Miracle-dz/UniFAR-FTUs huggingface dataset:
Advanced NEMS-based power management for 3D Stacked Integrated Circuits

In this paper we introduce a novel power management architecture for 3D Through Silicon Vias based integration technology. Our approach relies on the synergy of two new technological developments as follows: (i) we utilize a Nano-ElectroMechanical (NEM) device, the Suspended Gate FET (SG-FET), as sleep transistor; and (ii) we make use of the 3D potential by placing the sleep transistor (the entire power management infrastructure) on a dedicated tier of the 3D stacked Integrated Circuit. Due to the extreme low leakage current of the SG-FET our proposal results in 2 orders of magnitude static power reduction, when compared with equivalent counterparts based on traditional CMOS devices. The SG-FET power switch requires about 4× more area when compared to bulk CMOS, however, due to the 3D integration which allows for heterogeneous dies to be stacked, the power gating devices can be placed to a low cost dedicated layer, which also results in a substantial IR-drop reduction with minimum impact on leakage.
Role of quantitative nuclear cytomorphometric and NOR dots count in prediction of carcinogenic induced oral cellular proliferative activity

Introduction: To find a better way for predicting the cellular proliferative activity of apparently healthy oral epithelium exposed to certain carcinogens. Methods: The nuclear area (NA) and nucleolar organizer regions (NORs) counts were compared with that of cytological atypia in 100 cases of epithelia exposed to toombak (carcinogen), 100 controls (non­exposed) and two cases of squamous cell carcinoma (SCC), as internal controls. Results: Significant differences in AgNOR (p<0.001) mean count and NA mean values (P<0.001) were identified between cases and controls. Significant differences were also noted in AgNOR mean count and NA mean values between cases and two cases of SCC. Conclusions: AgNOR mean count and NA are useful markers for prediction of cytologically non­evident proliferative activity of oral mucosa exposed to carcinogens.
HSPC159 promotes proliferation and metastasis by inducing epithelial‐mesenchymal transition and activating the PI3K/Akt pathway in breast cancer

HSPC159 is a novel human galectin‐related protein that has been shown to be involved in carcinogenesis. Little is known about HSPC159 expression and function in breast cancer. Herein we showed that HSPC159 was aberrantly expressed in both breast cancer cell lines and tumor tissues and that its expression was associated with poor prognosis of breast cancer patients. Using gain‐ and loss‐of‐function methods we found that HSPC159 enhanced breast cancer cell proliferation and metastasis in vitro and in vivo. Mechanistically, HSPC159 was found to induce epithelial‐mesenchymal transition (EMT) and the F‐actin polymerization process of breast cancer cells. Moreover, HSPC159 promoted proliferation, migration and invasion through activating the PI3K/Akt signaling pathway in breast cancer. In conclusion, our findings showed that HSPC159 contributed to breast cancer progression through the PI3K/Akt pathway and might serve as a potential therapeutic target for the treatment of breast cancer.
BRAIN CONTROL OF ROBOTIC ARM USING AFFECTIVE STEADY-STATE VISUAL EVOKED POTENTIALS

The recent emergence of successfully performing BrainComputer Interfaces (BCI) has given new hope to the disabled and elderly populations for improvements in quality of life. However, most non-invasive BCI systems which allow direct brain-to-machine control still have rather limited capabilities. Visual-flicker-based SSVEPBCI systems have received increased attention due to their potential capability to provide a large number of commands with high reliability. Yet, researchers have had limited success improving further the single-trial extraction of the weak SSVEP oscillations buried in strong brain ‘noise’. In a previous study we have shown that the optimization of the stimulus properties is essential for the enhanced performance of SSVEP–based BCI designs. This paper presents substantial enhancements in the brain response and the processing algorithms necessary for reliable multi-command SSVEP-BCI systems. The visual perception of flickering emotional video, instead of neutral checkerboards, enhanced substantially the measurable SSVEP responses of the brain. Furthermore, a single-trial phase-locking gradient measure was found to be more reliable and resulted in decreased variability when compared to wavelet energy changes. When BCI users operated a robotic arm with this Hybrid BCI platform, the speed, reliability, and information transfer rates were substantially improved when utilizing the proposed affective flicker paradigm.
KIF16B is a candidate gene for a novel autosomal‐recessive intellectual disability syndrome

Intellectual disability (ID) and global developmental delay are closely related; the latter is reserved for children under the age of 5 years as it is challenging to reliably assess clinical severity in this population. ID is a common condition, with up to 1%–3% of the population being affected and leading to a huge social and economic impact. ID is attributed to genetic abnormalities most of the time; however, the exact role of genetic involvement in ID is yet to be determined. Whole exome sequencing (WES) has gained popularity in the workup for ID, and multiple studies have been published examining the diagnostic yield in identification of the disease‐causing variant (16%–55%), with the genetic involvement increasing as intelligence quotient decreases. WES has also accelerated novel disease gene discovery in this field. We identified a novel biallelic variant in the KIF16B gene (NM_024704.4:c.3611T > G) in two brothers that may be the cause of their phenotype.
Robust pulmonary lobe segmentation against incomplete fissures

As important anatomical landmarks of the human lung, accurate lobe segmentation may be useful for characterizing specific lung diseases (e.g., inflammatory, granulomatous, and neoplastic diseases). A number of investigations showed that pulmonary fissures were often incomplete in image depiction, thereby leading to the computerized identification of individual lobes a challenging task. Our purpose is to develop a fully automated algorithm for accurate identification of individual lobes regardless of the integrity of pulmonary fissures. The underlying idea of the developed lobe segmentation scheme is to use piecewise planes to approximate the detected fissures. After a rotation and a global smoothing, a number of small planes were fitted using local fissures points. The local surfaces are finally combined for lobe segmentation using a quadratic B-spline weighting strategy to assure that the segmentation is smooth. The performance of the developed scheme was assessed by comparing with a manually created reference standard on a dataset of 30 lung CT examinations. These examinations covered a number of lung diseases and were selected from a large chronic obstructive pulmonary disease (COPD) dataset. The results indicate that our scheme of lobe segmentation is efficient and accurate against incomplete fissures.
Synaptic Release of Acetylcholine Rapidly Suppresses Cortical Activity by Recruiting Muscarinic Receptors in Layer 4

Cholinergic afferents from the basal forebrain (BF) can influence cortical activity on rapid time scales, enabling sensory information processing and exploratory behavior. However, our understanding of how synaptically released acetylcholine (ACh) influences cellular targets in distinct cortical layers remains incomplete. Previous studies have shown that rapid changes in cortical dynamics induced by phasic BF activity can be mediated by the activation of nicotinic ACh receptors (nAChRs) expressed in distinct types of GABAergic interneurons. In contrast, muscarinic ACh receptors (mAChRs) are assumed to be involved in slower and more diffuse ACh signaling following sustained increases in afferent activity. Here, we examined the mechanisms underlying fast cholinergic control of cortical circuit dynamics by pairing optical stimulation of cholinergic afferents with evoked activity in somatosensory cortical slices of mice of either sex. ACh release evoked by single stimuli led to a rapid and persistent suppression of cortical activity, mediated by mAChRs expressed in layer 4 and to a lesser extent, by nAChRs in layers 1–3. In agreement, we found that cholinergic inputs to layer 4 evoked short-latency and long-lasting mAChR-dependent inhibition of the large majority of excitatory neurons, whereas inputs to layers 1–3 primarily evoked nAChR-dependent excitation of different classes of interneurons. Our results indicate that the rapid cholinergic control of cortical network dynamics is mediated by both nAChRs and mAChRs-dependent mechanisms, which are expressed in distinct cortical layers and cell types. SIGNIFICANCE STATEMENT Acetylcholine (ACh) release from basal forebrain (BF) afferents to cortex influences a variety of cognitive functions including attention, sensory processing, and learning. Cholinergic control occurs on the time scale of seconds and is mediated by BF neurons that generate action potentials at low rates, indicating that ACh acts as a point-to-point neurotransmitter. Our findings highlight that even brief activation of cholinergic afferents can recruit both nicotinic and muscarinic ACh receptors expressed in several cell types, leading to modulation of cortical activity on distinct time scales. Furthermore, they indicate that the initial stages of cortical sensory processing are under direct cholinergic control.
Effect of Exercise on Cognition, Conditioning, Muscle Endurance, and Balance in Older Adults With Mild Cognitive Impairment: A Randomized Controlled Trial

Background and Purpose: Mild cognitive impairment (MCI) may be a precursor to dementia; however, its progression may be prevented or slowed with exercise. This study aimed at determining the effects of group aerobic and strength training on cognition, conditioning, muscle endurance, and balance in underprivileged community-dwelling older adults with MCI. Methods: This was a single-blind, randomized, and matched-pair controlled (gender, age, body mass index, and Addenbrooke's Cognitive Examination—Revised for MCI diagnosis) clinical trial. It was developed in 4 community centers. Fifty-two sedentary, functionally independent individuals, aged 60 years or more, with MCI were randomized into intervention group (n = 26) and control group (n = 26). Participants were tested before and after a 24-week exercise program. Sociodemographic characteristics, cognition (Mini-Mental State Examination), conditioning (2-minute stationary walk test), lower-limb endurance (30-second sit/stand test), and balance data (Functional Reach test) were collected. The intervention group walked and exercised twice weekly (60 minutes each) using ankle weights, latex resistance bands, and dumbbells. The exercise load and intensity were regularly increased on the basis of a preestablished incremental number of sets and repetitions and on the basis of the participants' correct movement execution with a given load. Data were analyzed with Pearson &khgr;2 test, Fisher exact test, Student t test, Mann-Whitney U test, 2-way repeated measures analysis of variance, and the Cohen d. Results and Discussion: Before the intervention, no significant differences were found between groups for any of the variables. Postintervention, significant differences were observed in cognition, conditioning, muscle endurance, and balance. Significant time-by-group interactions were detected in all the intergroup analyses. The improvements observed in the intervention group had medium to large effect sizes (0.35-1.15). The control group's decrease in cognition (13.9%) had a large effect size, while its Functional Reach test decrease (11.4%) had a medium effect size, with no significant change in conditioning or muscle endurance. Conclusion: The training program improved cognitive function, muscle endurance, aerobic conditioning, and balance in older adults with MCI.
Massively Parallel Algorithms for Finding Well-Connected Components in Sparse Graphs

Massively parallel computation (MPC) algorithms for graph problems have witnessed a resurgence of interest in recent years. Despite major progress for numerous graph problems however, the complexity of the sparse graph connectivity problem in this model has remained elusive: While classical logarithmic-round PRAM algorithms for finding connected components in any n-vertex graph have been known for more than three decades (and imply the same bounds for MPC model), no o(log n)-round MPC algorithms are known for this task with truly sublinear in n memory per machine (which is the only interesting regime for sparse graphs with O(n) edges). It is conjectured that an o(log n)-round algorithm for connectivity on general sparse graphs with n1-Ω (1) per-machine memory may not exist, a conjecture that also forms the basis for multiple conditional hardness results on the round complexity of other problems in the MPC model. We take an opportunistic approach towards the sparse graph connectivity problem by designing an algorithm with improved performance in terms of the connectivity structure of the input graph. Formally, we design an MPC algorithm that finds all connected components with spectral gap at least λ in a graph in O(log log n + log(1/λ)) MPC rounds and nδ memory per machine for any constant δ ∈ (0,1). While this algorithm still requires Θ(log n) rounds in the worst-case, it achieves an exponential round reduction on "well-connected'' components with λ ≥ 1/polylog(n) using only nδ memory per machine and ł(n) total memory, and still operates in o(log n)l rounds even when λ = 1/no(1). En-route to our main result, we design a new distributed data structure for performing independent random walks from all vertices simultaneously, as well as a new leader-election algorithm with exponentially faster round complexity on random graphs.
Composition-related structural transition of random peptides: insight into the boundary between intrinsically disordered proteins and folded proteins

Previous studies based on bioinformatics showed that there is a sharp distinction of structural features and residue composition between the intrinsically disordered proteins and the folded proteins. What induces such a composition-related structural transition? How do various kinds of interactions work in such processes? In this work, we investigate these problems based on a survey on peptides randomly composed of charged residues (including glutamic acids and lysines) and the residues with different hydrophobicity, such as alanines, glycines, or phenylalanines. Based on simulations using all-atom model and replica-exchange Monte Carlo method, a coil-globule transition is observed for each peptide. The corresponding transition temperature is found to be dependent on the contents of the hydrophobic and charged residues. For several cases, when the mean hydrophobicity is larger than a certain threshold, the transition temperature is higher than the room temperature, and vise versa. These thresholds of hydrophobicity and net charge are quantitatively consistent with the border line observed from the study of bioinformatics. These results outline the basic physical reasons for the compositional distinction between the intrinsically disordered proteins and the folded proteins. Furthermore, the contributions of various interactions to the structural variation of peptides are analyzed based on the contact statistics and the charge-pattern dependence of the gyration radii of the peptides. Our observations imply that the hydrophobicity contributes essentially to such composition-related transitions. Thus, we achieve a better understanding on composition–structure relation of the natural proteins and the underlying physics.
Cell-based screen for discovering lipopolysaccharide biogenesis inhibitors

Significance The outer membrane of gram-negative bacteria contains LPS on the cell surface. The presence of LPS creates an effective permeability barrier that protects gram-negative bacteria from small hydrophobic molecules. Because the entire LPS biogenesis pathway, including biosynthesis and transport, is highly conserved, proteins involved are attractive targets for antibiotic discovery. Historically, it has been challenging to target LPS biogenesis since many of the components are membrane proteins with hard-to-assay activities. Utilizing the nonessentiality of this pathway in a gram-negative pathogen, we developed a cell-based screen specific to LPS biogenesis. We identified a small-molecule inhibitor targeting an essential component of the pathway, MsbA, and validated it as an antibacterial target using a combination of genetics, biochemistry, and cellular assays. New drugs are needed to treat gram-negative bacterial infections. These bacteria are protected by an outer membrane which prevents many antibiotics from reaching their cellular targets. The outer leaflet of the outer membrane contains LPS, which is responsible for creating this permeability barrier. Interfering with LPS biogenesis affects bacterial viability. We developed a cell-based screen that identifies inhibitors of LPS biosynthesis and transport by exploiting the nonessentiality of this pathway in Acinetobacter. We used this screen to find an inhibitor of MsbA, an ATP-dependent flippase that translocates LPS across the inner membrane. Treatment with the inhibitor caused mislocalization of LPS to the cell interior. The discovery of an MsbA inhibitor, which is universally conserved in all gram-negative bacteria, validates MsbA as an antibacterial target. Because our cell-based screen reports on the function of the entire LPS biogenesis pathway, it could be used to identify compounds that inhibit other targets in the pathway, which can provide insights into vulnerabilities of the gram-negative cell envelope.
Cost-effectiveness of mechanical thrombectomy for acute ischemic stroke: an Australian payer perspective

Abstract Aims: The goal of this study was to assess the cost-effectiveness of mechanical thrombectomy (MT) for acute ischemic stroke (AIS) from an Australian payer perspective. Methods: This study used a Markov model that employed a life-time time horizon, modeling patients from symptom onset of stroke until end of life. Clinical efficacy and safety data were taken from an individual patient level data (IPD) meta-analysis of clinical studies. The treatment effect of MT compared to usual care was measured by changes in modified Rankin Score (mRS). Post-treatment mRS scores were used to determine short- and long-term stroke care costs. Treatment costs were modeled, with health state utility values determined by literature review. All analyses were conducted using Microsoft Excel. Results: In comparison to usual care, MT is associated with higher costs ($10,666 per patient) and additional quality-adjusted life years (QALYs) (0.8281 per patient), resulting in an incremental cost per QALY of $12,880. Sensitivity analyses demonstrated the reliability of the base case results across a range of assumptions. The higher cost associated with MT is, to an extent, offset by the cost savings resulting from lower stroke care costs due to improved patient outcomes. The life-time cost savings in terms of stroke care costs are estimated to be more than $8,000 per patient for patients who had received MT in combination with usual care. Limitations: Stroke care costs based on patient disability/functional level were not available and were derived. As a consequence, long-term care costs for patients with poorer outcomes may be under-estimated. Patient outcomes at 90 days were extrapolated to a lifetime horizon, but this approach was supported by long-term evidence on stroke survival. Conclusions: Mechanical thrombectomy is a cost-effective treatment option for AIS, with clinical benefits translating to short- and long-term cost benefits. This analysis supports rapid update of stroke care pathways to incorporate this therapy as a treatment option.
Use of Attack Graphs in Security Systems

Attack graphs have been used to model the vulnerabilities of the systems and their potential exploits. The successful exploits leading to the partial/total failure of the systems are subject of keen security interest. Considerable effort has been expended in exhaustive modeling, analyses, detection, and mitigation of attacks. One prominent methodology involves constructing attack graphs of the pertinent system for analysis and response strategies. This not only gives the simplified representation of the system, but also allows prioritizing the security properties whose violations are of greater concern, for both detection and repair. We present a survey and critical study of state-of-the-art technologies in attack graph generation and use in security system. Based on our research, we identify the potential, challenges, and direction of the current research in using attack graphs.
Social interactions among Asian backpackers: scale development and validation

Social interactions are a key aspect of the travel experience for Asian backpackers. Underpinned by the paradigm of symbolic interactionism and drawing on the theories of liminality and social identity, this study investigates the social interactions of Asian backpackers and provides a validated measurement scale. The interactions of travel companions comprise six dimensions including motivation, similarity, connection, similarity avoidance, distinction and recommendation along the travel timeline from pre-travel to on-road and post-travel period. The findings also identify the change, from learner to mentor, in the traveller’s role as the trip progresses.
Bayesian propagation of record linkage uncertainty into population size estimation of human rights violations

Multiple-systems or capture-recapture estimation are common techniques for population size estimation, particularly in the quantitative study of human rights violations. These methods rely on multiple samples from the population, along with the information of which individuals appear in which samples. The goal of record linkage techniques is to identify unique individuals across samples based on the information collected on them. Linkage decisions are subject to uncertainty when such information contains errors and missingness, and when different individuals have very similar characteristics. Uncertainty in the linkage should be propagated into the stage of population size estimation. We propose an approach called linkage-averaging to propagate linkage uncertainty, as quantified by some Bayesian record linkage methodologies, into a subsequent stage of population size estimation. Linkage-averaging is a two-stage approach in which the results from the record linkage stage are fed into the population size estimation stage. We show that under some conditions the results of this approach correspond to those of a proper Bayesian joint model for both record linkage and population size estimation. The two-stage nature of linkage-averaging allows us to combine different record linkage models with different capture-recapture models, which facilitates model exploration. We present a case study from the Salvadoran civil war, where we are interested in estimating the total number of civilian killings using lists of witnesses' reports collected by different organizations. These lists contain duplicates, typographical and spelling errors, missingness, and other inaccuracies that lead to uncertainty in the linkage. We show how linkage-averaging can be used for transferring the uncertainty in the linkage of these lists into different models for population size estimation.