Miracle-dz/UniFAR-FTUs huggingface dataset:
To find out the effects of myofascial release in the management of Plantar Fasciitis

Background: Plantar fasciitis is regarded as the supreme reason of inferior heel pain. The pain and discomfort that comes with this condition have an intense impact on physical mobility and function. This study was conducted to evaluate the effectiveness of Myofascial release with conventional physical therapy in patients with chronic plantar fasciitis. Methods: Subjects were clinically diagnosed with chronic plantar fasciitis and then screened after assessing their suitability according to the inclusion and exclusion criteria. Subjects participating in the study were instructed about the nature of the study and the interventions and an informed written consent was taken. Data was collected from the patients visiting the outpatient department of Pakistan Institute of Medical Sciences (PIMS) Islamabad and Mega Medical Complex Hospital Rawalpindi. n=30 patients were divided into two groups using random allocation with n= 15 in each group, Group 1 received MFR with conventional physical therapy (ultrasound and exercise therapy) whereas Group 2 received conventional physical therapy alone. The treatment was given on alternative days for 2 weeks. Results: Within group analysis was done with repetitive measure ANOVA, mean percentage of visual analog scale for both groups were same at the baseline but for experimental group significantly decrease from baseline (8.00) to midline (4.73) and at the end of session (1.40). While, mean percentage of FFI in experimental group significantly decreased from baseline to midline and till the end of the sessions. Between the group analysis was performed with independent t-test and results of VAS and FFI were statistically significant in both groups (p<0.01) but mean values showed that experimental group showed more reduction in pain and improved functional level as compared to control group. Conclusion: Myofascial release technique with conventional physical therapy showed efficacy in reducing the pain intensity and increasing the foot function in chronic plantar fasciitis patients. This study will benefit the patients of plantar fasciitis for better management of their condition and thus overall quality of life of such patients will improve in future.
High-Efficiency Data Conversion Interface for Reconfigurable Function-in-Memory Computing

Recently, analog in-memory computing (IMC) systems exhibit the considerable potential to break through the inherent high computational latency and energy cost of Von Neumann’s computer architecture. However, inefficient data convertor will inhibit the performance improvement of this system. The tradeoff between different data conversion circuit technologies has turned into one of the major driving forces for the analog IMC system-level improvements. The primary contribution is in two aspects. First, this article shows a digital-to-time-to-analog converter (DTAC) with the tradeoff of latency, area, and power consumption compared to a digital-to-time converter (DTC) and digital-to-analog converter (DAC). Second, we develop an innovative reconfigurable joint-quantization nonlinear analog-to-digital convertor (JQNL-ADC) architecture with lower quantization error by merging the two paradigms of uniform input quantization and uniform output quantization. Compared to conventional DAC, DTAC can reduce power and area by <inline-formula> <tex-math notation="LaTeX">$50\times $ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$3\times $ </tex-math></inline-formula>, respectively. Compared to SAR-ADC, our JQNL-ADC can reduce area and power by <inline-formula> <tex-math notation="LaTeX">$1.6\times $ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$2\times $ </tex-math></inline-formula>, respectively. In an example of ReRAM-based reconfigurable function-IMC (RFIMC) macro with 256-kb memory, our design can reach 112.9 TOPS/W@8bIN-8bW-8bO under the 28-nm process conditions.
On the Discriminability of the Handwriting of Twins

Abstract: As handwriting is influenced by physiology, training, and other behavioral factors, a study of the handwriting of twins can shed light on the individuality of handwriting. This paper describes the methodology and results of such a study where handwriting samples of twins were compared by an automatic handwriting verification system. The results complement that of a previous study where a diverse population was used. The present study involves samples of 206 pairs of twins, where each sample consisted of a page of handwriting. The verification task was to determine whether two half‐page documents (where the original samples were divided into upper and lower halves) were written by the same individual. For twins there were 1236 verification cases—including 824 tests where the textual content of writing was different, and 412 tests where it was the same. An additional set of 1648 test cases were obtained from handwriting samples of nontwins (general population). To make the handwriting comparison, the system computed macro features (overall pictorial attributes), micro features (characteristics of individual letters), and style features (characteristics of whole‐word shapes and letter pairs). Four testing scenarios were evaluated: twins and nontwins writing the same text and writing different texts. Results of the verification tests show that the handwriting of twins is less discriminable than that of nontwins: an overall error rate of 12.91% for twins and 3.7% for nontwins. Error rates with identical twins were higher than with fraternal twins. Error rates in all cases can be arbitrarily reduced by rejecting (not making a decision on) borderline cases. A level of confidence in the results obtained is given by the fact that system error rates are comparable to that of humans (lower than that of lay persons and higher than that of questioned document examiners [QDEs]).
Land Surface Freeze/Thaw Detection Over the Qinghai–Tibet Plateau Using FY-3/MWRI Data

The spatial extent and duration of soil freeze/thaw (F/T) control water and heat exchange, the energy cycle, and climate change. Global warming causes permafrost thawing, which increases carbon emissions and in turn exacerbates climate change. Passive microwave remote sensing has been proven to be effective in monitoring land surface F/T. However, it was found that the applicability of existing passive microwave remote sensing-retrieved F/T products in large-scale areas [such as the Qinghai–Tibetan Plateau (QTP)] was influenced by some landscape factors, such as the arid climate type and terrain elevation gradient. FengYun-3 (FY-3) series satellites have accumulated nearly ten years of passive microwave data, but there is little work based on FY-3 passive microwave data to see its potential in land surface F/T status monitoring. In this work, we proposed a dynamic method to determine the surface F/T status by combining the edge detection method and discriminant function algorithm from FengYun-3B (FY-3B) X- and Ka-band microwave radiation imager (MWRI) data. Comparing the results against three F/T products based on in situ 5-cm soil temperature, we demonstrate that this algorithm performs best over different validation areas with an overall accuracy of 86.5%. More specifically, the new algorithm improved the accuracy of current F/T products in arid and semiarid regions from 73% to 90%. Additionally, the spatial distribution of frozen days over the QTP of 2018 based on the new algorithm has good consistency with the permafrost map. However, the accuracy is influenced by snowmelt and appears to be overestimated for thaw soil during the day. This algorithm performs well in QTP areas with complex topography and climate types and holds the promise of providing users with highly accurate F/T products on larger and even global scales.
A Comparative Analysis of ARIMA, GRU, LSTM and BiLSTM on Financial Time Series Forecasting

Machine learning and profound learning algorithms were one in every of the effective techniques to statistical prediction. Once it involves time series prediction, these algorithms shelled classic regression-based solutions in terms of accuracy. Long short-term memory (LSTM), one of the recurrent neural networks (RNN), has been incontestable to outperform typical prediction methods. The LSTM-based models are incorporated with further "gates" such that it will consider input data of longer sequences. LSTM-based models outperform Autoregressive Integrated Moving Average models attributable to these further capabilities (ARIMA). Gated-Recurrent Unit (GRU) and bidirectional long short-term memory (BiLSTM) are extended versions of LSTM. The major question is that an algorithmic program would shell the other two by giving smart predictions with minimum error. Bidirectional LSTMs provide extra training because it may be a 2-way formula, thus, it'll traverse the training information double (1. Left-to-right 2. Right-to-left). GRU has one gate below the LSTM architecture. Hence, our analysis is especially centred on that algorithm outperforms the opposite two and it conjointly deals with behavioural analysis of the algorithms, their comparison and therefore the standardization of hyper-parameters.
Toxicological and Metabolic Response of the Bollworm Heliothis Zea (Boddie) to Ddt.

A study of the toxicological and metabolic response of the bollworm larva, Heliothis zea (Boddie), to DDT was conducted over a three-year period. The primary objectives of this investigation were to determine if resistance to DDT had developed and to elucidate the metabolic fate of DDT in this species. Cultures of bollworm larvae from three selected locations in Louisiana were established for this study. Larvae from Baton Rouge, where populations are seldom exposed to DDT, were compared tp those from the Bunkie and Waterproof areas where DDT has been used extensively since 1947. The response to DDT of bollworm larvae from other areas of Louisiana was also investigated. In addition a survey was made of the response of bollworm larvae to endrin from five areas and toxaphene-DDT (2-1) mixture from three areas in Louisiana. Cultures were established by collecting adults from cotton fields by means of a light trap. Toxicological information was obtained by applying scalar doses of the insecticide to the dorsal thoracic region of individual larvae. LD-50's were determined by means of probit analysis of the 72-hour post-treatment observations. The response of second instar bollworm larvae from all areas to DDT was approximately the same. However, the slopes of the
Surface Modifications of Wheat Cultivar Bologna upon Treatment with Non-Equilibrium Gaseous Plasma

Seeds of wheat cultivar Bologna were treated with a low-pressure, inductively coupled, radio frequency oxygen plasma. E-mode and H-mode plasma at the real powers of 25 and 275 W, respectively, was used at treatment times of 0.1–300 s. Plasma affected seed surface chemistry, determined by XPS, and surface topography, visualized by SEM. The combined effects of functionalization and etching modified seed surface wettability. The water contact angle (WCA) exponentially decreased with treatment time and correlated with the product of discharge power and treatment time well. Super-hydrophilicity was seen at a few 1000 Ws, and the necessary condition was over 35 at. % of surface oxygen. Wettability also correlated well with O-atom dose, where super-hydrophilicity was seen at 1024–1025 m−2. A relatively high germination percentage was seen, up to 1000 Ws (O-atom dose 1023–1024 m−2), while seed viability remained unaffected only up to about 100 Ws. Extensively long treatments decreased germination percentage and viability.
Valorization of Wheat Bran by Three Fungi Solid-State Fermentation: Physicochemical Properties, Antioxidant Activity and Flavor Characteristics

Three medicinal fungi were used to carry out solid-state fermentation (SSF) of wheat bran. The results showed that the use of these fungi for SSF significantly improved wheat bran’s nutritional properties including the extraction yield of soluble dietary fiber (SDF), total phenolic content (TPC), total flavonoid content (TFC), physical properties containing swelling capacity (SC) and oil absorption capacity (OAC), as well as antioxidant activities. Electronic nose and GC–MS analyses showed that fermented wheat bran had different volatiles profiles compared to unfermented wheat bran. The results suggest that SSF by medicinal fungi is a promising way for the high-value utilization of wheat bran.
Meta-Analysis of Psychological Interventions for Reducing Stress, Anxiety, and Depression among University Students during the COVID-19 Pandemic

(1) Background: The aim of this study is to investigate the effects of internet-based intervention programs for reducing stress, anxiety, and depression among university students during the COVID-19 pandemic by conducting a meta-analysis. (2) Methods: Searches were conducted in the following databases: MEDLINE, EbscoHost Academic Search Ultimate, and PsycArticles, using a combination of “Covid-19 AND ‘Randomized Controlled Trial’ AND students”, as well as a combination of the following search terms: “internet”, “online”, “treat_”, “psycholog_”, “intervention”, “program_”, “stress_”, “depress_”, “anxiety”, “university”, “college”, ”freshm_”, “sophomore_”, and “undergraduat_”. The population, intervention, control, outcomes, and study design (PICOS) framework was used (P (population): university students during the COVID-19 pandemic; I (intervention): internet-based intervention programs for reducing stress, anxiety, and depression; C (control): no intervention, usual care, or on a waiting list; O (outcomes): stress, anxiety, and depression indicators; S (study design): meta-analysis including only randomized controlled trials (RCTs)). A meta-analysis was performed on the 10 retrieved studies published between 2021 and 2022. Only RCTs were analyzed. (3) Results: All 10 analyzed papers revealed a trend in the effectiveness of internet-based intervention for reducing stress, anxiety, and depression in university students during COVID-19. Significant effects from the included RCTs with interventions for reducing stress and depression were established. (4) Conclusions: Psychological internet-based interventions may help to reduce depression and stress among university students; however, more research is needed to determine their effectiveness in reducing anxiety.
Cross-Sectional Associations of Intakes of Starch and Sugars with Depressive Symptoms in Young and Middle-Aged Japanese Women: Three-Generation Study of Women on Diets and Health

The relationship between the intakes of saccharide subtypes and depressive symptoms is unclear in Asian countries. This cross-sectional study aimed to investigate this association among 3963 young (age of 18 years) and 3826 middle-aged (mean age of 47.8 years) Japanese women. The intakes of starch, total sugars, free sugars, sucrose, lactose, glucose, and total fructose were assessed using a validated diet history questionnaire. The prevalence of depressive symptoms was 22.0% and 16.8% among young and middle-aged women, assessed using the Center for Epidemiologic Studies Depression (CES-D) score. After adjusting for potential confounding factors, higher starch intake was associated with a lower prevalence of depressive symptoms in young women with an odds ratio (OR) of the fourth to the first quintiles of 0.75 (95% confidence interval (CI): 0.57, 0.99). Moreover, higher intakes of sugars (except for lactose) were associated with a higher prevalence of depressive symptoms in young women, with ORs (95% CI) of the fifth to the first quintiles ranging from 1.30 (0.995, 1.69) for glucose to 1.47 (1.12, 1.93) for sucrose. These associations were not observed in middle-aged women. Future prospective studies are needed to confirm these findings.
A Neural Predictive Model of Negative Emotions for COVID-19

The long-lasting global pandemic of Coronavirus disease 2019 (COVID-19) has changed our daily life in many ways and put heavy burden on our mental health. Having a predictive model of negative emotions during COVID-19 is of great importance for identifying potential risky population. To establish a neural predictive model achieving both good interpretability and predictivity, we have utilized a large-scale (n = 542) longitudinal dataset, alongside two independent samples for external validation. We built a predictive model based on psychologically meaningful resting state neural activities. The whole-brain resting-state neural activity and social-psychological profile of the subjects were obtained from Sept. to Dec. 2019 (Time 1). Their negative emotions were tracked and re-assessed twice, on Feb 22 (Time 2) and Apr 24 (Time 3), 2020, respectively. We first applied canonical correlation analysis on both the neural profiles and psychological profiles collected on Time 1, this step selects only the psychological meaningful neural patterns for later model construction. We then trained the neural predictive model using those identified features on data obtained on Time 2. It achieved a good prediction performance (r = 0.44, p = 8.13 × 10-27). The two most important neural predictors are associated with self-control and social interaction. This study established an effective neural prediction model of negative emotions, achieving good interpretability and predictivity. It will be useful for identifying potential risky population of emotional disorders related to COVID-19.
Prefrontal-amygdala emotion regulation and depression in multiple sclerosis

Abstract Depression is among the most common comorbidities in multiple sclerosis and has severe psychosocial consequences. Alterations in neural emotion regulation in amygdala and prefrontal cortex have been recognized as key mechanism of depression but never been investigated in multiple sclerosis depression. In this cross-sectional observational study, we employed a functional MRI task investigating neural emotion regulation by contrasting regulated versus unregulated negative stimulus perception in 16 persons with multiple sclerosis and depression (47.9 ± 11.8 years; 14 female) and 26 persons with multiple sclerosis but without depression (47.3 ± 11.7 years; 14 female). We tested the impact of depression and its interaction with lesions in amygdala-prefrontal fibre tracts on brain activity reflecting emotion regulation. A potential impact of sex, age, information processing speed, disease duration, overall lesion load, grey matter fraction, and treatment was taken into account in these analyses. Patients with depression were less able (i) to downregulate negative emotions than those without (t = −2.25, P = 0.012, β = −0.33) on a behavioural level according to self-report data and (ii) to downregulate activity in a left amygdala coordinate (t = 3.03, PFamily-wise error [FWE]-corrected = 0.017, β = 0.39). Moreover, (iii) an interdependent effect of depression and lesions in amygdala-prefrontal tracts on activity was found in two left amygdala coordinates (t = 3.53, pFWE = 0.007, β = 0.48; t = 3.21, pFWE = 0.0158, β = 0.49) and one right amygdala coordinate (t = 3.41, pFWE = 0.009, β = 0.51). Compatible with key elements of the cognitive depression theory formulated for idiopathic depression, our study demonstrates that depression in multiple sclerosis is characterized by impaired neurobehavioural emotion regulation. Complementing these findings, it shows that the relation between neural emotion regulation and depression is affected by lesion load, a key pathological feature of multiple sclerosis, located in amygdala-prefrontal tracts.
Quality of Beef Burgers Formulated with Fat Substitute in a Form of Freeze-Dried Hydrogel Enriched with Açai Oil

The growing number of people at high risk of cardiovascular disease development contributed to both changes in diets by consumers and the reformulation of food products by food producers. Cardiovascular diseases are caused by the i.a. consumption of meat that contains animal fat rich in saturated fatty acids (SFA). The use of fat substitutes in meat seems to be a promising tool for the reduction of cardiovascular disease occurrence. In the presented study, beef fat was replaced at 0 (CO), 25 (S-25%), 50 (S-50%), 75 (S-75%), and 100% (S-100%) by a fat substitute in a form of a lyophilized hydrogel emulsion enriched with encapsulated açai oil. The chemical (TBARS, volatile compound profile, fatty acid profile, pH), and physical (TPA, consumer rating, L*a*b* color, cooking loss) analyses were performed on raw and grilled burgers subjected to storage at cold conditions (4 °C) in days 0 and 7. Burgers formulated with hydrogels had a higher content of polyunsaturated fatty acids (PUFAs) of about 32% (p < 0.05) and reduced SFAs by 22%. Reformulation of the burger resulted in lower nutritional indices of the atherogenicity index (AI) (0.8 for CO, 0.3 for S-100%, p < 0.05) and thrombogenicity index (TI) (1.8 for CO, 0.6 for S-100%, p < 0.05), as well as led to an increased h/H ratio (1.3 for CO, 3.9 for S-100%, p < 0.05). Furthermore the application of freeze-dried hydrogels reduced cooking loss. Moreover, consumers did not observe significant differences (p < 0.05) between the control and S-25% and S-50% burgers. Thus, the use of lyophilized hydrogels formulated with konjac flour and sodium alginate and enriched with encapsulated acai oil can be successfully applied as a fat substitute in beef burgers.
Recent Advances in Production of Ecofriendly Polylactide (PLA)–Calcium Sulfate (Anhydrite II) Composites: From the Evidence of Filler Stability to the Effects of PLA Matrix and Filling on Key Properties

The melt–mixing of polylactide (PLA) with micro- and/or nanofillers is a key method used to obtain specific end-use characteristics and improvements of properties. So-called “insoluble” CaSO4 (CS) β-anhydrite II (AII) is a mineral filler recently considered for the industry of polymer composites. First, the study proves that AII made from natural gypsum by a specifically thermal treatment is highly stable compared to other CS forms. Then, PLAs of different isomer purity and molecular weights (for injection molding (IM) and extrusion), have been used to produce “green” composites filled with 20–40 wt. % AII. The composites show good thermal and mechanical properties, accounting for the excellent filler dispersion and stability. The stiffness of composites increases with the amount of filler, whereas their tensile strength is found to be dependent on PLA molecular weights. Interestingly, the impact resistance is improved by adding 20% AII into all investigated PLAs. Due to advanced kinetics of crystallization ascribed to the effects of AII and use of a PLA grade of high L-lactic acid isomer purity, the composites show after IM an impressive degree of crystallinity (DC), i.e., as high as 50%, while their Vicat softening temperature is remarkably increased to 160 °C, which are thermal properties of great interest for applications requiring elevated rigidity and heat resistance.