Miracle-dz/UniFAR-FTUs huggingface dataset:
Validation of Krathom (Mitragyna speciosa Korth.) Dependence Scale (KDS): A Dependence Screen for Internationally Emerging Psychoactive Substance

Background Krathom (Mitragyna speciosa Korth.) is the most commonly used illicit substance in Thailand, and its use has become widespread internationally. Studies on krathom dependence and its health impact are scarce, as there has been no instrument to measure its dependence syndrome and classify krathom users. This study aimed to develop and explore the factor structure, reliability, and validity of a Krathom Dependence Scale (KDS). Methods This study comprised 2 phases. First, cross-sectional surveys were conducted with 523 (Phase I) and 595 (Phase II) male villagers aged >25 years who were regular, occasional, ex-, or nonusers of krathom. Scale construction was based on the qualitative results from users and previous literature. Exploratory factor analysis (EFA) using maximum likelihood extraction with oblimin rotation was conducted in Phase I and confirmatory factor analysis (CFA) in Phase II to confirm the construct of the scale. Internal consistency of the KDS was assessed using Cronbach's alpha coefficient. Discriminative validity was examined by checking its ability to differentiate between regular and occasional users and patterns of krathom use and its concurrent validity by comparing its levels of score with the Fagerstrom Test for Nicotine Dependence (FTND). The KDS contains 16 items on a 0–3 (never–always) rating scale, making a total score of 0–48. Results Phase I EFA revealed a single-factor solution for the scale, which was confirmed by the CFA in Phase II, with an alpha coefficient of . 98. The KDS discriminates regular from occasional users reasonably well and is highly correlated with the FTND score. Two cutoffs were suggested: 34/35 for distinguishing moderate from high dependence and 13/14 for low from moderate. Conclusions The KDS appears to capture key theoretical constructs and correlates with indices of drug dependence by standard criteria. It should be useful in early intervention for those with krathom use disorders in community and primary care settings.
Interactive Temporal Recurrent Convolution Network for Traffic Prediction in Data Centers

Accurately predicting future service traffic would be of great help for load balancing and resource allocation, which plays a key role in guaranteeing the quality of service (QoS) in cloud computing. With the rapid development of data center, the large-scale network traffic prediction requires more suitable methods to deal with the complex properties (e.g., high-dimension, long-range dependence, non-linearity, and so on). However, due to the limitations of traditional methods (e.g., strong theoretical assumptions and simple implementation), few research works could predict the large-scale network traffic efficiently and accurately. More importantly, most of the studies took only the temporal features but without the services’ communications into consideration, which may weaken the QoS of applications in the data center. To this end, we applied the gated recurrent unit (GRU) model and the interactive temporal recurrent convolution network (ITRCN) to single-service traffic prediction and interactive network traffic prediction, respectively. Especially, ITRCN takes the communications between services as a whole and directly predicts the interactive traffic in large-scale network. Within the ITRCN model, the convolution neural network (CNN) part learns network traffic as images to capture the network-wide services’ correlations, and the GRU part learns the temporal features to help the interactive network traffic prediction. We conducted comprehensive experiments based on the Yahoo! data sets, and the results show that the proposed novel method outperforms the conventional GRU and CNN method by an improvement of 14.3% and 13.0% in root mean square error, respectively.
YWHAE silencing induces cell proliferation, invasion and migration through the up-regulation of CDC25B and MYC in gastric cancer cells: new insights about YWHAE role in the tumor development and metastasis process

We previously observed reduced YWHAE (14-3-3ε) protein expression in a small set of gastric cancer samples. YWHAE may act as a negative regulator of the cyclin CDC25B, which is a transcriptional target of MYC oncogene. The understanding of YWHAE role and its targets is important for the better knowledge of gastric carcinogenesis. Thus, we aimed to evaluate the relationship among YWHAE, CDC25B, and MYC in vitro and in vivo. For this, we analyzed the YWHAE, CDC25B, and MYC expression in YWHA-silenced, CDC25B-silenced, and MYC-silenced gastric cancer cell lines, as well as in gastric cancer and non-neoplastic gastric samples. In gastric cancer cell lines, YWHAE was able to inhibit the cell proliferation, invasion and migration through the reduction of MYC and CDC25B expression. Conversely, MYC induced the cell proliferation, invasion and migration through the induction of CDC25B and the reduction of YWHAE. Most of the tumors presented reduced YWHAE and increased CDC25B expression, which seems to be important for tumor development. Increased MYC expression was a common finding in gastric cancer and has a role in poor prognosis. In the tumor initiation, the opposite role of YWHAE and CDC25B in gastric carcinogenesis seems to be independent of MYC expression. However, the inversely correlation between YWHAE and MYC expression seems to be important for gastric cancer cells invasion and migration. The interaction between YWHAE and MYC and the activation of the pathways related to this interaction play a role in the metastasis process.
Engineered human angiogenin mutations in the placental ribonuclease inhibitor complex for anticancer therapy: Insights from enhanced sampling simulations

Targeted human cytolytic fusion proteins (hCFPs) represent a new generation of immunotoxins (ITs) for the specific targeting and elimination of malignant cell populations. Unlike conventional ITs, hCFPs comprise a human/humanized target cell‐specific binding moiety (e.g., an antibody or a fragment thereof) fused to a human proapoptotic protein as the cytotoxic domain (effector domain). Therefore, hCFPs are humanized ITs expected to have low immunogenicity. This reduces side effects and allows long‐term application. The human ribonuclease angiogenin (Ang) has been shown to be a promising effector domain candidate. However, the application of Ang‐based hCFPs is largely hampered by the intracellular placental ribonuclease inhibitor (RNH1). It rapidly binds and inactivates Ang. Mutations altering Ang's affinity for RNH1 modulate the cytotoxicity of Ang‐based hCFPs. Here we perform in total 2.7 µs replica‐exchange molecular dynamics simulations to investigate some of these mutations—G85R/G86R (GGRRmut), Q117G (QGmut), and G85R/G86R/Q117G (GGRR/QGmut). GGRRmut turns out to perturb greatly the overall Ang‐RNH1 interactions, whereas QGmut optimizes them. Combining QGmut with GGRRmut compensates the effects of the latter. Our results explain the in vitro finding that, while Ang GGRRmut‐based hCFPs resist RNH1 inhibition remarkably, Ang WT‐ and Ang QGmut‐based ones are similarly sensitive to RNH1 inhibition, whereas Ang GGRR/QGmut‐based ones are only slightly resistant. This work may help design novel Ang mutants with reduced affinity for RNH1 and improved cytotoxicity.
Lifestyle Behaviors in Elderly Cancer Survivors: A Comparison With Middle-Age Cancer Survivors.

PURPOSE Improved cancer screening and treatment have led to a greater focus on cancer survivorship care. Older cancer survivors may be a unique population. We evaluated whether older cancer survivors (age ≥ 65 years) had lifestyle behaviors, attitudes, and knowledge distinct from younger survivors. PATIENTS AND METHODS Adult cancer survivors with diverse cancer subtypes were recruited from Princess Margaret Cancer Centre (Toronto, Ontario, Canada). Multivariable models evaluated the effect of age on smoking, alcohol, and physical activity habits, attitudes toward and knowledge of these habits on cancer outcomes, and lifestyle information and recommendations received from health care providers, adjusted for sociodemographic and clinicopathologic covariates. RESULTS Among the 616 survivors recruited, 23% (n = 139) were older. Median follow-up since diagnosis was 24 months. Older survivors were more likely ex-smokers and less likely current smokers than younger survivors, but they were less likely to know that smoking could affect cancer treatment (adjusted odds ratio [OR], 0.53; P = .007) or prognosis (adjusted OR, 0.53; P = .008). Older survivors were more likely to perceive alcohol as improving overall survival (adjusted OR, 2.39; P = .02). Rates of meeting moderate-to-vigorous physical activity guidelines 1 year before diagnosis (adjusted OR, 0.55; P = .02) and maintaining and improving their exercise levels to meet these guidelines after diagnosis (adjusted OR, 0.48; P = .02) were lower in older survivors. Older and younger cancer survivors reported similar rates of receiving lifestyle behavior information from health care providers (P = .36 to .98). CONCLUSION Older cancer survivors reported being less aware of the impact of smoking on their overall health, more likely perceived alcohol as beneficial to survival, and were less likely to meet exercise goals compared with younger survivors. Survivorship programs need to consider age when counseling on lifestyle behaviors.
Controllable Fabrication of Nanogap Structure Based on Nanosphere Lithography

One method was developed for fabricating nanogap structures, which combined the nanosphere lithography, reaction ion etching and glancing deposition technologies. The results show that 10 nm-200 nm nanogaps structure could be prepared by changing the deposition angle, and nanogap structure patterns could be changed with different incident orientation.
The capacity of hybrid wireless mesh network

Wireless mesh network (WMN) consists of mesh gateways, mesh routers and mesh clients. In hybrid WMN, both backbone mesh network and client mesh network are mesh connected. Capacity analysis of multi-hop wireless networks has proven to be an interesting and challenging research topic. The capacity of hybrid WMN depends on several factors such as traffic model, topology, scheduling strategy and bandwidth allocation strategy, etc. In this paper, the capacity of hybrid WMN is studied according to the traffic model and bandwidth allocation. The traffic of hybrid WMN is categorized into internal and external traffic. Then the capacity of each mesh client is deduced according to appropriate bandwidth allocation. The analytical results show that hybrid WMN achieves lower capacity than infrastructure WMN. The results and conclusions can guide for the construction of hybrid WMN.
Performance of collaborative GPS localization in pedestrian ad hoc networks

In ad hoc networks without static nodes that could be used as reference points, mobile handhelds must rely on their GPS receivers to enable location-aware services. By sharing their position estimates using short range radios, neighboring devices may suppress unnecessary GPS activations in order to reduce energy consumption. We describe and evaluate two collaborative GPS localization protocols based on substitution and averaging of position estimates. The evaluation focuses on entertainment park scenarios and relies on realistic simulations to capture the mobility of park visitors. We demonstrate that the simple collaboration protocols, which do not require distance estimation between the neighbors, may provide significant energy savings. We discuss the impact of device density and provide guidelines for choosing the transmission range of their radio interfaces.
Poster: An In-Vehicle Software Defined Network Architecture for Connected and Automated Vehicles

Vehicular network architectures are being reviewed and re-designed to meet requirements for increasing data rates and flexibility driven in part by the adoption of Connected and Automated Vehicles (CAV) strategies. A progressive move from traditional bus based networks, such as CAN, to Ethernet-based network architectures is being considered across the automotive industry. In this paper we advocate for an in-vehicle Software-Defined Network architecture and discuss benefits that such a shift in the architectural paradigm will bring by strengthening cyber-security defences and enabling a fail-operational capability through network programmability and provably correct networks.
Body Shape and Weight Loss as Motivators for Breastfeeding Initiation and Continuation

Breastfeeding rates in the UK are low. Efforts to promote breastfeeding typically include the known health benefits for mother and child, many of which are not immediate. Gaining immediate benefits can be effective motivators of behaviour. Body-related changes resulting from breastfeeding could be an immediate benefit. This study explored breastfeeding mothers’ reports of body-related changes as benefits of breastfeeding. Mothers (N = 182) who currently, or had recently, breastfed an infant completed a survey detailing their infant feeding choices and the perceived benefits of breastfeeding on their bodies. Half of the mothers felt that breastfeeding had a positive effect on their body. Benefits were grouped into five themes: (1) Returning to pre-pregnancy body shape; (2) Health benefits; (3) Physical benefits; (4) Eating benefits; (5) Psychological benefits. These themes highlight the numerous body-related benefits that mothers identified as resulting from breastfeeding and suggest that immediate, personal, and appearance-related gains of breastfeeding are highly valued. These findings indicate that interventions would likely benefit from emphasising the more immediate physical and psychological benefits of breastfeeding, alongside the health and bonding benefits, as a way to promote breastfeeding initiation and continuation in more women. This may be particularly effective for groups such as young mothers, where breastfeeding rates are low and whose emphasis on body image may be greater.
Periodic Oscillation of Gene Networks with Forcing and Delay

In this paper, we derive new criteria for evaluating the global stability of periodic oscillation for gene networks with small forcing and delay. Our results rely on the Lipschtiz conditions of Hill function, topology of gene networks. In particular, Our method based on the proposed model transforms the original network into matrix analysis problem, thereby not only significantly reducing the computational complexity but also making analysis of periodic oscillation tractable for even large-scale nonlinear networks.
A Sparse Representation Method for a Priori Target Signature Optimization in Hyperspectral Target Detection

Many target detectors commonly utilize a single a priori target spectral signature as an input. However, the detection results are greatly affected by the quality of the a priori target spectral signature because the spectral variability phenomenon is universal and anisotropic in hyperspectral image data. This paper proposes a sparse representation-based method to generate an optimized target spectrum from limited target training samples, which is able to alleviate the impact of spectral variability on hyperspectral target detection. When lacking comprehensive knowledge about the target object of interest, an optimized representative target spectrum should be expected to be reconstructed by the hyperspectral data themselves in a sparse representation manner following the characteristics of the data structure and then be generated by a set of selected candidate pixels that contain the target signal with a varying status. With the optimized a priori target signature, the experimental results of the detection of different characteristics of objects with three different types of hyperspectral images confirm the effectiveness, robustness, and generality performance of the proposed method.
Policy Optimization by Genetic Distillation

Genetic algorithms have been widely used in many practical optimization problems. Inspired by natural selection, operators, including mutation, crossover and selection, provide effective heuristics for search and black-box optimization. However, they have not been shown useful for deep reinforcement learning, possibly due to the catastrophic consequence of parameter crossovers of neural networks. Here, we present Genetic Policy Optimization (GPO), a new genetic algorithm for sample-efficient deep policy optimization. GPO uses imitation learning for policy crossover in the state space and applies policy gradient methods for mutation. Our experiments on MuJoCo tasks show that GPO as a genetic algorithm is able to provide superior performance over the state-of-the-art policy gradient methods and achieves comparable or higher sample efficiency.
The role of quantum information in thermodynamics—a topical review

This topical review article gives an overview of the interplay between quantum information theory and thermodynamics of quantum systems. We focus on several trending topics including the foundations of statistical mechanics, resource theories, entanglement in thermodynamic settings, fluctuation theorems and thermal machines. This is not a comprehensive review of the diverse field of quantum thermodynamics; rather, it is a convenient entry point for the thermo-curious information theorist. Furthermore this review should facilitate the unification and understanding of different interdisciplinary approaches emerging in research groups around the world.
Research on Tests of Magnetic Abrasive Finishing by Sintering Method

This paper mainly illustrates the magnetic abrasive finishing by sintering method and research on tests of magnetic abrasive finishing, analyses the effect of the sintering temperature, ratio of magnetic and abrasive particle size, sintering time and sintering characteristics of magnetic particles on magnetic abrasive during the finishing process, so as to achieve a better process and principle for magnetic abrasive finishing.
Optimisation and prediction model of hot metal desulphurisation reagent consumption

Sulphur in steel, which is deleterious to its mechanical properties, is reduced in hot metal by external desulphurisation using calcium carbide (CaC2) based reagent at JSW Steel. With an aim of optimising the consumption of this reagent for desulphurisation, sulphur mapping was carried out at different locations, from hot metal production to steel casting, to establish optimum S levels at different stages of hot metal and steel treatment. The performance analysis of plant data for desulphurisation of hot metal shows that the degree of desulphurisation (DS) and hot metal temperature had significant impact on the consumption of reagent. Optimum consumption of desulphurisation reagent is achieved by maintaining hot metal temperature above 1350°C and the DS less than 80%. A computer based model using multiple linear regression techniques has been developed to guide the operator to ensure optimum consumption of desulphurisation reagent.
UCP2 is highly expressed in pancreatic α-cells and influences secretion and survival

In pancreatic β-cells, uncoupling protein 2 (UCP2) influences mitochondrial oxidative phosphorylation and insulin secretion. Here, we show that α-cells express significantly higher levels of UCP2 than do β-cells. Greater mitochondrial UCP2-related uncoupling was observed in α-cells compared with β-cells and was accompanied by a lower oxidative phosphorylation efficiency (ATP/O). Conversely, reducing UCP2 activity in α-cells was associated with higher mitochondrial membrane potential generated by glucose oxidation and with increased ATP synthesis, indicating more efficient metabolic coupling. In vitro, the suppression of UCP2 activity led to reduced glucagon secretion in response to low glucose; however, in vivo, fasting glucagon levels were normal in UCP2−/− mice. In addition to its effects on secretion, UCP2 played a cytoprotective role in islets, with UCP2−/− α-cells being more sensitive to specific death stimuli. In summary, we demonstrate a direct role for UCP2 in maintaining α-cell function at the level of glucose metabolism, glucagon secretion, and cytoprotection.
Tau Reduction Does Not Prevent Motor Deficits in Two Mouse Models of Parkinson's Disease

Many neurodegenerative diseases are increasing in prevalence and cannot be prevented or cured. If they shared common pathogenic mechanisms, treatments targeting such mechanisms might be of benefit in multiple conditions. The tau protein has been implicated in the pathogenesis of diverse neurodegenerative disorders, including Alzheimer's disease (AD) and Parkinson's disease (PD). Tau reduction prevents cognitive deficits, behavioral abnormalities and other pathological changes in multiple AD mouse models. Here we examined whether tau reduction also prevents motor deficits and pathological alterations in two mouse models of PD, generated by unilateral striatal injection of 6-hydroxydopamine (6-OHDA) or transgene-mediated neuronal expression of human wildtype α-synuclein. Both models were evaluated on Tau +/+, Tau +/– and Tau –/– backgrounds in a variety of motor tests. Tau reduction did not prevent motor deficits caused by 6-OHDA and slightly worsened one of them. Tau reduction also did not prevent 6-OHDA-induced loss of dopaminergic terminals in the striatum. Similarly, tau reduction did not prevent motor deficits in α-synuclein transgenic mice. Our results suggest that tau has distinct roles in the pathogeneses of AD and PD and that tau reduction may not be of benefit in the latter condition.
Predicting Sexual Assault Revictimization in a Longitudinal Sample of Women Survivors: Variation by Type of Assault

This study used a large community sample of women sexual assault survivors to prospectively assess 17 theorized predictors across four types of sexual assault revictimization: unwanted contact, coercion, substance-involved assault (SIA), and force. Results indicated that predictors varied across types of revictimization: Unwanted contact and coercion appeared more common in social contexts more hostile toward survivors, whereas forcible assaults and SIAs occurred in circumstances where survivors were vulnerable to being targeted by perpetrators. Overall, the strongest predictors were social environments hostile to survivors, race, childhood sexual abuse, decreased refusal assertiveness, and having more sexual partners. We discuss implications for intervention and research.
Multi-Target Tracking Based on Regional Correlation and Color Histogram Match

A method based on regional correlation and color histogram match was proposed for multi-target adaptive tracking. Firstly, target detection method was used to get the difference images. Then, the same target could be recognized according to the correlation of target regions of consecutive frames and the matching rate of color histogram. Finally, the active value, lifetime and dormancy value of targets were used to carry out long-time target tracking and deal with the problems of missing detection, false detection and target exit. The experiment shows that the method proposed in this paper has reached to a high accuracy rate of 95%, which has good robustness against the processing of missing detection, false detection and target exit.