Miracle-dz/UniFAR-FTUs huggingface dataset:
QoS-aware joint mode selection and channel assignment for D2D communications

Underlaying device-to-device (D2D) communications to a cellular network is considered as a key technique to improve spectral efficiency in 5G networks. For such D2D systems, mode selection and resource allocation have been widely utilized for managing interference. However, previous works allowed at most one D2D link to access the same channel, while mode selection and resource allocation are typically separately designed. In this paper, we jointly optimize the mode selection and channel assignment in a cellular network with underlaying D2D communications, where multiple D2D links may share the same channel. Meanwhile, the QoS requirements for both cellular and D2D links are guaranteed, in terms of Signal-to-Interference-plus-Noise Ratio (SINR). We first propose an optimal dynamic programming (DP) algorithm, which provides a much lower computation complexity compared to exhaustive search and serves as the performance bench mark. A bipartite graph based greedy algorithm is then proposed to achieve a polynomial time complexity. Simulation results will demonstrate the advantage of allowing each channel to be accessed by multiple D2D links in dense D2D networks, as well as, the effectiveness of the proposed algorithms.
Coexpression of dynorphin and neurokinin B immunoreactivity in the rat hypothalamus: Morphologic evidence of interrelated function within the arcuate nucleus

Considerable evidence suggests that dynorphin and neurokinin B (NKB) neurons in the hypothalamic arcuate nucleus participate in the sex‐steroid regulation of reproduction. In the present study, we used dual‐label immunofluorescence to explore the distribution of prodynorphin and proNKB immunoreactivity in the rat hypothalamus. Additionally, we investigated whether arcuate prodynorphin‐ir (immunoreactive) neurons expressed the neurokinin 3 receptor (NK3R) or nuclear estrogen receptor‐α (ERα). We found that the majority of prodynorphin‐ir neurons in the rat arcuate nucleus expressed proNKB, whereas nearly all (99%) of the proNKB neurons were immunoreactive for prodynorphin. The arcuate nucleus was the only site in the hypothalamus where neuronal somata coexpressing prodynorphin and proNKB‐immunoreactivity were identified. A dense plexus of double‐labeled prodynorphin/proNKB‐ir fibers was found within the arcuate nucleus extending to the median eminence and throughout the periventricular zone of the hypothalamus. Prodynorphin/proNKB fibers were also identified in the paraventricular nucleus, anterior hypothalamic area, medial preoptic area, median preoptic nucleus, anteroventral periventricular nucleus, and bed nucleus of the stria terminalis in a distribution consistent with previously described arcuate nucleus projections. Interestingly, the majority of prodynorphin‐ir neurons in the arcuate nucleus expressed NK3R, and nearly 100% of the prodynorphin‐ir neurons contained nuclear ERα. Our results suggest that there is a close functional relationship between dynorphin and NKB peptides within the arcuate nucleus of the rat, which may include an autofeedback loop mediated through NK3R. The diverse hypothalamic projections of fibers expressing both prodynorphin and proNKB provide evidence that these neurons may participate in a variety of homeostatic and neuroendocrine processes. J. Comp. Neurol. 498:712–726, 2006. © 2006 Wiley‐Liss, Inc.
MiR-338-3p inhibits the proliferation and migration of gastric cancer cells by targeting ADAM17.

BACKGROUND MicroRNAs (miRNA) have been documented playing a critical role in cancer progression. Although miR-338-3p has been implicated in several cancers, its role in gastric cancer is still unknown. The aim of our study was to investigate the role of miR-338-3p in gastric cancer progression. METHODS Expression levels of miR-338-3p in gastric cancer cell lines and tissues were determined by quantitative real-time PCR (qRT-PCR). The effect of miR-338-3p on proliferation was evaluated by MTT assay, cell migration and invasion were evaluated by transwell migration and invasion assays. Furthermore, luciferase reporter assay was conducted to confirm the target gene of miR-338-3p, and the results were validated in gastric cancer cells. RESULTS In the present study, we found that miR-338-3p was down-regulated in both gastric cancer cell lines and tissues. Enforced expression of miR-338-3p inhibited proliferation, migration and invasion of gastric cancer cells in vitro. Moreover, we identified A disintegrin and metalloproteinase 17 (ADAM17) gene as potential target of miR-338-3p. Importantly, ADAM17 rescued the miR-338-3p mediated inhibition of cell proliferation, migration and invasion. CONCLUSIONS Our study suggested that miR-338-3p is significantly decreased in gastric cancer, and inhibits cell proliferation, migration and invasion partially via the downregulation of ADAM17. Thus, miR-338-3p may represent a potential therapeutic target for gastric cancer intervention.
Spatial and temporal genetic homogeneity of the Monterey Spanish mackerel, Scomberomorus concolor, in the Gulf of California

The genetic homogeneity of the Monterey Spanish mackerel Scomberomorus concolor population in the Gulf of California was confirmed using nine nuclear microsatellite loci in combination with mitochondrial cytochrome b gene sequences. Samples were collected from the upper and central Gulf areas, representing the two main biogeographical regions of the Gulf. The analyses support the existence of a single panmictic population of S. concolor inhabiting the Gulf of California which in terms of fishery management represents a single genetic stock. Additionally, the contemporary effective population size estimated for the S. concolor population (Ne = 3056.9) was high and similar to another pelagic species. The gene flow seems to be bidirectional between the upper and central Gulf, which coincides with the seasonal movements between both regions related to spawning and feeding activities. A population expansion event was detected, which agrees with a colonization-expansion hypothesis of the S. concolor population in the Gulf.
Designing a character avatar model for the Mermaids MMO

This paper describes the technique formed for the creation of an efficient, simply rigged, customizable mermaid avatar model for the 'Mermaids' massively multiplayer online game (MMOG). Our goal was to improve the in game customization of the player's 3D mermaid model, while maintaining rendering efficiency. We devised a procedure that utilizes the iterative nature of design without sacrificing the scientific and technical aspects of the project. Our procedure begins by a method known as " Partitioning " where we break down the model's body into distinct sub-models. During development, this partitioning allowed us to focus on smaller concise areas of interest, whereas during game-play this change granted the player greater strands of customization freedom. Since the model relied on a skeleton for its animations, it's partitioning required " Skeletal Reformations " to reassess the control scheme of the rig over the sub-models. In this method, individual sub-skeletons were designed to provide increased local control over their respective sub-models in contrast to the global control that the previous rig allowed. The sub-skeletons were then joined together forming a combined and complete skeletal rig for the mermaid model. We iterated through the previous methods refining their procedures in efforts of " Balancing Customizability with Efficiency " , which in turn provided us with the results of our novel technique. Our technique utilizes innovative methods that localize skeletal control over respective sub-models in a novel way, which allows increased customizability with limited costs to efficiency.
Comparative Analysis of MSER and DTW for Offline Signature Recognition

This paper describes the signature as a one of the most robust and widely used trait in biometric verification. The signature is also known as behavioral biometric property. We present comparative analysis of offline signature recognition based on Dynamic Time Warping (DTW) and Maximally Stable Extremely Regions (MSER). The MSER system reported accuracy of 95.371% where FAR is 5.25% and FRR is 4% whereas DTW system reported accuracy of 70.5% and average horizontal projection WER 70% and average vertical projection WER of 71%.
Intraperitoneal chemotherapy in ovarian cancer: a review of tolerance and efficacy

Purpose To review the two main approaches of intraperitoneal (IP) chemotherapy delivery in ovarian cancer: postoperative adjuvant IP chemotherapy after cytoreductive surgery (CRS) and intraoperative hyperthermic intraperitoneal chemotherapy (HIPEC). Methods A literature search was conducted to identify studies that employed postoperative adjuvant IP chemotherapy after CRS or combined CRS and intraoperative HIPEC in patients with ovarian cancer. Data of interest included chemotherapy protocol, morbidity and mortality, and survival data. Results Three large randomized controlled trials comprising 707 patients with advanced ovarian cancer who received postoperative adjuvant IP chemotherapy were reviewed. Morbidity rate ranged from 56% to 94% in IP chemotherapy, and mortality rate ranged from 1% to 2%. Median disease-free survival ranged from 24 to 28 months, and overall survival ranged from 49 to 66 months. Planned chemotherapy completion rates ranged from 42% to 71%. Twenty-four nonrandomized studies that reported HIPEC comprised 1167 patients with both advanced and recurrent ovarian cancer. In patients with advanced ovarian cancer, mortality ranged from 0% to 5%, minor morbidity ranged from 16% to 90%, and major morbidity ranged from 0% to 40%. Median disease-free survival ranged from 13 to 56 months, and overall survival ranged from 14 to 64 months. Survival at 5 years ranged from 35% to 70%. In patients with recurrent ovarian cancer, the mortality rate ranged from 0% to 10%, minor morbidity ranged from 7% to 90%, and major morbidity ranged from 0% to 49%. Median disease-free survival ranged from 13 to 24 months and overall survival from 23 to 49 months. Survival at 5 years ranged from 12% to 54%. Conclusion There is level-one evidence suggesting the benefit of postoperative adjuvant intraperitoneal chemotherapy for patients with advanced ovarian cancer after cytoreductive surgery, albeit catheter-related complications resulted after treatment discontinuation. Studies report the use of HIPEC predominantly in the setting of recurrent disease and have demonstrated encouraging results, which merits further investigation in future clinical trials.
Ties of silence - Family lived experience of selective mutism in identical twins

This article is based on an in-depth interview with a pair of twins diagnosed with selective mutism and their parents 2 years after recovery. Selective mutism (SM) is a rare disorder, and identical twins sharing the condition are extremely rare. The twins developed SM simultaneously during their first year of school. The treatment and follow-up they received for several years are briefly described in this article. The interview explored the children’s and their parents’ narratives about the origin of the condition, the challenges it entailed in their daily lives, and what they found helpful in the treatment they were offered. In the interview, the children conveyed experiences that even the parents were unaware of and revealed examples of daily life-traumas for which they were unable to obtain support and help. The whole family was trapped in the silence. The twins and their parents emphasized different aspects in terms of what they believed were helpful. The implications of these findings for our understanding and treatment of children with SM are discussed, as well as the potential of service user involvement in child and adolescent mental health research.
Intervention Completion Rates among African Americans in a Randomized Effectiveness Trial for Diet and Physical Activity Changes

Background: The intervention completion rate is an important metric in behavioral and intervention research; trials with limited intervention completion rates may have reduced internal validity. We examined intervention completion rates among 530 African Americans who had been randomized to an integrated (INT) or disease-specific (DSE) risk education protocol as part of a comparative effectiveness trial from September 2009 to August 2012. Methods: The interventions were developed by an academic-community partnership using community-based participatory research. Intervention completion rates were determined based on attendance at all four intervention sessions. Intervention completers were participants who completed all four sessions and noncompleters were those who did not complete any session or only completed one to three sessions following randomization. Results: Seventy-three percent of participants were intervention completers and 27% were noncompleters. There were no differences in intervention completion based on randomization to INT (72%) or DSE (75%), sociodemographic factors, or body mass index (BMI) in the total sample. Different factors were associated significantly with intervention completion within study groups. Among participants randomized to INT, the odds of intervention completion were greater with higher levels of intrinsic motivation, less exposure to information about diet and cardiovascular disease, and greater BMI. Among participants randomized to DSE, the odds of completing the intervention were associated significantly with older age and greater dietary self-efficacy. Conclusions: Many African Americans are likely to complete risk education interventions. Impact: Psychologic characteristics should be considered when determining intervention completion rates following randomization in behavioral and intervention trials. Cancer Epidemiol Biomarkers Prev; 23(7); 1306–13. ©2014 AACR.
Partial information classes

In this survey we present partial information classes, which have been studied under different names and in different contexts in the literature. They are defined in terms of partial information algorithms. Such algorithms take a word tuple as input and yield a small set of possibilities for its characteristic string as output. We define a unified framework for the study of partial information classes and show how previous notions fit into the framework. The framework allows us to study the relationship of a large variety of partial information classes in a uniform way. We survey how partial information classes are related to other complexity theoretic notions like advice classes, lowness, bi-immunity, NP-completeness, and decidability.
Use of powdered coconut charcoal as a toxicity identification and evaluation manipulation for organic toxicants in marine sediments

We report on a procedure using powdered coconut charcoal to sequester organic contaminants and reduce toxicity in sediments as part of a series of toxicity identification and evaluation (TIE) methods. Powdered coconut charcoal (PCC) was effective in reducing the toxicity of endosulfan‐spiked sediments by 100%. Powdered coconut charcoal also was effective in removing almost 100% of the toxicity from two field sediments contaminated with polychlorinated biphenyls (PCBs) and polycyclic aromatic hydrocarbons (PAHs). Powdered coconut charcoal did not change the toxicity of ammonia or metal‐spiked sediments; however, there was some quantitative reduction in the concentrations of free metals (element specific) in metal‐spiked sediments. Powdered coconut charcoal is an effective, relatively specific method to sequester and remove toxicity from sediments contaminated with organic contaminants.
Application of Artificial Neural Network in Jitter Analysis of Dispersion-Managed Communication System

Artificial Neural Network (ANN) is used as numerical methode in solving modified Nonlinear Schroedinger (NLS) equation with Dispersion Managed System (DMS) for jitter analysis. We take the optical axis z and the time t as input, and then some relevant values such as the change of position and the center frequency of the pulse, and further the mean square time of incoming pulse which are needed for jitter analysis. It shows that ANN yields numerical solutions which are adaptive with respect to the numerical errors and also verifies the previous numerical results using conventional numerical method. Our result indicates that DMS can minimize the timing jitter induced by some amplifiers.
Adaptive Scheduling with Parallelism Feedback

Multiprocessor scheduling in a shared multiprogramming environment can be structured as two-level scheduling, where a kernel-level job scheduler allots processors to jobs and a user-level thread scheduler schedules the work of a job on the allotted processors. In this context, the number of processors allotted to a particular job may vary during the job's execution, and the thread scheduler must adapt to these changes in processor resources. For overall system efficiency, the thread scheduler should also provide parallelism feedback to the job scheduler to avoid allotting a job more processors than it can use productively. This paper provides an overview of several adaptive thread schedulers we have developed that provide provably good history-based feedback about the job's parallelism without knowing the future of the job. These thread schedulers complete the job in near-optimal time while guaranteeing low waste. We have analyzed these thread schedulers under stringent adversarial conditions, showing that the thread schedulers are robust to various system environments and allocation policies. To analyze the thread schedulers under this adversarial model, we have developed a new technique, called trim analysis, which can be used to show that the thread scheduler provides good behavior on the vast majority of time steps, and performs poorly on only a few. When our thread schedulers are used with dynamic equipartitioning and other related job scheduling algorithms, they are O(1)-competitive against an optimal offline scheduling algorithm with respect to both mean response time and makespan for batched jobs and nonbatched jobs, respectively. Our algorithms are the first nonclairvoy-ant scheduling algorithms to offer such guarantees.
Perspectives in musculoskeletal injury management by traditional bone setters in Ashanti, Ghana

Background The popularity of the services of traditional bone setters (TBS) in Ghana as an alternative health care requires exploration and documentation of the perspectives of providers and users. Objective To explore and document the perspectives of providers and users of the services of TBS in the management of musculoskeletal injuries in the Ashanti region, Ghana. Methods From the social constructivist and qualitative approach, in-depth interviews were used to explore the perspectives of eight TBS and 16 users of their services, selected purposively through snowballing. Thematic content analysis (TCA) was employed. Results High recovery rate, warm reception, prompt attention, and the relatively lower charges, are reported to motivate the patronage of the services of TBS for the management of fractures in the legs, arms, ribs, joint bones dislocations, waist and spinal cord problems. The TBS combined traditional and orthodox procedures, using plant and animal-based materials, beliefs, spirituality (God-given) and physical therapy in the management of musculoskeletal injuries. No adverse experience was reported by either the providers or users of the traditional management methods. Conclusion With plant and animal-based materials, TBS are observed to combine traditional and orthodox procedures to confidently manage musculoskeletal injuries to the satisfaction of their highly motivated patrons. Although over 60% of the TBS attribute the healing power behind their practice to God, the rest do not discount the role of spiritual therapy. Further studies expanded to include the perspectives of non-users of the services of the TBS will authenticate the findings of this study.
To Carry or To Forward? A Traffic-Aware Data Collection Protocol in VANETs

Vehicles can provide useful data to many urban computing applications. This paper addresses the issue of collecting data from multiple vehicles to a roadside base station using VANET. The impacts of real-time traffic condition have not been widely discussed in literature. In this paper, we study the data collection problem under different traffic conditions. The objective is to minimize the network communication overhead while satisfying the data collection time constraint. We formulate the problem as an scheduling optimization problem. A dynamic programming based solution and a genetic algorithm based solution are developed to solve the problem for different application scenarios. The solution can adaptively choose to carry or forward data based on current traffic information. Evaluation shows that the proposed solution outperforms some existing ones in terms of effectiveness and efficiency.
The competition model: the input, the context, and the brain

Introduction Language learning is a three-way interaction between the input, the learner, and the interactional context (Bloom, 1974). This three-way interaction provides a general framework for understanding first and second language acquisition (SLA), in both naturalistic and formal contexts. In order to elaborate this general framework, we need to model its three components: The input. We need to know how the linguistic input can be structured to maximize effective learning. What aspects of the phonology, syntax, semantics, and morphology of the input does the learner use to ‘crack the code’ of the new language? The learner. We need to understand exactly how the cognitive abilities of the learner shape the process and outcome of L2 instruction. The context. Traditionally, the classroom environment maintains a rather uniform structure in which interaction is controlled by the instructor. How does this framework affect learning and how can it be varied to improve the learning process? This paper will examine these three components within the framework of the Competition Model (MacWhinney, 1987; MacWhinney & Bates, 1989). To quantify the role of the input in L2 learning, the model relies on the concepts of cue reliability and availability. To characterize the cognitive abilities of the learner, the model relies on findings from cognitive neuroscience. To understand the role of the context, the model elaborates the concepts of environmental and social support. The Competition Model views both L1 and L2 learning as constructive, data-driven processes that rely not on universals of linguistic structure, but on universals of cognitive structure.