Miracle-dz/UniFAR-FTUs huggingface dataset:
Can Deep Networks Learn to Play by the Rules? A Case Study on Nine Men's Morris

Deep networks have been successfully applied to a wide range of tasks in artificial intelligence, and game playing is certainly not an exception. In this paper, we present an experimental study to assess whether purely subsymbolic systems, such as deep networks, are capable of learning to play by the rules, without any a priori knowledge neither of the game, nor of its rules, but only by observing the matches played by another player. Similar problems arise in many other application domains, where the goal is to learn rules, policies, behaviors, or decisions, simply by the observation of the dynamics of a system. We present a case study conducted with residual networks on the popular board game of Nine Men's Morris, showing that this kind of subsymbolic architecture is capable of correctly discriminating legal from illegal decisions, just from the observation of past matches of a single player.
Contactless Monitoring of Breathing Patterns and Respiratory Rate at the Pit of the Neck: A Single Camera Approach

Vital signs monitoring is pivotal not only in clinical settings but also in home environments. Remote monitoring devices, systems, and services are emerging as tracking vital signs must be performed on a daily basis. Different types of sensors can be used to monitor breathing patterns and respiratory rate. However, the latter remains the least measured vital sign in several scenarios due to the intrusiveness of most adopted sensors. In this paper, we propose an inexpensive, off-the-shelf, and contactless measuring system for respiration signals taking as region of interest the pit of the neck. The system analyses video recorded by a single RGB camera and extracts the respiratory pattern from intensity variations of reflected light at the level of the collar bones and above the sternum. Breath-by-breath respiratory rate is then estimated from the processed breathing pattern. In addition, the effect of image resolution on monitoring breathing patterns and respiratory rate has been investigated. The proposed system was tested on twelve healthy volunteers (males and females) during quiet breathing at different sensor resolution (i.e., HD 720, PAL, WVGA, VGA, SVGA, and NTSC). Signals collected with the proposed system have been compared against a reference signal in both the frequency domain and time domain. By using the HD 720 resolution, frequency domain analysis showed perfect agreement between average breathing frequency values gathered by the proposed measuring system and reference instrument. An average mean absolute error (MAE) of 0.55 breaths/min was assessed in breath-by-breath monitoring in the time domain, while Bland-Altman showed a bias of −0.03 ± 1.78 breaths/min. Even in the case of lower camera resolution setting (i.e., NTSC), the system demonstrated good performances (MAE of 1.53 breaths/min, bias of −0.06 ± 2.08 breaths/min) for contactless monitoring of both breathing pattern and breath-by-breath respiratory rate over time.
An Indoor and Outdoor Positioning Using a Hybrid of Support Vector Machine and Deep Neural Network Algorithms

Indoor and outdoor positioning lets to offer universal location services in industry and academia. Wi-Fi and Global Positioning System (GPS) are the promising technologies for indoor and outdoor positioning, respectively. However, Wi-Fi-based positioning is less accurate due to the vigorous changes of environments and shadowing effects. GPS-based positioning is also characterized by much cost, highly susceptible to the physical layouts of equipment, power-hungry, and sensitive to occlusion. In this paper, we propose a hybrid of support vector machine (SVM) and deep neural network (DNN) to develop scalable and accurate positioning in Wi-Fi-based indoor and outdoor environments. In the positioning processes, we primarily construct real datasets from indoor and outdoor Wi-Fi-based environments. Secondly, we apply linear discriminate analysis (LDA) to construct a projected vector that uses to reduce features without affecting information contents. Thirdly, we construct a model for positioning through the integration of SVM and DNN. Fourthly, we use online datasets from unknown locations and check the missed radio signal strength (RSS) values using the feed-forward neural network (FFNN) algorithm to fill the missed values. Fifthly, we project the online data through an LDA-based projected vector. Finally, we test the positioning accuracies and scalabilities of a model created from a hybrid of SVM and DNN. The whole processes are implemented using Python 3.6 programming language in the TensorFlow framework. The proposed method provides accurate and scalable positioning services in different scenarios. The results also show that our proposed approach can provide scalable positioning, and 100% of the estimation accuracies are with errors less than 1 m and 1.9 m for indoor and outdoor positioning, respectively.
Osiris: A Low-Cost Mechanism to Enable Restoration of Secure Non-Volatile Memories

With Non-Volatile Memories (NVMs) beginning to enter the mainstream computing market, it is time to consider how to secure NVM-equipped computing systems. Recent Meltdown and Spectre attacks are evidence that security must be intrinsic to computing systems and not added as an afterthought. Processor vendors are taking the first steps and are beginning to build security primitives into commodity processors. One security primitive that is associated with the use of emerging NVMs is memory encryption. Memory encryption, while necessary, is very challenging when used with NVMs because it exacerbates the write endurance problem. Secure architectures use cryptographic metadata that must be persisted and restored to allow secure recovery of data in the event of power-loss. Specifically, encryption counters must be persistent to enable secure and functional recovery of an interrupted system. However, the cost of ensuring and maintaining persistence for these counters can be significant. In this paper, we propose a novel scheme to maintain encryption counters without the need for frequent updates. Our new memory controller design, Osiris, repurposes memory Error-Correction Codes (ECCs) to enable fast restoration and recovery of encryption counters. To evaluate our design, we use Gem5 to run eight memory-intensive workloads selected from SPEC2006 and U.S. Department of Energy (DoE) proxy applications. Compared to a write-through counter-cache scheme, on average, Osiris can reduce 48.7% of the memory writes (increase lifetime by 1.95x), and reduce the performance overhead from 51.5% (for write-through) to only 5.8%. Furthermore, without the need for backup battery or extra power-supply hold-up time, Osiris performs better than a battery-backed write-back (5.8% vs. 6.6% overhead) and has less write-traffic (2.6% vs. 5.9% overhead).
Leveraging CPU Electromagnetic Emanations for Voltage Noise Characterization

Worst-case dI/dt voltage noise is typically characterized post-silicon using direct voltage measurements through either on-package measurement points or on-chip dedicated circuitry. These approaches consume expensive pad resources or suffer from design-time and run-time overheads. This work proposes an alternative non-intrusive, zero-overhead approach for post-silicon dI/dt voltage noise generation based on sensing CPU electromagnetic emanations using an antenna and a spectrum analyzer. The approach is based on the observation that high amplitude electromagnetic emanations are correlated with high voltage noise. We leverage this observation to automatically generate voltage noise (dI/dt) stress tests with a genetic-algorithm that is driven by electromagnetic signal amplitude and to obtain the first-order resonance-frequency of the Power-Delivery LC-tank network. The generality of the approach is established by successfully applying it to three different CPUs: two ARM multi-core mobile CPU clusters hosted on a big.LITTLE configuration and an x86-64 AMD desktop CPU. The efficacy of the proposed methodology is validated through VMIN and direct voltage noise measurements.
Exposure to phthalates aggravates pulmonary function and airway inflammation in asthmatic children

Introduction Studies on the associations between phthalate exposures and respiratory outcomes are limited. We investigated the association of phthalates exposure with pulmonary function and airway inflammation in asthmatic children. Methods Fifty-six children with asthma living in Seoul Metropolitan Area, Korea aged 6–16 years were enrolled. Their pulmonary function including forced expiratory volume in 1 sec (FEV1) and peak expiratory flow rate (PEFR) were measured, and the fractional exhaled nitric oxide (FeNO) as a marker of airway inflammation was examined repeatedly up to four times during the study period. Urinary levels of mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP) and mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP), metabolites for di-(2-ethylhexyl) phthalate (DEHP), and mono-n-butyl phthalate (MnBP), a metabolite of di-n-butyl phthalate (DnBP), were also measured on the same days. The effects of phthalate metabolites on the respiratory symptoms were analyzed using linear mixed effect models with adjustment for potential cofounders. Results An increase in phthalate metabolites was associated with a decrease in pulmonary function and an increase in FeNO in asthmatic children. As one natural log-unit (ln-unit) levels of urinary MEHHP and MEOHP increased, FeNO levels on the same day increased by 19.47 ppb [95% confidence interval (CI): 9.28, 29.67] and 17.93 ppb (95% CI: 5.86, 30.01), respectively. An increases in the urinary level of MEHHP, MEOHP, and MnBP by one ln-unit was associated with a decrease in PEFR on the next day by 12.17 L/min (95% CI: 2.59, 21.74), 10.80 L/min (95% CI: 0.29, 21.32), and 13.65 L/min (95% CI: 5.07, 22.24), respectively. Conclusion Phthalates, especially DEHP, may worsen pulmonary function and airway inflammation in asthmatic children. To control asthma symptoms, exposure to phthalates needs to be avoided.
Novel Design of Miniaturized Filtering Power Dividers Using Dual-Composite Right-/Left-Handed Resonators

One kind of miniaturized filtering power divider (FPD) with a new topology is proposed. For previously published FPDs, the isolation resistors were usually added with additional quarter-wave (<inline-formula> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula>/4) transmission lines for output isolation. In this paper, <inline-formula> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula>/4 transmission lines are removed, and the resistor is added to the loaded resonator for the miniaturized design. By regarding the input external quality factor (<inline-formula> <tex-math notation="LaTeX">$Q_{e\text {-in}}$ </tex-math></inline-formula>) as an admittance inverter, the indispensable 90° delay can be easily realized. To further improve the miniaturization, the dual-composite right-/left-handed (D-CRLH) resonators are adopted; therefore, the overall sizes of the resulting FPDs can be smaller than <inline-formula> <tex-math notation="LaTeX">$0.012\lambda _{g}^{2}$ </tex-math></inline-formula>. Moreover, the equivalent circuit of the proposed FPD is investigated for the performance improvement. Input <inline-formula> <tex-math notation="LaTeX">$Q_{e\text {-in}}$ </tex-math></inline-formula> should be double of output <inline-formula> <tex-math notation="LaTeX">$Q_{e\text {-out}}$ </tex-math></inline-formula> for good matching, and good isolation can be obtained by appropriately utilizing <inline-formula> <tex-math notation="LaTeX">$Q_{e\text {-in}}$ </tex-math></inline-formula>. For demonstration, three D-CRLH FPDs are designed for narrowband, wideband, and dual-band applications. Satisfactory agreements between the measured results and theoretical expectations are observed, verifying the validity of the proposed design concepts.
Culture and Customs of Botswana

Botswana's large deposits of diamonds have made it one of the richest African countries on a per capita basis. However, more than wealth, what has made Botswana a model country in southern Africa is its long tradition of democratic rule, respect for ethnic and racial differences, freedom of the press, and governmental programs to support its citizens. Even though Botswana has had its share of problems—including ecological disasters such as drought— the spirit of its people and their willingness, despite cultural differences, to work together to overcome such setbacks make this country exceptional. General readers will find a wealth of up-to-date information on such topics as the legacy of Christian missionaries, especially the famous David Livingstone, society post-Independence, the unique blend of Christianity and ancestral spiritual practices, the AIDS crisis, initiation rites, community rule by chiefs, polygamy, cattle raising, food and beer, betrothal customs, education, unique games, the integral music and dance, and much more. The authors provide a thorough, one-stop resource for learning about a significant country that has stayed peaceful despite the strife of neighboring South Africa and Angola, for example. Narrative chapters by these insiders cover the land, people, languages, education, economy, history, religion and worldview, literature and media, art and architecture, cuisine and traditional dress, gender roles, marriage, and family, social customs and lifestyle, and music and dance. Photos, a chronology, and a glossary complement the narrative.
Expanding the Reach of Federated Learning by Reducing Client Resource Requirements

Communication on heterogeneous edge networks is a fundamental bottleneck in Federated Learning (FL), restricting both model capacity and user participation. To address this issue, we introduce two novel strategies to reduce communication costs: (1) the use of lossy compression on the global model sent server-to-client; and (2) Federated Dropout, which allows users to efficiently train locally on smaller subsets of the global model and also provides a reduction in both client-to-server communication and local computation. We empirically show that these strategies, combined with existing compression approaches for client-to-server communication, collectively provide up to a $14\times$ reduction in server-to-client communication, a $1.7\times$ reduction in local computation, and a $28\times$ reduction in upload communication, all without degrading the quality of the final model. We thus comprehensively reduce FL's impact on client device resources, allowing higher capacity models to be trained, and a more diverse set of users to be reached.
The nature of the band gap of GeSn alloys

We present a detailed analysis of the electronic structure of GeSn alloys using density functional theory. Special attention is paid to Sn-induced conduction band mixing effects. Our calculations indicate a continuous evolution from an indirect to a direct band gap material with increasing Sn content. This finding is in stark contrast to the literature perception of a sharp transition at a fixed critical Sn composition. Finally, we discuss and present initial results on how the density functional data is used to establish semi-empirical tight-binding models.
The role of diet in the prevention and treatment of Inflammatory Bowel Diseases

Inflammatory bowel diseases (IBD) – Crohn’s disease (CD) and ulcerative colitis (UC) – are chronic conditions characterised by relapsing inflammation of the gastrointestinal tract. They represent an increasing public health concern and an aetiological enigma due to unknown causal factors. The current knowledge on the pathogenesis of IBD is that genetically susceptible individuals develop intolerance to a dysregulated gut microflora (dysbiosis) and chronic inflammation develops as a result of environmental triggers. Among the environmental factors associated with IBD, diet plays an important role in modulating the gut microbiome, and, consequently, it could have a therapeutic impact on the disease course. An overabundance of calories and some macronutrients typical of the Western dietetic pattern increase gut inflammation, whereas several micronutrients characteristic of the Mediterranean Diet have the potential to modulate gut inflammation, according to recent evidence. Immunonutrition has emerged as a new concept putting forward the role of vitamins such as vitamins A, C, E, and D, folic acid, beta carotene and trace elements such as zinc, selenium, manganese and iron. However, when assessed in clinical trials, specific micronutrients showed a limited benefit. Further research is required to evaluate the role of individual food compounds and complex nutritional interventions with the potential to decrease inflammation as a means of prevention and management of IBD. The current dietary recommendations for disease prevention and management are scarce and non evidence-based. This review summarizes the current knowledge on the complex interaction between diet, microbiome and immune-modulation in IBD, with particular focus to the role of the Mediterranean Diet as a tool for prevention and treatment of the disease. (www.actabiomedica.it)
Peer-assisted learning after onsite, low-dose, high-frequency training and practice on simulators to prevent and treat postpartum hemorrhage and neonatal asphyxia: A pragmatic trial in 12 districts in Uganda

An urgent need exists to improve and maintain intrapartum skills of providers in sub-Saharan Africa. Peer-assisted learning may address this need, but few rigorous evaluations have been conducted in real-world settings. A pragmatic, cluster-randomized trial in 12 Ugandan districts provided facility-based, team training for prevention and management of postpartum hemorrhage and birth asphyxia at 125 facilities. Three approaches to facilitating simulation-based, peer assisted learning were compared. The primary outcome was the proportion of births with uterotonic given within one minute of birth. Outcomes were evaluated using observation of birth and supplemented by skills assessments and service delivery data. Individual and composite variables were compared across groups, using generalized linear models. Overall, 107, 195, and 199 providers were observed at three time points during 1,716 births across 44 facilities. Uterotonic coverage within one minute increased from: full group: 8% (CI 4%‒12%) to 50% (CI 42%‒59%); partial group: 19% (CI 9%‒30%) to 42% (CI 31%‒53%); and control group: 11% (5%‒7%) to 51% (40%‒61%). Observed care of mother and newborn improved in all groups. Simulated skills maintenance for postpartum hemorrhage prophylaxis remained high across groups 7 to 8 months after the intervention. Simulated skills for newborn bag-and-mask ventilation remained high only in the full group. For all groups combined, incidence of postpartum hemorrhage and retained placenta declined 17% and 47%, respectively, from during the intervention period compared to the 6‒9 month period after the intervention. Fresh stillbirths and newborn deaths before discharge decreased by 34% and 62%, respectively, from baseline to after completion, and remained reduced 6‒9 months post-implementation. Significant improvements in uterotonic coverage remained across groups 6 months after the intervention. Findings suggest that while short, simulation-based training at the facility improves care and is feasible, more complex clinical skills used infrequently such as newborn resuscitation may require more practice to maintain skills. Trial Registration: ClinicalTrials.gov NCT03254628.
Epidemiological Characteristics of Work-Related Ocular Trauma among the Carpenters in Medan, Indonesia

BACKGROUND: Medan is the capital of North Sumatera Province and the most industrialised area of North Sumatera. One of the largest industries in Medan is the wooden industry. Ocular trauma is often happened in Medan and causes a serious problem. AIM: This study aimed to analyse the correlation between ocular trauma among the carpenters and the using of eye protection during work and educational level. METHODS: This study is conducted among the carpenters that work in the wooden industry. There were 30 carpenters that being observed about age, educational level and working hours and the using of eye protection during work that might be related to ocular trauma. All carpenters completed a comprehensive examination and interview. RESULTS: The most common age range of ocular trauma was between 26-45 years (56.7%), and all were male. Most of the traumatised carpenters educational level had a higher educational level (50%), and workers that had traumatised works more than 8 hours a day (66.7%). From this study, there was a significant correlation between ocular trauma among the carpenters and age (p = 0.047), and working hours (p = 0.039). CONCLUSION: No significant correlation between ocular trauma among the carpenters and the using of eye protection during work (p = 0.464), and educational level (0.925) was found. Furthermore to anticipate the high rate of worked-related ocular trauma required labour regulations that cover the age of recruitment workers and working hours a day. Work safety regulation protects the workers from work-related ocular trauma.