Miracle-dz/UniFAR-FTUs huggingface dataset:
A Study of STTRAM-based Page Walker Caches for Energy-Efficient Address Translation

This paper studies spin-transfer torque RAM (STTRAM) as an energy-efficient alternative to SRAM for implementing page walker caches (PWCs) in resource-constrained systems' memory management units. We analyze the access characteristics and persistence of PWC blocks in a set of multithreaded workloads, revealing that individual threads might have different runtime behaviors. Given this observation, we explore and analyze the benefits of heterogeneous retention time STTRAM-wherein STTRAM's data retention time is specialized to cache blocks' persistence needs-for implementing the PWC in multicore systems. Based on our analysis, we propose NECTAR, an energy-efficient heterogeneous STTRAM-based page walker cache architecture. Experimental results using multithreaded PARSEC benchmarks show that NECTAR enables runtime adaptability and offers substantial energy benefits for implementing the PWC, reducing the average energy by 81.36% compared to SRAM, without introducing significant overheads.
Knowledge-Based Environment Dependency Inference for Python Programs

Besides third-party packages, the Python interpreter and system libraries are also critical dependencies of a Python program. In our empirical study, 34% programs are only compatible with specific Python interpreter versions, and 24% programs require specific system libraries. However, existing techniques mainly focus on inferring third-party package dependencies. Therefore, they can lack other necessary dependencies and violate version constraints, thus resulting in program build failures and runtime errors. This paper proposes a knowledge-based technique named PyEGo, which can automatically infer dependencies of third-party packages, the Python interpreter, and system libraries at compatible versions for Python programs. We first construct the dependency knowl-edge graph PyKG, which can portray the relations and constraints among third-party packages, the Python interpreter, and system libraries. Then, by querying PyKG with extracted program features, PyEGo constructs a program-related sub-graph with dependency candidates of the three types. It finally outputs the latest compatible dependency versions by solving constraints in the sub-graph. We evaluate PyEGo on 2,891 single-file Python gists, 100 open-source Python projects and 4,836 jupyter notebooks. The experimental re-sults show that PyEGo achieves better accuracy, 0.2x to 3.5x higher than the state-of-the-art approaches.
CALL FOR PAPERS Mechanisms of Tissue Repair Macrophages and skeletal muscle regeneration: a clodronate-containing liposome depletion study

Macrophages and skeletal muscle regeneration: a clo-dronate-containing liposome depletion study. Am J Physiol Regul Integr Physiol 2006. study evaluates the inﬂu-ence of monocytes/macrophages in the mechanisms of skeletal muscle injury using a mouse model and selective depletion of peripheral monocyte with systemic injections of liposomal clodronate (dichloromethylene bisphosphonate). This pharmacological treatment has been demonstrated to induce speciﬁc apoptotic death in monocytes and phagocytic macrophages. In the current studies, the liposomal clodronate injections resulted in a marked attenuation of the peak inﬂammatory response in the freeze-injured muscle in the ﬁrst three days after injury. The effect was accompanied by a transient reduction (at day 1 or 3 postinjury) of the expression of several genes coding for inﬂammatory, as well as growth-related mediators, including TNF, monocyte chemoattractant protein (MCP)-1, thioredoxin, high-mobility group AT-hook 1, insulin-like growth factor-binding protein (IGFBP), and IGF-1. In contrast, the expression of major myogenic factors (i.e., MyoD and myogenin) directly involved in the activation/proliferation and differentiation of muscle precursor cells was not altered by the clodronate liposome treatment. The repair process in the injured muscle of clodronate liposome-treated mice was characterized by prolonged clearance of necrotic myoﬁbers and a tendency for increased muscle fat accumulation at day 9 and 14 postinjury, respectively. In conclusion, a signiﬁcant reduction of the initial monocyte/macrophage inﬂux into the injured muscle is associated with not improved, but moderately impaired, repair processes after skeletal muscle injury. and transforming growth factor beta 1 (TGF- (cid:10) 1) was performed with predeveloped primers and probes (Assays-On-Demand Gene Expression Products, PE Applied Biosys- tems). PCR products were ampliﬁed on the ABI Prism 7700 spectroﬂuorometric thermal cycler. The differences in mRNA expression between control and treatment groups were determined by the relative quantiﬁcation method (18), using the threshold cycle (C T ) method and real-time PCR efﬁciencies of the target gene normalized to the housekeeping gene 18S/rRNA. The housekeeping gene expression was not inﬂuenced by the injury or by the pharmacological treatment.
Free2CAD

CAD modeling, despite being the industry-standard, remains restricted to usage by skilled practitioners due to two key barriers. First, the user must be able to mentally parse a final shape into a valid sequence of supported CAD commands; and second, the user must be sufficiently conversant with CAD software packages to be able to execute the corresponding CAD commands. As a step towards addressing both these challenges, we present Free2CAD wherein the user can simply sketch the final shape and our system parses the input strokes into a sequence of commands expressed in a simplified CAD language. When executed, these commands reproduce the sketched object. Technically, we cast sketch-based CAD modeling as a sequence-to-sequence translation problem, for which we leverage the powerful Transformers neural network architecture. Given the sequence of pen strokes as input, we introduce the new task of grouping strokes that correspond to individual CAD operations. We combine stroke grouping with geometric fitting of the operation parameters, such that intermediate groups are geometrically corrected before being reused, as context, for subsequent steps in the sequence inference. Although trained on synthetically-generated data, we demonstrate that Free2CAD generalizes to sketches created from real-world CAD models as well as to sketches drawn by novice users. Code and data are at https://github.com/Enigma-li/Free2CAD.
SPILLOVERS FROM US MONETARY SHOCKS: ROLE OF POLICY DRIVERS AND CYCLICAL CONDITIONS

We provide new evidence on the spillover effects from US interest rate changes, focusing on factors that are pertinent to the current conjuncture: weak recovery prospects in emerging market and developing economies (EMDEs), and the confluence of macroeconomic shocks shaping the path of interest rates in the US. The drivers of US monetary policy matter for the nature of spillovers. With an SVAR-IV model used to identify structural monetary policy, demand, and supply shocks, we find that an increase in US interest rates driven by demand shocks engenders a positive spillover to economic activity in the near term, while an exogenous tightening of monetary policy would have a large negative spillover effect. Spillovers from US monetary policy shocks also depend on the state of the business cycle, exerting larger effects when growth is weak outside the US. Finally, tighter US monetary policy affects the left tail of the growth distribution disproportionately: the fat left tail highlights the salience of growth at risk. and the 2-year US bond yield (basis points) to one standard deviation demand, supply and monetary policy shocks estimated using a SVAR model for the US.
Building Lightweight Ontologies for Faceted Search with Named Entity Recognition: Case WarMemoirSampo

This paper discusses building lightweight ontologies for faceted search user interfaces with Named Entity Recognition (NER) from textual data. This is studied in the context of building a Knowledge Graph for the textual indexing of interview videos in the in-use WarMemoirSampo system, consisting of a Linked Open Data service and an open semantic web portal for contextualized video viewing. It is shown that state-of-the-art NER tools are able to find entities from textual data and categorize them with high enough recall and precision to be useful for building facet ontologies, without involving considerable manual domain ontology engineering. To enable entity disambiguation and to be able to show relevant contextual information and useful links for the users of the portal, also Named Entity Linking techniques are employed.
CHANGES IN EXERCISES ARE MORE EFFECTIVE THAN

Fonseca, RM, Roschel, H, Tricoli, V, de Souza, EO, Wilson, JM, Laurentino, GC, Aihara, AY, de Souza Leão, AR, and Ugrinowitsch, C. Changes in exercises are more effective than in loading schemes to improve muscle strength. J Strength Cond Res 28(11): 3085–3092, 2014—This study investigated the effects of varying strength exercises and loading scheme on muscle cross-sectional area (CSA) and maximum strength after 4 strength training loading schemes: constant intensity and constant exercise (CICE), constant intensity and varied exercise (CIVE), varied intensity and constant exercise (VICE), varied intensity and varied exercise (VIVE). Forty-nine individuals were allocated into 5 groups: CICE, CIVE, VICE, VIVE, and control group (C). Experimental groups underwent twice a week training for 12 weeks. Squat 1 repetition maximum was assessed at baseline and after the training period. Whole quadriceps muscle and its heads CSA were also obtained pretraining and posttraining. The whole quadriceps CSA increased significantly (p # 0.05) in all of the experimental groups from pretest to posttest in both the right and left legs: CICE: 11.6 and 12.0%; CIVE: 11.6 and 12.2%; VICE: 9.5 e 9.3%; and VIVE: 9.9 and 11.6%, respectively. The CIVE and VIVE groups presented hypertrophy in all of the quadriceps muscle heads (p # 0.05), whereas the CICE and VICE groups did not present hypertrophy in the vastus medialis and rectus femoris (RF), and in the RF muscles, respectively (p. 0.05). The CIVE group had greater strength increments than the other training groups (effect size confidence limit of the difference [ESCLdiff] CICE: 1.4121.56; VICE: 2.13–2.28; VIVE: 0.59–0.75). Our findings suggest: (a) CIVE is more efficient to produce strength gains for physically active individuals; (b) as long as the training intensity reaches an alleged threshold, muscle hypertrophy is similar regardless of the training intensity and exercise variation.
Fitness and Training OF MODERATE AND HIGH INTENSITY AEROBIC SE ON THE BODY COMPOSITION OF EIGHT MEN

Bottaro M, Oliveira RJ, Novaes JS. Effect Of Moderate And sity Aerobic Exercise On The Body Composition Of Overweight online 2005;8(2):39-45. The optimal aerobic exercise training improve body composition in overweight men is unclear. The f this study was to determine the effect of 14 weeks of high ersus moderate intensity aerobic exercise of equal work output omposition in overweight men (BMI = 25-29.9 kg/m). Sixteen military men (18 33 yrs) were randomized in two equal groups oderate intensity exercise (MI; 60 70% of their maximum ; HRmax), and 2) high intensity exercise (HI; 75 90% HRmax). ic exercise (jogging/running) training program was performed /wk. Relative body fat (% BF) was assessed by dual energy xtiometry (DXA) (Lunar DPX IQ). Significant differences nd within the groups were analyzed using a two-way split-plot f variance (SPANOVA). Statistical significance was accepted at fter the 14 wks of the aerobic exercise program the mean %BF ignificantly (p<0.05) decreased to 22.49 % (∆=4.91%). The in mean %BF (∆=1.4 %) in the MI was not significant (p>0.05). It ed that 14 wks of HI aerobic exercise may be more effective in body composition than MI aerobic exercise in overweight young n with physical characteristics similar to the present study. s: Obesity, DXA, Fat mass, Aerobic training Intensity of Exercise Training and Body Composition 40
Resistance Training for Children and Adolescents: Are There Health Outcomes?

1 Abstract Although much of what we understand about the stimulus of resistance exercise has been gained by exploring the responses of adults to various training protocols, research into the effects of resistance exercise on children and adolescents has increased over the past decade. Despite outdated concerns that resistance training was ineffective or unsafe for youth, research increasingly suggests that resistance training can be a safe and effective method of exercise for children and adolescents provided that appropriate training guidelines are followed. In addition to enhancing motor skills and sports performance, regular participation in a youth resistance training program has the potential to positively infl uence several measurable indices of health. It helps strengthen bone, facilitate weight control, enhance psychosocial well-being, and improve one’s cardiovascular risk profi le. Furthermore, a stronger musculoskeletal system will enable boys and girls to perform life’s daily activities with more energy and vigor and may increase a young athlete’s resistance to sports-related injuries. Along with other types of physical activity, a properly designed youth resistance training program can offer observable health value to children and adolescents when appropriately prescribed and supervised.
An approach for fixed coefficient RNS-based FIR filter

ABSTRACT In this work, an efficient new modular multiplication method for {2k−1, 2k, 2k+1−1} moduli set is proposed to implement a residue number system (RNS)-based fixed coefficient finite impulse response filter. The new multiplication approach reduces the number of partial products by using pre-loaded product block. The reduction in partial products with the proposed modular multiplication improves the clock frequency and reduces the area and power as compared with the conventional modular multiplication. Further, the present approach eliminates a binary number to residue number converter circuit, which is usually needed at the front end of RNS-based system. In this work, two fixed coefficient filter architectures with the new modular multiplication approach are proposed. The filters are implemented using Verilog hardware description language. The United Microelectronics Corporation 90 nm technology library has been used for synthesis and the results area, power and delay are obtained with the help of Cadence register transfer level compiler. The power delay product (PDP) is also considered for performance comparison among the proposed filters. One of the proposed architecture is found to improve PDP gain by 60.83% as compared with the filter implemented with conventional modular multiplier. The filters functionality is validated with the help of Altera DSP Builder.
Mind Wandering in a Smartphone World: The Impact of Pervasive Smartphone Usage on Mind Wandering and Attentional Restoration

Mind-wandering is a cognitive process that often occurs during idleness and rest. Nowadays, due to the rise of the smartphone’s popularity, people tend to spend most of their free time on their mobile devices. Previous research has evaluated the primarily negative impact of both mind-wandering and smartphone usage during attention and performance tasks. The aim of this work was to investigate the impact of smartphone usage and mind-wandering during periods of rest on one’s ability to maintain attention during a subsequent task. In this study, participants (N = 129) completed an attentional network test, under two conditions: (a) without breaks between test sections and (b) with two breaks, which they spent either using their smartphones or letting their minds wander. Results indicate that the smartphone break led to higher levels of mindwandering during the task, compared to other conditions. Moreover, the smartphone break improved performance and reduced reaction time during the task. The present findings confirm the complexity of the relationship between attention and mindwandering, as well as between attention and smartphone usage. Future studies should address these findings and reexamine previous assumptions that mind-wandering and attention, and smartphone usage and attention are anticorrelated processes.
Tartan: A taskbot that assists with recipes and do-it-yourself projects

Tartan is a multi-domain task-oriented bot that assists users with two different tasks: 1. cooking with recipes from Whole Foods and 2. doing projects from WikiHow. The bot’s system is divided into two stages. In the ﬁrst stage, the bot assists the user in identifying a task that they want to do. In the second stage, the bot guides the users through sequences of step-by-step instructions. We developed several machine learning based components to guide the bot, including a domain classiﬁer, named entity extractor, and question answering module. The core of the system is a dialogue manager. The dialogue manager guides a user’s session, referencing information from the aforementioned components. Primarily, the dialogue manager is rule-based, necessitated by the lack of domain-speciﬁc data available to it. We describe our systems and provide observations on its behavior.
Hiding Critical Program Components via Ambiguous Translation

Software systems may contain critical program components such as patented program logic or sensitive data. When those components are reverse-engineered by adversaries, it can cause significantly damage (e.g., financial loss or operational failures). While protecting critical program components (e.g., code or data) in software systems is of utmost importance, existing approaches, unfortunately, have two major weaknesses: (1) they can be reverse-engineered via various program analysis techniques and (2) when an adversary obtains a legitimate-looking critical program component, he or she can be sure that it is genuine. In this paper, we propose Ambitr, a novel technique that hides critical program components. The core of Ambitr is Ambiguous Translator that can generate the critical program components when the input is a correct secret key. The translator is ambiguous as it can accept any inputs and produces a number of legitimate-looking outputs, making it difficult to know whether an input is correct secret key or not. The executions of the translator when it processes the correct secret key and other inputs are also indistinguishable, making the analysis inconclusive. Our evaluation results show that static, dynamic and symbolic analysis techniques fail to identify the hidden information in Ambitr. We also demonstrate that manual analysis of Ambitr is extremely challenging.
Primary Folding of Aspartylglucosaminidase SIGNIFICANCE OF DISULFIDE BRIDGES AND EVIDENCE OF EARLY MULTIMERIZATION*

Aspartylglucosaminidase (AGA) is a lysosomal enzyme involved in the degradation ofN-linked glycoproteins in lysosomes. AGA is synthesized as an inactive precursor molecule, which is rapidly activated in the endoplasmic reticulum by a proteolytic cleavage into aand b-subunits. We have recently determined the three-dimensional structure of AGA and shown that it is a globular molecule with a heterotetrameric (ab)2 structure. On the basis of structural and functional analyses, AGA seems to be the first mammalian protein belonging to a newly described protein family, the N-terminal nucleophile hydrolases. Because the activation of the prokaryotic members of the N-terminal nucleophile hydrolase family seems to be triggered by the assembly of the subunits, we have studied the initial folding and oligomerization of AGA and provide evidence that dimerization of two precursor molecules in the endoplasmic reticulum is a prerequisite for the activation of AGA. To gain further information on the structural determinants influencing the early folding of AGA, we used site-specific mutagenesis of cysteine residues to define the role of intrachain disulfide bridges in the folding and activation of the enzyme. The N-terminal disulfide bridges in both the aand b-subunits seem to have only a stabilizing role, whereas the C-terminal disulfide bridge in both subunits evidently plays an important role in the early folding and activation of AGA.
Nonequilibrium THz conductivity of Bi 2 Sr 2 CaCu 2 O 8+ δ

Using high sensitivity visible-pump/THz-probe spectroscopy we investigate the dynamics of the complex optical conductivity, σ ( ω ) = σ 1 ( ω ) + i σ 2 ( ω ), in optimally-doped Bi 2 Sr 2 CaCu 2 O 8+ δ films directly after photoexcitation. The photoinduced change in the imaginary part Δσ 2 , indicative of a reduction in the superconducting condensate density, saturates at higher laser-fluences and shows a complete destruction of the condensate.
DMSO_A_355980 1677..1686

Purpose: Diabetes is one of the most prevalent chronic diseases in the world, and its prevalence is expected to rise further. To help understand the utility of the ratio of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol (NHHR) in diabetes prevention, this large-scale longitudinal cohort study aims to explore the association of NHHR with diabetes risk and compare it as a risk predictor with conventional lipid parameters. Patients and Methods: This observational study extracted data from the NAGALA longitudinal cohort study conducted in Japan between 2004 and 2015. Multivariate Cox regression analysis was used to evaluate the association between NHHR and the risk of diabetes. The dose–response relationship was analyzed by restricted cubic spline (RCS) regression and the potential risk threshold was estimated. The receiver operator characteristic curve (ROC) was used to analyze and calculate the predictive value and optimal threshold of NHHR and other conventional lipids for new-onset diabetes. Results: Of the 15,464 people aged 18–79, 373 (2.41%) were diagnosed with new-onset diabetes during the study period, with a median age of 46 years. The sensitivity analysis based on multivariate adjustment showed that the independent positive correlation between diabetes and NHHR was stable in different populations. RCS and ROC analysis indicated that the association between NHHR and diabetes was non-linear, and the NHHR was a better marker for predicting diabetes risk than other conventional lipid parameters; Additionally, it is worth noting that an NHHR of approximately 2.74 may be the optimal threshold for intervention in diabetes risk. Conclusion: In the general population, NHHR is a better marker for predicting diabetes risk than conventional lipid parameters, and an NHHR of about 2.74 may be the optimal threshold for assessing diabetes risk.
Crude extract of Jatobá leaves promotes canine osteosarcoma cell D17 proliferation

Background and Aim: New substances for neoplasm treatment have to be carefully studied to minimize adverse effects and prevent disease progression stimulation. Jatobá is a typical tree of the Cerrado and Caatinga biome, with antifungal, antimicrobial, larvicide, antioxidant, and antiproliferative properties. This study aimed to investigate the action of the crude extract of Jatobá leaves (EBFJ) on canine osteosarcoma (CO) cells and analyze the expression of biomarkers in neoplasm progression. Materials and Methods: D17 cells were cultured and subjected to treatment with EBFJ at different concentrations (10 μg/mL; 100 μg/mL; 1000 μg/mL; 2000 μg/mL; and 5000 μg/mL) and exposure times (24 h, 48 h, and 72 h). The tetrazolium reduction assay and the immunocytochemistry technique, with anti-Bcl2, anti-p53, and anti-Ki-67 antibodies, were used to observe the effect of the extract on cell proliferation. Results: Doses of 2000 µg and 5000 µg had cell viability of 300.80% and 361.84%, respectively. The extract did not show significant cytotoxicity of samples with the control group. The confluence of cells, the number of labeled cells, and the expression of Bcl2, Ki-67, and p53 were higher in the groups treated with EBFJ, with a statistical difference from the group without treatment. Conclusion: EBFJ was not cytotoxic and had a proliferative effect on CO D17 cells. The confluence of cells, the number of labeled cells, and the expression of Bcl2, Ki-67, and p53 were higher in the groups treated with the extract.