Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization Challenges of a Low Noise Charge Detection ROIC

This article presents the experimentally characterized performance of a low noise and wideband sensor readout integrated circuit (ROIC). The ROIC is designed to detect small amounts of charge generated by a silicon p-i-n detector as a result of particle detection, with very high time resolution and limited power consumption. The architecture of the ROIC permits the analog components of the particle readout to be designed with a reduced bandwidth by implementing the so-called intersymbol interference (ISI) cancellation technique, which improves the noise performance, while reducing the deterministic ISI-induced errors associated with the narrowband circuit; hence, a low error rate (ER) can be maintained. The readout is designed to detect 160 aC charge portions delivered randomly by the detector at a maximum of $4 \times 10^{8}$ events/s with a small average ER while consuming 2.85 mW. Detailed information about the ROIC designed in 65-nm CMOS technology, and the simulated performance, are already reported in a previous publication. This article aims to present the challenges related to the design of the test setup and the obtained experimental results with the first prototype of the ROIC, as well as to discuss the data acquisition process.
Novel In-Memory Computing Adder Using 8+T SRAM

Von Neumann architecture-based computing systems are facing a von Neumann bottleneck owing to data transfer between separated memory and processor units. In-memory computing (IMC), on the other hand, reduces energy consumption and improves computing performance. This study explains an 8+T SRAM IMC circuit based on 8+T differential SRAM (8+T SRAM) and proposes 8+T SRAM-based IMC full adder (FA) and 8+T SRAM-based IMC approximate adder, which are based on the 8+T SRAM IMC circuit. The 8+T SRAM IMC circuit performs SRAM read and bitwise operations simultaneously and performs each logic operation parallelly. The proposed IMC FA and the proposed IMC approximate adder can be applied to a multi-bit adder. The two adders are based on the 8+T SRAM IMC circuit and thus read and compute simultaneously. In this study, the 8+T SRAM IMC circuit was applied to the adder, leveraging its ability to perform read and logic operations simultaneously. According to the performance in this study, the 8+T SRAM IMC circuit, proposed FA, proposed RCA, and proposed approximated adder are good candidates for IMC, which aims to reduce energy consumption and improve overall performance.
Multi Biometric Model for Authentication Method

In recent years, biometric authentication has seen considerable improvements in reliability and accuracy,with some biometrics contribute reasonably good overall performance. In biometric based systems for identity verification, static ,(and/or) dynamic biometric measures may be used as personal passwords. However, even the most advanced biometric systems are still facing numerous problems, some inherent to the type of data and some to the methodology itself. Each biometric system must perform four basic tasks i.e. acquisition, feature extraction, matching and decision making. Multimodal systems can significantly improve the recognition and authentication performance in addition to improving population coverage, preventing spoof attacks, increasing the degrees of freedom, and decreasing the failure-to-enroll rate. A Multimodal Biometric Authentication Method is proposed that fuses results from both the RS (Reference Subject) and the user’s biometric data to generate a BioCapsule based on secure fusion and employing Biometric Cryptosystems for authentication. The proposed authentication system uses the face and iris image for authenticating a user to access the system. The proposed multimodal biometric authentication method possesses a number of unique qualities, such a user-centric model, privacy-preserving, identity bearing, revocability, cancellable biometrics, non-intrusive authentication and resilient to attacks. It also supports “one-click sign-on” across systems by fusing the user’s biometrics with a distinct RS on each system. The secure fusion based approach is secure against various attacks and it is formally proved.
The Complete Mitochondrial Genome of the Chicken Body Louse, Menacanthus cornutus, and Evolutionary Patterns of Extensive Gene Rearrangements in the Mitochondrial Genomes of Amblycera (Psocodea: Phthiraptera)

Animal mitochondrial (mt) genomes are typically double-strand circular DNA molecules, but diverse structural variations have been widely found in multiple groups. In parasitic lice (Phthiraptera), the structure of mt genomes varies remarkably across all five suborders. In this study, we reported the complete mt genome of a chicken body louse, Menacanthus cornutus, which has a typical single circular mt chromosome and drastic mt gene rearrangements. This mt genome is 15,693 bp in length, consisting of 13 protein-coding genes, 23 tRNA genes, 2 rRNA genes, and a control region. A comparison with a typical insect mt genome suggested that two highly similar trnM are present in the mt genome of M. cornutus. Moreover, almost every single gene was rearranged, and over half of mt genes were inverted. Phylogenetic analyses inferred from the mt genome sequences supported the monophyly and position of Amblycera. Mapped over the phylogenetic relationships of Amblycera, we identified two inversion events for the conserved gene blocks in Boopidae and Menoponidae. The inverted ND4L-ND4 was likely a synapomorphic rearrangement in Menoponidae. Our study demonstrated the importance of sequencing mt genomes for additional taxa to uncover the mechanism underlying the structural evolution of the mt genome in parasitic lice.
The Effect of Eight-Week Functional Core Training on Core Stability in Young Rhythmic Gymnasts: A Randomized Clinical Trial

It is suggested that core stability (CS) might improve rhythmic gymnasts’ performance. Nevertheless, the effect of core stability training (CST) in CS performance is not clear. Purpose: Evaluating the effect of an eight-week functional CST on young rhythmics gymnasts’ CS performance. Method: A sample of 45 young female rhythmic gymnasts from a competitive team (age = 10.5 ± 1.8 years, height = 144.1 ± 10.6 cm, weight 38.2 ± 8.9 kg, peak height velocity (PHV) = 12.2 ± 0.6 years) participated in the study. The participants were randomly allocated into the control group (CG) and experimental group (EG) and completed pre-tests and post-tests of specific CS tests using a pressure biofeedback unit (PBU). The CS was assessed by the bent knee fall out (BKFO), the active straight leg raise (ASLR) tests and the pelvic tilt test, all performed on the right and left sides. The EG (n = 23) performed an eight-week functional CST program based on rhythmic gymnastics (RG) technical requirements added to the traditional RG training sessions. Meanwhile, the CG (n = 22) received the traditional RG training sessions. Results: Mixed model analysis showed non-significant interaction effects; however, the ANOVA omnibus test showed a time effect (p < 0.05) in right BKFO (F1,42 = 4.60; p = 0.038) and both pelvic tilt tests (right F1,42 = 22.01, p < 0.001; left F1,42 = 19.13, p < 0.001). There were non-significant interaction effects. The fixed effects estimated parameters for right BKFO showed that both groups had less pressure variation after intervention compared with pre-intervention (β = −1.85 mmHg, 95%CI = [−3.54 to −0.16], t42 = −2.14, p = 0.038). Furthermore, the left pelvic tilt (β = 37.0 s, 95%CI = [20.4 to 53.6], t42 = 4.37, p < 0.001) improved 8.9 s more than the right pelvic tilt (β = 28.1 s, 95%CI = [16.3 to 39.8], t42 = 4.69, p < 0.001) considering both groups together. Conclusions: Adding a functional CST to regular training showed a trend in improving the performance of CS-related variables, which could help improve RG-specific performance. Coaches working with rhythmic gymnasts should consider adding a functional CST to regular training to improve CS performance leading to increased specific RG performance.
Evaluation of Dietary Management Using Artificial Intelligence and Human Interventions: Nonrandomized Controlled Trial

Background There has been an increase in personal health records with the increased use of wearable devices and smartphone apps to improve health. Traditional health promotion programs by human professionals have limitations in terms of cost and reach. Due to labor shortages and to save costs, there has been a growing emphasis in the medical field on building health guidance systems using artificial intelligence (AI). AI will replace advanced human tasks to some extent in the future. However, it is difficult to sustain behavioral change through technology alone at present. Objective This study investigates whether AI alone can effectively encourage healthy behaviors or whether human interventions are needed to achieve and sustain health-related behavioral change. We examined the effectiveness of AI and human interventions to encourage dietary management behaviors. In addition, we elucidated the conditions for maximizing the effect of AI on health improvement. We hypothesized that the combination of AI and human interventions will maximize their effectiveness. Methods We conducted a 3-month experiment by recruiting participants who were users of a smartphone diet management app. We recruited 102 participants and divided them into 3 groups. Treatment group I received text messages using the standard features of the app (AI-based text message intervention). Treatment group II received video messages from a companion, in addition to the text messages (combined text message and human video message intervention by AI). The control group used the app to keep a dietary record, but no feedback was provided (no intervention). We examine the participants’ continuity and the effects on physical indicators. Results Combined AI and video messaging (treatment group II) led to a lower dropout rate from the program compared to the control group, and the Cox proportional-hazards model estimate showed a hazard ratio (HR) of 0.078, which was statistically significant at the 5% level. Further, human intervention with AI and video messaging significantly reduced the body fat percentage (BFP) of participants after 3 months compared to the control group, and the rate of reduction was greater in the group with more individualized intervention. The AI-based text messages affected the BMI but had no significant effect on the BFP. Conclusions This experiment shows that it is challenging to sustain participants' healthy behavior with AI intervention alone. The results also suggest that even if the health information conveyed is the same, the information conveyed by humans and AI is more effective in improving health than the information sent by AI alone. The support received from the companion in the form of video messages may have promoted voluntary health behaviors. It is noteworthy that companions were competent, even though they were nonexperts. This means that person-to-person communication is crucial for health interventions.
Selecting Stochastic Climate Realizations to Efficiently Explore a Wide Range of Climate Risk to Water Resource Systems

AbstractThere are significant computational requirements for assessing climate change impacts on water resource system reliability and vulnerability, particularly when analyzing a wide range of plausible scenarios. These requirements often deter analysts from exhaustively identifying climate hazards. This technical note investigates two approaches for generating a subset of stochastic climate realizations that efficiently explore a range of risk to water supply systems. In both methods, a large ensemble of stochastic weather time series is generated to simulate the natural variability of the local climate system, and a selected subset of these sequences is used in the impacts assessment. Method 1 selects the subset by first passing the entire ensemble through a rainfall-runoff model and then screening the hydrologic sequences using the sequent peak algorithm. Method 2 selects a subset of climate sequences based on climate statistics alone, prior to hydrological modeling. Both methods provide insight for i.
Emotional Personalization in Immersive Journalism: Exploring the Influence of Emotional Testimonies and Modality on Emotional Valence, Presence, Empathy, and Recall

Abstract Immersive journalism (IJ), where individuals engage in a news story from a first-person perspective using interactive technologies, has become increasingly popular in recent years. Such stories may improve the impact of journalism on the audience by enhancing feelings and emotions associated with the news content. Studies have shown that rather than undermining rationality, emotion could increase engagement toward news pieces, and improve knowledge of social issues. Emotional personalization (EP), a strategy where the production of news content involves the emotional testimony of ordinary citizens at the heart of the story, is therefore increasingly employed. This study explores how EP, as well as the modality of IJ content, influences our perceptions and cognitions with regards to an IJ piece on war and conflict. In our study, 193 participants took part in a 2 (EP: present vs. absent) × 2 (modality: VR vs. desktop) experiment. Participants in the EP-present condition reported stronger feelings of presence and greater story recall, while those in the VR condition experienced lower emotional valence and stronger feelings of empathy. Our results support current literature on IJ and EP and suggest that with the rising interest in immersive technologies, sustained investigation on the implications of EP strategies in IJ is crucial.
Electrical-Thermal-Reliability Co-Design for TSV-Based 3D-ICs

This paper presents an electrical-thermal-reliability co-design technique for TSV-based 3D-ICs. Although TSV-based 3D-IC shows significant electrical performance improvement compared to traditional 2D circuit, researchers have reported strong electromigration (EM) in TSVs, which is induced by the thermal mechanical stress and the local temperature hotspot. We argue that rather than addressing 3D-IC’s EM issue after the IC designing phase, the designer should be aware of the circuit’s thermal and EM properties during the IC designing phase. For example, one should be aware that the TSVs establish vertical heat conduction path thus changing the chip’s thermal profile and also produce significant thermal mechanical stress to the nearby TSVs, which deteriorates other TSV’s EM reliability. Therefore, the number and location of TSVs play a crucial role in deciding 3D-IC’s electrical performance, changing its thermal profile, and affecting its EM-reliability. We investigate the TSV placement problem, in order to improve 3D-IC’s electrical performance and enhance its thermal-mechanical reliability. We derive and validate simple but accurate thermal and EM models for 3D-IC, which replace the current employed time-consuming finite-element-method (FEM) based simulation. Based on these models, we propose a systematic optimization flow to solve this TSV placement problem. Results show that compared to conventional performance-centered technique, our design methodology achieves 3.24x longer EM-lifetime, with only 1% performance degradation. © 2015 ASME
THE ROLE OF WOMEN’S TRANSFORMATIVE POLITICAL LEADERSHIP IN DECONSTRUCTING PATRIARCHY DURING COVID-19 PANDEMIC

AbstrakBerita media massa dalam waktu dua tahun terakhir selalu pesan-pesan yang disebarkan dari sosial media, konferensi pers hampir selalu menampilkan informasi dan opini mengenai penyebaran virus Corona sebagai krisis kesehatan yang telah menggobal. Tanggapan bersama terhadap pandemi Covid-19 menunjukkan bahwa masyarakat percaya akan pentingnya kesejahteraan manusia dibandingkan dengan pertumbuhan ekonomi, inilah yang menjadi fokus dari kebijakan ekonomi. Pentingya reproduksi manusia secara berkelanjutan pada bidang ekonomi. Kepala daerah Kabupaten Sragen yang telah mendapat kepercayaan dan terlegitimasi kekusaaannya oleh masyarakat mengupayakan ketahanan ekonomi keluarga sebagai basis mempertahankan keberlanjutan kehidupan warganya. Tujuan dari tulisan ini untuk melihat kebijakan dan program pada bidang ekonomi yang ditetapkan oleh Bupati Sragen Kusdinar Untung Yuni Sukowati yang mampu mendobrak jeratan patriarki untuk mengatasi dampak Covid-19 pada bidang ekonomi. Pendekatan deskriptif kualitatif menjadi pedoman dalam penyusunan penelitian ini dengan pengumpulan data dari penelusuran pustaka dan dokumentasi. Hasil penelitian menunjukkan bahwa perempuan yang diberi kesempatan dan kepercayaan untuk menjadi pemimpin politik mampu merespon permasalahan yang dihadapi rakyatnya. Bupati Sragen yang seorang perempuan menerapkan kepemimpinan transformatif pada masa Covid-19 mengupayakan berbagai cara guna mempertahankan sumber daya ekonomi masyarakatnya dengan melibatkan dan memberdayakan semua sumber daya yang ada di wilayahnya. AbstractMass media news in the last two years has always been messages spread from social media, press conferences almost always display information and opinions about the spread of the Corona virus as a global health crisis. All responses to the Covid-19 pandemic shows that people believe in the importance of human well-being compared to economy growth, which is the focus of economy policy. The importance is economy sustainable reproduction. The regional head of Sragen Regency who has gained trust and legitimized her power by citizens seeks the economy resilience of the family as a basis for maintaining the sustainability of life. The purpose of this paper to show economy policies and programs of Kusdinar Untung Yuni Sukowati as a Sragen Regent who was able to break the patriarchy's entanglements to overcome the economy impact of Covid-19. Qualitative description approach as guidelines of this research with the data collection from library browsing and documentation. Result of this research show that women who given the opportunity and trust to become a political leader able to respond to the problems faced by her people. Regent Sragen who is a woman implementing transformative leadership during Covid-19 seeks various ways to maintain and strengthen economy of her citizens by involving and empowering all resources in her region.
Development of an LC–DAD–MS-Based Method for the Analysis of Hydroxyanthracene Derivatives in Food Supplements and Plant Materials

Products based on plants containing hydroxyanthracene derivatives (HADs)—such as Rheum, Cassia, and Aloe species—are widely used in food supplements or nutraceuticals due to their laxative effects. A more restricted control of HAD contents in food supplements has been implemented by EU Regulation 2021/468, in order to increase the safety of these preparations. Due to their toxicity, aloin A, aloin B, aloe emodin, emodin, and the synthetic derivative danthron have been listed as prohibited substances in food supplements, being tolerated in amounts < 1 mg kg−1 in marketed products. In this work, we report the development of a sensitive and fast LC–DAD–MS-based procedure for the determination of these five compounds in food supplements and plant materials or extracts. The entire procedure includes a simple sample preparation step, where target analytes are concentrated by means of solvent extraction and evaporative concentration (solid samples), or by lyophilisation (liquid samples). The average LOQ of 0.10 mg/L, LOD of 0.03 mg/L, accuracy, and precision with CVs below 12.72 were obtained for the studied analytes. This method is suitable for assessing the compliance of commercial products and raw materials with EU Regulation 2021/468. Furthermore, the proposed method can represent a starting point for the development of a unique and standardised analytical approach for the determination of other HADs under the attention of EU authorities.
Distinct element modelling of jointed rock masses : algorithms and their verification

The distinct element method (DEM) is a useful tool in rock engineering to model jointed rock masses. To simulate a jointed rock mass realistically, the main challenge is to be able to capture its complex geometry which consists of blocks with various shapes and sizes, and to model the interactions between these blocks. The main contribution of this thesis is the development of novel algorithms in the DEM to model jointed rock masses, namely rock slicing procedures for block generation, and algorithms for contact detection between polygonal blocks in 2-D or polyhedral blocks in 3-D. These algorithms make use of convex optimisation techniques, for which there exist efficient solution procedures. They do not rely on conventional vertex-edge-face hierarchical data structures and tedious housekeeping algorithms. The algorithms have been verified against analytical and numerical solutions, as well as validated against experimental results published in the literature. Among those, the results of DEM simulations were compared against the experimental model tests and numerical simulations of jointed beams carried out by Talesnick et al. (2007) and Tsesarsky & Talesnick (2007) respectively. Emphasis was placed on modelling the stiffness of the block interfaces accurately, and this was accomplished by reinterpreting the laboratory data published by the investigators. The capabilities of the numerical tools are also examined and demonstrated in areas for which the DEM has found practical application. A substantial fraction of this thesis is devoted to illustrating how these tools can assist the engineer in designing support systems; for example, designing the length and spacing of rock bolts and the lining thickness for a tunnel. Algorithms to model rock bolt and lining support were implemented for this purpose. Interesting comparisons with elastic solutions for supported openings were obtained. Further, it is shown that the relative benefit of introducing more rock bolts or thicker lining can be evaluated using the numerical tools with the aid of an interaction diagram. In the final part of this thesis, the case history of the 1963 Vaiont rock slide in Italy is studied. The 2-D analyses led to useful insights concerning the influence of the reservoir water level, the rock mass strength and deformability, and the slide surface shear stiffness. 3-D analyses were undertaken to investigate the influence of the eastern boundary of the slope, and interesting insights were obtained concerning the slope kinematics. Overall, the case study shows that the tools are capable of modelling problems with specific physical and geometrical detail in both 2-D and 3-D.
Emotional Intelligence, Psychological Well-Being and Burnout of Active and In-Training Teachers

The main activating variables of psychological well-being and Emotional Intelligence that influence teachers include the process of evaluating well-being, their motivation, and their ability to perceive and regulate sources of stress and burnout. The relationship and influence of psychological well-being and emotional intelligence was analyzed with the adequate regulation of burnout. Those who participated included 386 active teachers (55%), and teachers in training (45%), studying for degrees in Pre-School and Primary Education, and Master’s degrees in Secondary Education Teacher Training of which 71.5% were women. The following were used: Psychological Well-Being Scales, Trait Meta-Mood Scale and the Spanish Burnout Inventory. Pearson’s correlation analysis and multiple regression analysis were performed. The results showed that enthusiasm for the teaching job is related to psychological well-being, especially domain of the environment and personal growth. Multiple regression analysis made it possible to establish a predictive model of well-being, showing that psychological well-being is the main adjustment predictor and/or the mismatch in the work of the teaching staff in both samples, through an adequate regulation of positive relationships, mastery of their environment and having a purpose in life.