel fault patches seemed to be triggered by the increase in Coulomb stress caused by the mainshock. Two large aftershocks on the subparallel fault patches show slightly higher stress drops than the large foreshock and mainshock on the main fault plane, likely due to high frictional strength on those fault patches. Events of the 2022 Goesan earthquake sequence progressed rapidly in time and appear to be high stress-drop events compared with other earthquakes that occurred in other regions in Korea, probably due to the long quiescent period in the Goesan earthquake epicentral region.

Multi-objective multi-agent deep reinforcement learning to reduce bus bunching for multiline services with a shared corridor

Bus bunching is a long-standing problem in transit operation and ruining the regularity of transit service. In a typical urban transit network setting of multiple lines with a shared corridor, bus bunching becomes more frequent as there is more uncertainty inside the shared corridor. While multi-agent reinforcement learning (MARL) has been a promising scheme for learning efficient control policy in a multi-agent system, few studies have explored its applicability in multi-line transit control scenarios. In this study, we focus on a basic transit network where there are two bus lines with a shared corridor. An efficient MARL framework is proposed to learn multi-line bus holding control to avoid bus bunching. Specifically, we design observation and reward functions that incorporate multi-line information. In addition, a preference weights producer is introduced to update the objective weights towards a good trajectory evaluation during daily transit operation. In this way, we handle the multi-objective issue in multi-line control. In experimental studies, we validate the superiority of the method in real-world bus lines. Results show that the state and reward augmented with multi-line information benefit MARL in multi-line bus control. Besides, by updating preference weights towards less passenger waiting time, the regularity of transit service is further improved.

Influence of ultrasound machine settings on quantitative measures derived from spatial frequency analysis of muscle tissue

BackgroundUltrasound is a powerful tool for diagnostic purposes and provides insight into both normal and pathologic tissue structure. Spatial frequency analysis (SFA) methods characterize musculoskeletal tissue organization from ultrasound images. Both sonographers in clinical imaging and researchers may alter a minimized range of ultrasound settings to optimize image quality, and it is important to know how these small adjustments of these settings affect SFA parameters. The purpose of this study was to investigate the effects of making small adjustments in a typical default ultrasound machine setting on extracted spatial frequency parameters (peak spatial frequency radius (PSFR), Mmax, Mmax%, and Sum) in the biceps femoris muscle.MethodsLongitudinal B-mode images were collected from the biceps femoris muscle in 36 participants. The window depth, foci locations, and gain were systematically adjusted consistent with clinical imaging procedures for a total of 27 images per participant. Images were analyzed by identifying a region of interest (ROI) in the middle portion of the muscle belly in a template image and using a normalized two-dimensional cross-correlation technique between the template image and subsequent images. The ROI was analyzed in the frequency domain using conventional SFA methods. Separate linear mixed effects models were run for each extracted parameter.ResultsPSFR was affected by modifications in focus location only (p < 0.001) with differences noted between all locations. Mmax% was influenced by the interaction of gain and focus location (p < 0.001) but was also independently affected by increasing window depth (p < 0.001). Both Mmax and Sum parameters were sensitive to small changes in machine settings with the interaction of focus location and window depth (p < 0.001 for both parameters) as well as window depth and gain (p < 0.001 for both) influencing the extracted values.ConclusionsFrequently adjusted imaging settings influence some SFA statistics. PSFR and Mmax% appear to be most robust to small changes in image settings, making them best suited for comparison across individuals and between studies, which is appealing for the clinical utility of the SFA method.

What Factors Are Associated With Arterial Line–Related Limb Ischemia in Patients on Extracorporeal Membrane Oxygenation? A Single-Center Retrospective Cohort Study

The primary purpose of this study was to identify factors associated with the development of arterial line-related limb ischemia in patients on extracorporeal membrane oxygenation (ECMO). The authors also sought to characterize and report the outcomes of patients who developed arterial line-related limb ischemia. Retrospective cohort study. A single academic tertiary referral ECMO center. Consecutive patients who were treated with ECMO over 6 years. Use of arterial line. A total of 278 consecutive ECMO patients were included, with 19 (7%) patients developing arterial line-related limb ischemia during the ECMO run. Postcannulation Sequential Organ Failure Assessment (SOFA) (adjusted odds ratio [aOR] 1.20, 95% CI 1.08-1.32), Acute Physiology and Chronic Health Evaluation-II (aOR 0.84, 95% CI 0.74-0.95), and adjusted Vasopressor Dose Equivalence (aOR 1.03, 95% CI 1.01-1.05) scores were independently associated with the development of arterial line-associated limb ischemia. A SOFA score of ≥17 at the time of ECMO cannulation had an 80% sensitivity and 87% specificity for predicting arterial line-related limb ischemia. Arterial line-related limb ischemia is much more common in ECMO patients than in the typical intensive care unit setting. The SOFA score may be useful in identifying which patients may be at risk for arterial line-related limb ischemia. As this was a single-center retrospective study, these results are inherently exploratory, and prospective multicenter studies are necessary to validate these results.

An educational model for special patient care in dentistry.

Dental school graduates often have a basic knowledge in the management of patients with specialized healthcare needs. As of August 2019, CODA amended their accreditation standard 2-25: dental school graduates must be competent in the assessment and management of treatment of patients with specialized healthcare needs and disabilities. While the majority of these patients require modified dental care, many dental schools lack the facilities to provide both the proper care and education. This paper identifies improvements to dental education brought on by the innovations at Penn Dental Medicines' Personalized Care Suite for Persons with Disabilities (PCARE). Patient centered care is the emphasis of the PCARE curriculum. Although the clinic has special rooms and equipment to assist in accommodating the special needs of the patients, the program focuses on teaching dental students how to provide comfortable, safe, and effective care in a typical office setting. Detailed patient assessment, non-pharmacological management techniques, and treatment plans designed to meet the needs and abilities of the patients and caregivers are taught through lecture and direct patient care. Teaching assessment and management of this population is of great importance. Including treatment in Standard 2-25 creates another challenge to dental education. Penn Dental's facility allows multidisciplinary care in a cohesive and timely manner. The experience in PCARE offers unique opportunities to educate dental professionals in developing a patient centered approach in the treatment and maintenance of oral health in those patients who require accommodation.

Clinical Management of COPD in the Real World: Can Studies Reveal Errors in Management and Pathways to Improve Patient Care?

Real world data comprise information on health care that is derived from multiple sources outside typical clinical research settings. This review focuses on what real world evidence tells us about problems with the diagnosis of chronic obstructive pulmonary disease (COPD), problems with the initial and follow-up pharmacological and non-pharmacological management, problems with the management of exacerbations and problems with palliative care. Data from real world studies show errors in the management of COPD with delays to diagnosis, lack of confirmation of the diagnosis with spirometry, lack of holistic assessment, lack of attention to smoking cessation, variable adherence to management guidelines, delayed implementation of appropriate interventions, under-recognition of patients at higher risk of adverse outcomes, high hospitalisation rates for exacerbations and poor implementation of palliative care. Understanding that these problems exist and considering how and why they occur is fundamental to developing solutions to improve the diagnosis and management of patients with COPD.

Sensing in Sacral Neuromodulation: A Feasibility Study in Subjects With Urinary Incontinence and Retention

ObjectivesSacral neuromodulation (SNM) therapy standard of care relies on visual-motor responses and patient-reported sensory responses in deciding optimized lead placement and programming. Automatic detection of stimulation responses could offer a simple, consistent indicator for optimizing SNM. The purpose of this study was to measure and characterize sacral evoked responses (SERs) resulting from sacral nerve stimulation using a commercial, tined SNM lead. Materials and MethodsA custom external research system with stimulation and sensing hardware was connected to the percutaneous extension of an implanted lead during a staged (tined lead) evaluation for SNM. The system collected SER recordings across a range of prespecified stimulation settings (electrode configuration combinations for bipolar stimulation and bipolar sensing) during intraoperative and postoperative sessions in 21 subjects with overactive bladder (OAB) and nonobstructive urinary retention (NOUR). Motor and sensory thresholds were collected during the same sessions. ResultsSERs were detected in all 21 subjects. SER morphology (number of peaks, magnitude, and timing) varied across electrode configurations within and across subjects. Among subjects and electrode configurations tested, recordings contained SERs at motor threshold and/or sensory threshold in 75% to 80% of subjects. ConclusionsThis study confirmed that implanted SNM leads can be used to directly record SERs elicited by stimulation in subjects with OAB and NOUR. SERs were readily detectable at typical SNM stimulation settings and procedural time points. Using these SERs as possible objective measures of SNM response has the capability to automate patient-specific SNM therapy, potentially providing consistent lead placement, programming, and/or closed-loop therapy.

An Online Toolkit for Applications Featuring Collaborative Robots Across Different Domains

Collaborative robots (cobots) are being applied in areas such as healthcare, rehabilitation, agriculture and logistics, beyond the typical manufacturing setting. This is leading to a marked increase in the number of cobot stakeholders with little or no experience in traditional safety engineering. Considering the importance of human safety in collaborative robotic applications, this is currently proving to be a barrier to more widespread cobot usage. A web-based Toolkit that targets cobot end-users and manufacturers with varying levels of safety expertise was developed, helping them to understand how to consider the safety of their cobot applications. In this work, we will provide an overview of the state of the art for ensuring cobot safety, highlight the support provided by the “COVR Toolkit” and introduce three examples where third parties applied the Toolkit for their collaborative robotics application.

Data-Aided CSI Estimation Using Affine-Precoded Superimposed Pilots in Orthogonal Time Frequency Space Modulated MIMO Systems

An orthogonal affine-precoded superimposed pilot (AP-SIP)-based architecture is developed for the cyclic prefix (CP)-aided single input single output (SISO) and multiple input multiple output (MIMO) orthogonal time frequency space (OTFS) systems relying on arbitrary transmitter-receiver (Tx-Rx) pulse shaping. The data and pilot symbol matrices are affine-precoded and superimposed in the delay Doppler (DD)-domain followed by the development of an end-to-end DD-domain relationship for the input-output symbols. At the receiver, the decoupled pilot and data symbol are extracted by employing orthogonal precoder matrices, which eliminates the mutual interference. Furthermore, a novel pilot-aided Bayesian learning (PA-BL) technique is conceived for the channel state information (CSI) estimation of SISO OTFS systems based on the expectation-maximization (EM) technique. Subsequently, a data-aided Bayesian learning (DA-BL)-based joint CSI estimation and data detection technique is proposed, which beneficially harnesses the estimated data symbols for improved CSI estimation. In this scenario our sophisticated data detection rule also integrates the CSI uncertainty of channel estimation into our the linear minimum mean square error (LMMSE) detectors. The AP-SIP framework is also extended to MIMO OTFS systems, wherein the DD-domain input matrix is affine-precoded for each transmit antenna (TA). Then an EM algorithm-based PA-BL scheme is derived for simultaneous row-group sparse CSI estimation for this system, followed also by our data-aided DA-BL scheme that performs joint CSI estimation and data detection. Moreover, the Bayesian Cramer-Rao bounds (BCRBs) are also derived for both SISO as well as MIMO OTFS systems. Finally, simulation results are presented for characterizing the performance of the proposed CSI estimation techniques in a range of typical settings along with their bit error rate (BER) performance in comparison to an ideal system having perfect CSI.

Constraints on the origin of the cenozoic intraplate aldama volcanic field, tamaulipas, NE México

The Cenozoic Aldama Volcanic Field (8–0.24 Ma) is located on the southeastern margin of the Sierra de Tamaulipas and is the largest field of the Eastern Mexican Alkaline Province. It contains cinder cones, tuff rings, maars, and simple cones, as well as widespread lava flows. The volcanic rocks are geochemically characterized as alkali basalts, subalkaline basalts, trachybasalts (potassic and hawaiites), latites to trachytes, and grouped in six rock types according to their Mg-content and normative composition: (a) Alkaline near-primary rocks, (b) Alkaline basic rocks, (c) Alkaline intermediate rocks, (d) Subalkaline near-primary rocks, (e) Subalkaline basic rocks, and (f) Subalkaline intermediate rocks.Trace elements and isotopic ratios show that the source of the basaltic melts displays asthenospheric characteristics and stability conditions, indicating that the partial melting (<5%) occurred in lithospheric levels within the spinel stability depth. The coexistence in time and space of alkaline and subalkaline rocks could be explained by selective alkali metasomatism of a regional HFSE and REE-enriched OIB-like source. The magma generation occurred in a typical continental intraplate setting, associated with mantle disturbances produced by the eclogitization and detachment of the Hess conjugate subducted under NE Mexico. Some alkaline and subalkaline melts evolved to intermediate members by fractional crystallization.

High-Speed Automated Reconstruction of Drosophila Larval Brain from Volumetric EM Data.

To uncover the relationship between neural activity and behavior, it is essential to reconstruct neural circuits. However, methods typically used for neuron reconstruction from volumetric electron microscopy (EM) dataset are often time-consuming and require extensive manual proofreading, making it difficult to reproduce in a typical laboratory setting. To address this challenge, we have developed a set of acceleration techniques that build upon the Flood Filling Network (FFN), significantly reducing the time required for this task. These techniques can be easily adapted to other similar datasets and laboratory settings. To validate our approach, we tested our pipeline on a dataset of Drosophila larval brain serial section EM images at synaptic-resolution level. Our results demonstrate that our pipeline significantly reduces the inference time compared to the FFN baseline method and greatly reduces the time required for reconstructing the 3D morphology of neurons.

Infrared thermography monitoring of rock faces – Potential and pitfalls

Rock surface temperatures are of fundamental importance for studies on weathering, rockfall and permafrost. Point temperature measurements may not reflect the small-scale variability of temperature as a function of micro-topography. To close this gap, infrared thermography (IRT) seems to be a simple and promising approach. However, there are several pitfalls in terms of interpretation, as radiation temperatures depend on emissivity and reflectivity of the rock, which in turn are influenced by rock type, surface roughness, wetness, surrounding weather conditions, and angle to the camera axis.We performed laboratory and exemplary field experiments in order to estimate the magnitude of possible errors. We used rough and smooth (sawn) specimen of six different stone types in wet and dry condition and took IRT images at different tilt angles between camera axis and rock surface. Furthermore, we applied the approach to a small rock outcrop (approx. 3 × 3 m) and to a rockwall (approx. 100 × 100 m).The results of the laboratory measurements show that the temperature error increases with increasing tilt angle of the rock surface. Depending on the nature of the reflected surroundings, radiation temperatures can be warmer or cooler than sensor temperatures. In typical settings, the error is low (<0.5 K) up to a tilt of 40° but it may increase to >1 K at tilt angles of 50° and more. Smooth and wet surfaces tend to be more prone to deviations.The field examples confirm the results of the laboratory tests. But they show that spatial differences in temperature can still be detected as the “true” differences are usually larger than the magnitude of error. We suggest to reduce the error of the IRT image by correcting temperatures using a high-resolution surface model.

Resilient Localization and Coverage in the Internet of Things

The proliferation of the Internet of Things (IoT) has revolutionized traditional services, giving rise to emerging smart infrastructures by connecting the physical and digital worlds. Sensory data is essential in IoT-based systems for providing context-aware and location-based services. Hence, the accurate localization of IoT devices is paramount. Anchor misplacement can significantly affect location information and coverage services in IoT. We study the effect of anchor misplacement in typical IoT settings where sensors are randomly deployed, can be mobile, and may belong to multiple providers. We identify sensing coverage holes formed by anchor misplacement and analyze their presence and impact. To mitigate the impact of anchor misplacement on network reliability, we propose a framework to identify the affected sensor nodes and then identify and remove misplaced anchor nodes. The validity of our approach is verified, and its effectiveness is demonstrated by several experiments with different network topologies and parameters. Our results are promising and can be utilized in multiple coverage applications, such as smart agriculture systems and habitat monitoring, regardless of the sensors or deployment types. It also sheds light on best practices and methods for a reliable design of IoT-based systems.

Obstacles and strategies in ecosystem governance: a view from the orchestrator side

PurposePlatform ecosystem governance is a decisive issue for orchestrators, as the motivation and behaviors of the complementors in an ecosystem can be distinctly different, shaped by the specific arrangements they have within the ecosystem. However, knowledge about adaptation in the governance of platform ecosystems is quite limited. First, the authors hardly know which obstacles are arising for orchestrators due to typical governance settings and their consequences. Second, the authors know less about governance strategies by orchestrators that help deal with these obstacles.Design/methodology/approachThe authors follow an inductive, multistep case-study-based approach with multiple cases using guidelines proposed by Yin (2018). Based on predefined criteria, the authors selected 41 platform ecosystems with a “hub and spoke” system within and across several industries and collected a wide range of data. The authors conducted 14 interviews with executives of these platform ecosystems to gain further insights, transcribed and/or summarized all interviews, and analyzed the data.FindingsBased on the dataset, the authors identify four significant obstacles and ten strategies of orchestrators in platform ecosystems. This approach allows us to gain insight into innovative approaches orchestrators conduct to cope with these challenges.Originality/valueThe authors already have a broad range of studies on ecosystem governance in the literature. However, research dealing with the dynamics of governance regimes is quite rare. The study examines how orchestrators of platform ecosystems react to emerging obstacles they are confronted with during the evolution of their platform ecosystems. Partly, these strategies might be expected, but mostly they show innovative approaches for handling these obstacles that have not been reported in research so far.

Quantum criticality enabled by intertwined degrees of freedom

Strange metals appear in a wide range of correlated materials. Electronic localization-delocalization and the expected loss of quasiparticles characterize beyond-Landau metallic quantum critical points and the associated strange metals. Typical settings involve local spins. Systems that contain entwined degrees of freedom offer new platforms to realize unusual forms of quantum criticality. Here, we study the fate of an SU(4) spin-orbital Kondo state in a multipolar Bose-Fermi Kondo model, which provides an effective description of a multipolar Kondo lattice, using a renormalization-group method. We show that at zero temperature, a generic trajectory in the model's parameter space contains two quantum critical points, which are associated with the destruction of Kondo entanglement in the orbital and spin channels, respectively. Our asymptotically exact results reveal an overall phase diagram, provide the theoretical basis to understand puzzling recent experiments of a multipolar heavy fermion metal, and point to a means of designing different forms of quantum criticality and strange metallicity in a variety of strongly correlated systems.

Wavelength-multiplexing high-spectral resolution imaging based on Fourier ptychographic microscopy

A wide field of view (FOV), high spectral resolution, and high spatial resolution are the targets of optical microscopic imaging. Fourier ptychographic microscopy (FPM) imaging can solve the contradiction between a wide FOV and spatial resolution. However, the spectral resolution of the samples is not accessible to typical LED-based FPM. Here, we report a wavelength-multiplexing high-spectral resolution reconstruction strategy based on the FPM of the halogen lamp. In contrast to the typical FPM setting, we can obtain spectral information of arbitrary wavelengths and greatly improve the sampling efficiency. We optimize and combine the wavelength-multiplexed decoupled algorithm with the high-spectral resolution reconstruction algorithm. We show that, by using our strategy, we can better reconstruct the image with a spectral resolution of 5 nm and maintain wide FOV and high spatial resolution. We believe the reported strategy may provide ideas for FPM-based spectral microimaging.

Cooperative, Connected and automated mobility (CCAM) services provisioning in cross-border settings: Techno-economic analysis in the light of technical challenges

Cooperative, connected and automated mobility (CCAM) has a great potential to change drastically the mobility landscape and improve safety on the roads by assisting drivers to take the best decisions in given circumstances or by supporting autonomous driving features aboard the car, among other expected benefits. Yet, providing CCAM services poses not only technical but also business challenges, especially in cross-border environments. In this paper, we present a general techno-economic methodology intended first, to identify the cross-border ecosystem and the potential business models to enable CCAM services provision and second, to derive the Total Cost of Ownership (TCO) of deploying the required Vehicle to Infrastructure (V2I) and Vehicle to Network (V2N) infrastructure. As an illustration, we then apply this methodology to a canonical Cooperative Lane Merging (CLM) scenario in a representative border environment (i.e., the Brenner pass between Italy and Austria). On this occasion, the impact of Multi-access Edge Computing (MEC) placement on the deployment cost is also discussed and finally, a cost allocation model is developed to link these deployment costs to the key stakeholders within the identified business models. Results aim to give insights into the different deployment strategies in typical cross-border environments and settings.

Woody plant diversity and aboveground carbon stock of Dipterocarpus chartaceus dominant forests in Binh Chau-Phuoc Buu Nature Reserve, South Vietnam

Abstract. Hop NV, Quy NV, Lam NV, Trong PT, Thinh PC. 2023. Woody plant diversity and aboveground carbon stock of Dipterocarpus chartaceus dominant forests in Binh Chau-Phuoc Buu Nature Reserve, South Vietnam. Asian J For: 114-124. The dominant forest of Dipterocarpus chartaceus Symington in Binh Chau-Phuoc Buu Nature Reserve, South Vietnam, has an important ecological role and high conservation value relevant to climate change by storing large amounts of CO2 from the atmosphere. This study assesses the diversity of woody plants and estimates biomass and carbon stocks in different forest states. The study used a typical sample plot setting method was used. Trees with a Diameter at Breast Height (DBH) &gt; 6 cm were measured, and species were identified in 9 sample plots of 50m x 20m in the very poor, poor, and medium forests. A total of 640 tree individuals belonging to 45 species, 34 genera, and 25 families were recorded. The most species-rich family was represented by Dipterocarpaceae (7 species). A total of 15 threatened species (33.33%) belonging to 11 genera from 8 families were listed in the Vietnam Red Data Book (2007) and IUCN Red List (2022). The Margalef (d), Shannon-Wiener (H'), Simpson (Cd), and Sorensen Index (SI) were analyzed for tree species. The study illustrated that medium forests had the highest diversity, followed by poor forests, and the lowest belonged to very poor forests. The ability to accumulate biomass and aboveground carbon stocks varied widely from 48.15 t/ha-196.15 t/ha and 24.07 Ct/ha-98.42 Ct/ha. The medium forest had the highest total carbon stock, followed by the very poor forest and the lowest poor forest. The study provides an essential database for strategies and plans for conserving plant biodiversity and improving the power of CO2 accumulation to adapt to climate change.